SYMBOL INDEX (7970 symbols across 690 files) FILE: 3rdparty/ctc_include/contrib/moderngpu/include/mgpuenums.h function namespace (line 37) | namespace mgpu { FILE: 3rdparty/ctc_include/contrib/moderngpu/include/util/static.h function namespace (line 67) | namespace mgpu { FILE: 3rdparty/ctc_include/detail/cpu_ctc.h function namespace (line 32) | namespace mxnet_warpctc { FILE: 3rdparty/ctc_include/detail/ctc_helper.h type ctcStatus_t (line 28) | typedef enum { type ctcComputeLocation (line 36) | typedef enum { function namespace (line 41) | namespace ctc_helper { FILE: 3rdparty/ctc_include/detail/gpu_ctc.h function namespace (line 26) | namespace mxnet_warpctc { FILE: 3rdparty/ctc_include/detail/gpu_ctc_kernels.h type CTASegReduce (line 30) | struct CTASegReduce { type CTASegReduce (line 247) | typedef CTASegReduce> Se... FILE: 3rdparty/miniz/miniz.c function mz_ulong (line 39) | mz_ulong mz_adler32(mz_ulong adler, const unsigned char *ptr, size_t buf... function mz_ulong (line 69) | mz_ulong mz_crc32(mz_ulong crc, const mz_uint8 *ptr, size_t buf_len) function mz_ulong (line 88) | mz_ulong mz_crc32(mz_ulong crc, const mz_uint8 *ptr, size_t buf_len) function mz_free (line 155) | void mz_free(void *p) function miniz_def_free_func (line 165) | void miniz_def_free_func(void *opaque, void *address) function mz_deflateInit (line 183) | int mz_deflateInit(mz_streamp pStream, int level) function mz_deflateInit2 (line 188) | int mz_deflateInit2(mz_streamp pStream, int level, int method, int windo... function mz_deflateReset (line 224) | int mz_deflateReset(mz_streamp pStream) function mz_deflate (line 233) | int mz_deflate(mz_streamp pStream, int flush) function mz_deflateEnd (line 291) | int mz_deflateEnd(mz_streamp pStream) function mz_ulong (line 303) | mz_ulong mz_deflateBound(mz_streamp pStream, mz_ulong source_len) function mz_compress2 (line 310) | int mz_compress2(unsigned char *pDest, mz_ulong *pDest_len, const unsign... function mz_compress (line 340) | int mz_compress(unsigned char *pDest, mz_ulong *pDest_len, const unsigne... function mz_ulong (line 345) | mz_ulong mz_compressBound(mz_ulong source_len) type inflate_state (line 350) | typedef struct function mz_inflateInit2 (line 359) | int mz_inflateInit2(mz_streamp pStream, int window_bits) function mz_inflateInit (line 395) | int mz_inflateInit(mz_streamp pStream) function mz_inflateReset (line 400) | int mz_inflateReset(mz_streamp pStream) function mz_inflate (line 426) | int mz_inflate(mz_streamp pStream, int flush) function mz_inflateEnd (line 538) | int mz_inflateEnd(mz_streamp pStream) function mz_uncompress (line 550) | int mz_uncompress(unsigned char *pDest, mz_ulong *pDest_len, const unsig... type tdefl_sym_freq (line 728) | typedef struct function tdefl_sym_freq (line 732) | static tdefl_sym_freq *tdefl_radix_sort_syms(mz_uint num_syms, tdefl_sym... function tdefl_calculate_minimum_redundancy (line 766) | static void tdefl_calculate_minimum_redundancy(tdefl_sym_freq *A, int n) function tdefl_huffman_enforce_max_code_size (line 826) | static void tdefl_huffman_enforce_max_code_size(int *pNum_codes, int cod... function tdefl_optimize_huffman_table (line 850) | static void tdefl_optimize_huffman_table(tdefl_compressor *d, int table_... function tdefl_start_dynamic_block (line 969) | static void tdefl_start_dynamic_block(tdefl_compressor *d) function tdefl_start_static_block (line 1056) | static void tdefl_start_static_block(tdefl_compressor *d) function mz_bool (line 1081) | static mz_bool tdefl_compress_lz_codes(tdefl_compressor *d) function mz_bool (line 1175) | static mz_bool tdefl_compress_lz_codes(tdefl_compressor *d) function mz_bool (line 1223) | static mz_bool tdefl_compress_block(tdefl_compressor *d, mz_bool static_... function tdefl_flush_block (line 1232) | static int tdefl_flush_block(tdefl_compressor *d, int flush) function mz_uint16 (line 1369) | static mz_uint16 TDEFL_READ_UNALIGNED_WORD(const mz_uint8* p) function mz_uint16 (line 1375) | static mz_uint16 TDEFL_READ_UNALIGNED_WORD2(const mz_uint16* p) function MZ_FORCEINLINE (line 1385) | static MZ_FORCEINLINE void tdefl_find_match(tdefl_compressor *d, mz_uint... function MZ_FORCEINLINE (line 1438) | static MZ_FORCEINLINE void tdefl_find_match(tdefl_compressor *d, mz_uint... function mz_uint32 (line 1485) | static mz_uint32 TDEFL_READ_UNALIGNED_WORD32(const mz_uint8* p) function mz_bool (line 1494) | static mz_bool tdefl_compress_fast(tdefl_compressor *d) function MZ_FORCEINLINE (line 1668) | static MZ_FORCEINLINE void tdefl_record_literal(tdefl_compressor *d, mz_... function MZ_FORCEINLINE (line 1681) | static MZ_FORCEINLINE void tdefl_record_match(tdefl_compressor *d, mz_ui... function mz_bool (line 1711) | static mz_bool tdefl_compress_normal(tdefl_compressor *d) function tdefl_status (line 1856) | static tdefl_status tdefl_flush_output_buffer(tdefl_compressor *d) function tdefl_status (line 1877) | tdefl_status tdefl_compress(tdefl_compressor *d, const void *pIn_buf, si... function tdefl_status (line 1945) | tdefl_status tdefl_compress_buffer(tdefl_compressor *d, const void *pIn_... function tdefl_status (line 1951) | tdefl_status tdefl_init(tdefl_compressor *d, tdefl_put_buf_func_ptr pPut... function tdefl_status (line 1986) | tdefl_status tdefl_get_prev_return_status(tdefl_compressor *d) function mz_uint32 (line 1991) | mz_uint32 tdefl_get_adler32(tdefl_compressor *d) function mz_bool (line 1996) | mz_bool tdefl_compress_mem_to_output(const void *pBuf, size_t buf_len, t... type tdefl_output_buffer (line 2011) | typedef struct function mz_bool (line 2018) | static mz_bool tdefl_output_buffer_putter(const void *pBuf, int len, voi... function tdefl_compress_mem_to_mem (line 2058) | size_t tdefl_compress_mem_to_mem(void *pOut_buf, size_t out_buf_len, con... function mz_uint (line 2074) | mz_uint tdefl_create_comp_flags_from_zip_params(int level, int window_bi... function tdefl_compressor (line 2190) | tdefl_compressor *tdefl_compressor_alloc() function tdefl_compressor_free (line 2195) | void tdefl_compressor_free(tdefl_compressor *pComp) function tinfl_status (line 2381) | tinfl_status tinfl_decompress(tinfl_decompressor *r, const mz_uint8 *pIn... function tinfl_decompress_mem_to_mem (line 2892) | size_t tinfl_decompress_mem_to_mem(void *pOut_buf, size_t out_buf_len, c... function tinfl_decompress_mem_to_callback (line 2901) | int tinfl_decompress_mem_to_callback(const void *pIn_buf, size_t *pIn_bu... function tinfl_decompressor (line 2931) | tinfl_decompressor *tinfl_decompressor_alloc() function tinfl_decompressor_free (line 2939) | void tinfl_decompressor_free(tinfl_decompressor *pDecomp) function FILE (line 2990) | static FILE *mz_fopen(const char *pFilename, const char *pMode) function FILE (line 2996) | static FILE *mz_freopen(const char *pPath, const char *pMode, FILE *pStr... type mz_zip_array (line 3194) | typedef struct type mz_zip_internal_state_tag (line 3201) | struct mz_zip_internal_state_tag function MZ_FORCEINLINE (line 3228) | static MZ_FORCEINLINE mz_uint mz_zip_array_range_check(const mz_zip_arra... function MZ_FORCEINLINE (line 3238) | static MZ_FORCEINLINE void mz_zip_array_init(mz_zip_array *pArray, mz_ui... function MZ_FORCEINLINE (line 3244) | static MZ_FORCEINLINE void mz_zip_array_clear(mz_zip_archive *pZip, mz_z... function mz_bool (line 3250) | static mz_bool mz_zip_array_ensure_capacity(mz_zip_archive *pZip, mz_zip... function MZ_FORCEINLINE (line 3270) | static MZ_FORCEINLINE mz_bool mz_zip_array_reserve(mz_zip_archive *pZip,... function MZ_FORCEINLINE (line 3280) | static MZ_FORCEINLINE mz_bool mz_zip_array_resize(mz_zip_archive *pZip, ... function MZ_FORCEINLINE (line 3291) | static MZ_FORCEINLINE mz_bool mz_zip_array_ensure_room(mz_zip_archive *p... function MZ_FORCEINLINE (line 3296) | static MZ_FORCEINLINE mz_bool mz_zip_array_push_back(mz_zip_archive *pZi... function MZ_TIME_T (line 3307) | static MZ_TIME_T mz_zip_dos_to_time_t(int dos_time, int dos_date) function mz_zip_time_t_to_dos_time (line 3322) | static void mz_zip_time_t_to_dos_time(MZ_TIME_T time, mz_uint16 *pDOS_ti... function mz_bool (line 3345) | static mz_bool mz_zip_get_file_modified_time(const char *pFilename, MZ_T... function mz_bool (line 3359) | static mz_bool mz_zip_set_file_times(const char *pFilename, MZ_TIME_T ac... function MZ_FORCEINLINE (line 3372) | static MZ_FORCEINLINE mz_bool mz_zip_set_error(mz_zip_archive *pZip, mz_... function mz_bool (line 3379) | static mz_bool mz_zip_reader_init_internal(mz_zip_archive *pZip, mz_uint... function MZ_FORCEINLINE (line 3413) | static MZ_FORCEINLINE mz_bool mz_zip_reader_filename_less(const mz_zip_a... function mz_zip_reader_sort_central_dir_offsets_by_filename (line 3442) | static void mz_zip_reader_sort_central_dir_offsets_by_filename(mz_zip_ar... function mz_bool (line 3494) | static mz_bool mz_zip_reader_locate_header_sig(mz_zip_archive *pZip, mz_... function mz_bool (line 3540) | static mz_bool mz_zip_reader_read_central_dir(mz_zip_archive *pZip, mz_u... function mz_zip_zero_struct (line 3792) | void mz_zip_zero_struct(mz_zip_archive *pZip) function mz_bool (line 3798) | static mz_bool mz_zip_reader_end_internal(mz_zip_archive *pZip, mz_bool ... function mz_bool (line 3845) | mz_bool mz_zip_reader_end(mz_zip_archive *pZip) function mz_bool (line 3849) | mz_bool mz_zip_reader_init(mz_zip_archive *pZip, mz_uint64 size, mz_uint... function mz_zip_mem_read_func (line 3869) | static size_t mz_zip_mem_read_func(void *pOpaque, mz_uint64 file_ofs, vo... function mz_bool (line 3877) | mz_bool mz_zip_reader_init_mem(mz_zip_archive *pZip, const void *pMem, s... function mz_zip_file_read_func (line 3912) | static size_t mz_zip_file_read_func(void *pOpaque, mz_uint64 file_ofs, v... function mz_bool (line 3925) | mz_bool mz_zip_reader_init_file(mz_zip_archive *pZip, const char *pFilen... function mz_bool (line 3930) | mz_bool mz_zip_reader_init_file_v2(mz_zip_archive *pZip, const char *pFi... function mz_bool (line 3984) | mz_bool mz_zip_reader_init_cfile(mz_zip_archive *pZip, MZ_FILE *pFile, m... function MZ_FORCEINLINE (line 4026) | static MZ_FORCEINLINE const mz_uint8 *mz_zip_get_cdh(mz_zip_archive *pZi... function mz_bool (line 4033) | mz_bool mz_zip_reader_is_file_encrypted(mz_zip_archive *pZip, mz_uint fi... function mz_bool (line 4047) | mz_bool mz_zip_reader_is_file_supported(mz_zip_archive *pZip, mz_uint fi... function mz_bool (line 4083) | mz_bool mz_zip_reader_is_file_a_directory(mz_zip_archive *pZip, mz_uint ... function mz_bool (line 4115) | static mz_bool mz_zip_file_stat_internal(mz_zip_archive *pZip, mz_uint f... function MZ_FORCEINLINE (line 4235) | static MZ_FORCEINLINE mz_bool mz_zip_string_equal(const char *pA, const ... function MZ_FORCEINLINE (line 4246) | static MZ_FORCEINLINE int mz_zip_filename_compare(const mz_zip_array *pC... function mz_bool (line 4263) | static mz_bool mz_zip_locate_file_binary_search(mz_zip_archive *pZip, co... function mz_zip_reader_locate_file (line 4303) | int mz_zip_reader_locate_file(mz_zip_archive *pZip, const char *pName, c... function mz_bool (line 4312) | mz_bool mz_zip_reader_locate_file_v2(mz_zip_archive *pZip, const char *p... function mz_bool (line 4377) | mz_bool mz_zip_reader_extract_to_mem_no_alloc(mz_zip_archive *pZip, mz_u... function mz_bool (line 4520) | mz_bool mz_zip_reader_extract_file_to_mem_no_alloc(mz_zip_archive *pZip,... function mz_bool (line 4528) | mz_bool mz_zip_reader_extract_to_mem(mz_zip_archive *pZip, mz_uint file_... function mz_bool (line 4533) | mz_bool mz_zip_reader_extract_file_to_mem(mz_zip_archive *pZip, const ch... function mz_bool (line 4592) | mz_bool mz_zip_reader_extract_to_callback(mz_zip_archive *pZip, mz_uint ... function mz_bool (line 4790) | mz_bool mz_zip_reader_extract_file_to_callback(mz_zip_archive *pZip, con... function mz_zip_reader_extract_iter_state (line 4799) | mz_zip_reader_extract_iter_state* mz_zip_reader_extract_iter_new(mz_zip_... function mz_zip_reader_extract_iter_state (line 4927) | mz_zip_reader_extract_iter_state* mz_zip_reader_extract_file_iter_new(mz... function mz_zip_reader_extract_iter_read (line 4939) | size_t mz_zip_reader_extract_iter_read(mz_zip_reader_extract_iter_state*... function mz_bool (line 5056) | mz_bool mz_zip_reader_extract_iter_free(mz_zip_reader_extract_iter_state... function mz_zip_file_write_callback (line 5098) | static size_t mz_zip_file_write_callback(void *pOpaque, mz_uint64 ofs, c... function mz_bool (line 5105) | mz_bool mz_zip_reader_extract_to_file(mz_zip_archive *pZip, mz_uint file... function mz_bool (line 5139) | mz_bool mz_zip_reader_extract_file_to_file(mz_zip_archive *pZip, const c... function mz_bool (line 5148) | mz_bool mz_zip_reader_extract_to_cfile(mz_zip_archive *pZip, mz_uint fil... function mz_bool (line 5161) | mz_bool mz_zip_reader_extract_file_to_cfile(mz_zip_archive *pZip, const ... function mz_zip_compute_crc32_callback (line 5171) | static size_t mz_zip_compute_crc32_callback(void *pOpaque, mz_uint64 fil... function mz_bool (line 5179) | mz_bool mz_zip_validate_file(mz_zip_archive *pZip, mz_uint file_index, m... function mz_bool (line 5385) | mz_bool mz_zip_validate_archive(mz_zip_archive *pZip, mz_uint flags) function mz_bool (line 5438) | mz_bool mz_zip_validate_mem_archive(const void *pMem, size_t size, mz_ui... function mz_bool (line 5480) | mz_bool mz_zip_validate_file_archive(const char *pFilename, mz_uint flag... function MZ_FORCEINLINE (line 5526) | static MZ_FORCEINLINE void mz_write_le16(mz_uint8 *p, mz_uint16 v) function MZ_FORCEINLINE (line 5531) | static MZ_FORCEINLINE void mz_write_le32(mz_uint8 *p, mz_uint32 v) function MZ_FORCEINLINE (line 5538) | static MZ_FORCEINLINE void mz_write_le64(mz_uint8 *p, mz_uint64 v) function mz_zip_heap_write_func (line 5548) | static size_t mz_zip_heap_write_func(void *pOpaque, mz_uint64 file_ofs, ... function mz_bool (line 5586) | static mz_bool mz_zip_writer_end_internal(mz_zip_archive *pZip, mz_bool ... function mz_bool (line 5632) | mz_bool mz_zip_writer_init_v2(mz_zip_archive *pZip, mz_uint64 existing_s... function mz_bool (line 5681) | mz_bool mz_zip_writer_init(mz_zip_archive *pZip, mz_uint64 existing_size) function mz_bool (line 5686) | mz_bool mz_zip_writer_init_heap_v2(mz_zip_archive *pZip, size_t size_to_... function mz_bool (line 5714) | mz_bool mz_zip_writer_init_heap(mz_zip_archive *pZip, size_t size_to_res... function mz_zip_file_write_func (line 5720) | static size_t mz_zip_file_write_func(void *pOpaque, mz_uint64 file_ofs, ... function mz_bool (line 5736) | mz_bool mz_zip_writer_init_file(mz_zip_archive *pZip, const char *pFilen... function mz_bool (line 5741) | mz_bool mz_zip_writer_init_file_v2(mz_zip_archive *pZip, const char *pFi... function mz_bool (line 5788) | mz_bool mz_zip_writer_init_cfile(mz_zip_archive *pZip, MZ_FILE *pFile, m... function mz_bool (line 5809) | mz_bool mz_zip_writer_init_from_reader_v2(mz_zip_archive *pZip, const ch... function mz_bool (line 5896) | mz_bool mz_zip_writer_init_from_reader(mz_zip_archive *pZip, const char ... function mz_bool (line 5902) | mz_bool mz_zip_writer_add_mem(mz_zip_archive *pZip, const char *pArchive... type mz_zip_writer_add_state (line 5907) | typedef struct function mz_bool (line 5914) | static mz_bool mz_zip_writer_add_put_buf_callback(const void *pBuf, int ... function mz_uint32 (line 5927) | static mz_uint32 mz_zip_writer_create_zip64_extra_data(mz_uint8 *pBuf, m... function mz_bool (line 5962) | static mz_bool mz_zip_writer_create_local_dir_header(mz_zip_archive *pZi... function mz_bool (line 5980) | static mz_bool mz_zip_writer_create_central_dir_header(mz_zip_archive *p... function mz_bool (line 6005) | static mz_bool mz_zip_writer_add_to_central_dir(mz_zip_archive *pZip, co... function mz_bool (line 6045) | static mz_bool mz_zip_writer_validate_archive_name(const char *pArchive_... function mz_uint (line 6056) | static mz_uint mz_zip_writer_compute_padding_needed_for_file_alignment(m... function mz_bool (line 6065) | static mz_bool mz_zip_writer_write_zeros(mz_zip_archive *pZip, mz_uint64... function mz_bool (line 6081) | mz_bool mz_zip_writer_add_mem_ex(mz_zip_archive *pZip, const char *pArch... function mz_bool (line 6087) | mz_bool mz_zip_writer_add_mem_ex_v2(mz_zip_archive *pZip, const char *pA... function mz_bool (line 6373) | mz_bool mz_zip_writer_add_read_buf_callback(mz_zip_archive *pZip, const ... function mz_file_read_func_stdio (line 6678) | static size_t mz_file_read_func_stdio(void *pOpaque, mz_uint64 file_ofs,... function mz_bool (line 6689) | mz_bool mz_zip_writer_add_cfile(mz_zip_archive *pZip, const char *pArchi... function mz_bool (line 6696) | mz_bool mz_zip_writer_add_file(mz_zip_archive *pZip, const char *pArchiv... function mz_bool (line 6728) | static mz_bool mz_zip_writer_update_zip64_extension_block(mz_zip_array *... function mz_bool (line 6808) | mz_bool mz_zip_writer_add_from_zip_reader(mz_zip_archive *pZip, mz_zip_a... function mz_bool (line 7170) | mz_bool mz_zip_writer_finalize_archive(mz_zip_archive *pZip) function mz_bool (line 7258) | mz_bool mz_zip_writer_finalize_heap_archive(mz_zip_archive *pZip, void *... function mz_bool (line 7283) | mz_bool mz_zip_writer_end(mz_zip_archive *pZip) function mz_bool (line 7289) | mz_bool mz_zip_add_mem_to_archive_file_in_place(const char *pZip_filenam... function mz_bool (line 7294) | mz_bool mz_zip_add_mem_to_archive_file_in_place_v2(const char *pZip_file... function mz_zip_mode (line 7437) | mz_zip_mode mz_zip_get_mode(mz_zip_archive *pZip) function mz_zip_type (line 7442) | mz_zip_type mz_zip_get_type(mz_zip_archive *pZip) function mz_zip_error (line 7447) | mz_zip_error mz_zip_set_last_error(mz_zip_archive *pZip, mz_zip_error er... function mz_zip_error (line 7460) | mz_zip_error mz_zip_peek_last_error(mz_zip_archive *pZip) function mz_zip_error (line 7468) | mz_zip_error mz_zip_clear_last_error(mz_zip_archive *pZip) function mz_zip_error (line 7473) | mz_zip_error mz_zip_get_last_error(mz_zip_archive *pZip) function mz_bool (line 7562) | mz_bool mz_zip_is_zip64(mz_zip_archive *pZip) function mz_zip_get_central_dir_size (line 7570) | size_t mz_zip_get_central_dir_size(mz_zip_archive *pZip) function mz_uint (line 7578) | mz_uint mz_zip_reader_get_num_files(mz_zip_archive *pZip) function mz_uint64 (line 7583) | mz_uint64 mz_zip_get_archive_size(mz_zip_archive *pZip) function mz_uint64 (line 7590) | mz_uint64 mz_zip_get_archive_file_start_offset(mz_zip_archive *pZip) function MZ_FILE (line 7597) | MZ_FILE *mz_zip_get_cfile(mz_zip_archive *pZip) function mz_zip_read_archive_data (line 7604) | size_t mz_zip_read_archive_data(mz_zip_archive *pZip, mz_uint64 file_ofs... function mz_uint (line 7612) | mz_uint mz_zip_reader_get_filename(mz_zip_archive *pZip, mz_uint file_in... function mz_bool (line 7633) | mz_bool mz_zip_reader_file_stat(mz_zip_archive *pZip, mz_uint file_index... function mz_bool (line 7638) | mz_bool mz_zip_end(mz_zip_archive *pZip) FILE: 3rdparty/miniz/miniz.h type mz_ulong (line 225) | typedef unsigned long mz_ulong; type mz_internal_state (line 306) | struct mz_internal_state type mz_stream (line 309) | typedef struct mz_stream_s type mz_stream (line 331) | typedef mz_stream *mz_streamp; type Byte (line 427) | typedef unsigned char Byte; type uInt (line 428) | typedef unsigned int uInt; type mz_ulong (line 429) | typedef mz_ulong uLong; type Byte (line 430) | typedef Byte Bytef; type uInt (line 431) | typedef uInt uIntf; type charf (line 432) | typedef char charf; type intf (line 433) | typedef int intf; type uLong (line 435) | typedef uLong uLongf; type mz_uint8 (line 512) | typedef unsigned char mz_uint8; type mz_int16 (line 513) | typedef signed short mz_int16; type mz_uint16 (line 514) | typedef unsigned short mz_uint16; type mz_uint32 (line 515) | typedef unsigned int mz_uint32; type mz_uint (line 516) | typedef unsigned int mz_uint; type mz_int64 (line 517) | typedef int64_t mz_int64; type mz_uint64 (line 518) | typedef uint64_t mz_uint64; type mz_bool (line 519) | typedef int mz_bool; type mz_dummy_time_t (line 539) | typedef struct mz_dummy_time_t_tag type mz_bool (line 666) | typedef mz_bool (*tdefl_put_buf_func_ptr)(const void *pBuf, int len, voi... type tdefl_status (line 709) | typedef enum { type tdefl_flush (line 717) | typedef enum { type tdefl_compressor (line 725) | typedef struct type tinfl_decompressor_tag (line 826) | struct tinfl_decompressor_tag type tinfl_decompressor (line 827) | typedef struct tinfl_decompressor_tag tinfl_decompressor; type tinfl_status (line 841) | typedef enum { type tinfl_huff_table (line 898) | typedef struct type mz_uint64 (line 911) | typedef mz_uint64 tinfl_bit_buf_t; type mz_uint32 (line 914) | typedef mz_uint32 tinfl_bit_buf_t; type tinfl_decompressor_tag (line 918) | struct tinfl_decompressor_tag type mz_zip_archive_file_stat (line 950) | typedef struct type mz_bool (line 1008) | typedef mz_bool (*mz_file_needs_keepalive)(void *pOpaque); type mz_zip_internal_state_tag (line 1010) | struct mz_zip_internal_state_tag type mz_zip_internal_state (line 1011) | typedef struct mz_zip_internal_state_tag mz_zip_internal_state; type mz_zip_mode (line 1013) | typedef enum { type mz_zip_flags (line 1020) | typedef enum { type mz_zip_type (line 1032) | typedef enum { type mz_zip_error (line 1043) | typedef enum { type mz_zip_archive (line 1079) | typedef struct type mz_zip_reader_extract_iter_state (line 1106) | typedef struct FILE: 3rdparty/mshadow/guide/basic.cpp function main (line 27) | int main(void) { FILE: 3rdparty/mshadow/guide/defop.cpp type addone (line 29) | struct addone { method MSHADOW_XINLINE (line 32) | MSHADOW_XINLINE static DType Map(DType a) { type maxoftwo (line 37) | struct maxoftwo { method MSHADOW_XINLINE (line 40) | MSHADOW_XINLINE static float Map(float a, float b) { function main (line 46) | int main(void) { FILE: 3rdparty/mshadow/guide/mshadow-ps/dbstr.h function string (line 25) | string dbstr(mshadow::Tensor ts) { function string (line 34) | string dbstr(mshadow::Tensor ts) { function string (line 47) | string dbstr(mshadow::Tensor ts) { FILE: 3rdparty/mshadow/guide/mshadow-ps/dist_async_sum-inl.h function namespace (line 34) | namespace mshadow { FILE: 3rdparty/mshadow/guide/mshadow-ps/dist_async_sum.cpp function CreateServerNode (line 22) | int CreateServerNode(int argc, char *argv[]) { function WorkerNodeMain (line 28) | int WorkerNodeMain(int argc, char *argv[]) { FILE: 3rdparty/mshadow/guide/mshadow-ps/local_sum-inl.h function Print_ (line 28) | void Print_(mshadow::Tensor ts) { function namespace (line 93) | namespace mshadow { FILE: 3rdparty/mshadow/guide/mshadow-ps/local_sum.cpp function main (line 21) | int main(int argc, char *argv[]) { FILE: 3rdparty/mshadow/guide/neuralnet/util.h type real_t (line 26) | typedef float real_t; function pack (line 30) | int pack(unsigned char zz[4]){ function LoadMNIST (line 51) | inline void LoadMNIST(const char *path_img, const char *path_label, FILE: 3rdparty/mshadow/mshadow-ps/mshadow_ps.h function namespace (line 47) | namespace mshadow { function InvokeLambda_ (line 272) | inline static void InvokeLambda_(Stream *stream, void *fun) { function virtual (line 289) | virtual void SetParam(const char *name, const char *val) {} function virtual (line 296) | virtual void InitUpdater(int rank, int argc, char *argv[]) {} function virtual (line 303) | virtual void InitModel(int key, DType *dptr, size_t size) { function virtual (line 312) | virtual void Update(int key, DType *dptr, size_t size) { function virtual (line 332) | virtual void Update_(int key, Tensor data) { function namespace (line 349) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow-ps/ps_dist-inl.h function namespace (line 35) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow-ps/ps_local-inl.h type ms_omp_uint (line 35) | typedef int ms_omp_uint; type ms_omp_uint (line 37) | typedef unsigned ms_omp_uint; function namespace (line 44) | namespace mshadow { function Init (line 532) | inline void Init(int ndevice, Shape<2> shape, type PullEntry (line 580) | struct PullEntry { function PushHandlerGlobal (line 681) | inline void PushHandlerGlobal(void) { function PushHandlerLocal (line 694) | inline void PushHandlerLocal(size_t tid) { function MSHADOW_THREAD_PREFIX (line 705) | inline static MSHADOW_THREAD_PREFIX PushGlobalThread(void *pthread) { function MSHADOW_THREAD_PREFIX (line 710) | inline static MSHADOW_THREAD_PREFIX PushLocalThread(void *arg) { function PullProc (line 718) | inline void PullProc(utils::ThreadPQueue > *queue) { function PullHandlerGlobal (line 756) | inline void PullHandlerGlobal(void) { function PullHandlerLocal (line 769) | inline void PullHandlerLocal(size_t tid) { function MSHADOW_THREAD_PREFIX (line 780) | inline static MSHADOW_THREAD_PREFIX PullGlobalThread(void *arg) { function MSHADOW_THREAD_PREFIX (line 784) | inline static MSHADOW_THREAD_PREFIX PullLocalThread(void *arg) { function GetWorkIndex (line 792) | inline int GetWorkIndex(int devid) const { function InitPullMap (line 799) | inline void InitPullMap(int key) { function InitPushMap (line 817) | inline void InitPushMap(int key, Shape<2> shape) { FILE: 3rdparty/mshadow/mshadow-ps/ps_rabit-inl.h function namespace (line 34) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow-ps/thread.h function namespace (line 33) | namespace mshadow { function ThreadExit (line 121) | inline void ThreadExit(void *status) { function namespace (line 132) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow-ps/thread_util.h function namespace (line 32) | namespace mshadow { function Destroy (line 146) | inline void Destroy(void) { function TValue (line 153) | inline TValue *Get(int key) { function TValue (line 166) | inline TValue &GetRef(int key) { function Init (line 171) | inline void Init(int key) { FILE: 3rdparty/mshadow/mshadow/base.h type __int16 (line 52) | typedef __int16 int16_t; type __int32 (line 53) | typedef __int32 int32_t; type __int64 (line 54) | typedef __int64 int64_t; type index_t (line 326) | typedef int64_t index_t; type index_t (line 328) | typedef int32_t index_t; type openmp_index_t (line 333) | typedef int64_t openmp_index_t; type index_t (line 336) | typedef index_t openmp_index_t; type index_t (line 342) | typedef index_t lapack_index_t; type lapack_index_t (line 344) | typedef int lapack_index_t; type default_real_t (line 348) | typedef float default_real_t; type TypeFlag (line 351) | enum TypeFlag { function float (line 371) | struct DataType { function double (line 385) | struct DataType { function half_t (line 399) | struct DataType { function bf16_t (line 413) | struct DataType { function uint8_t (line 418) | struct DataType { function int8_t (line 433) | struct DataType { function int32_t (line 447) | struct DataType { function int64_t (line 461) | struct DataType { function bool (line 466) | struct DataType { function int16_t (line 471) | struct DataType { function uint16_t (line 476) | struct DataType { function uint32_t (line 481) | struct DataType { function uint64_t (line 486) | struct DataType { type LayoutFlag (line 498) | enum LayoutFlag { function LayoutFlag (line 514) | inline LayoutFlag layoutFlag(std::string layoutstr) { function std (line 545) | inline std::string toString(LayoutFlag layout) { function kNCHW (line 576) | struct LayoutType { function kNHWC (line 586) | struct LayoutType { function kNCDHW (line 599) | struct LayoutType { function kNDHWC (line 609) | struct LayoutType { function namespace (line 622) | namespace op { function namespace (line 678) | namespace sv { type plusto (line 694) | struct plusto { function AlphaBLAS (line 701) | AlphaBLAS(void) { return 1.0f; } function default_real_t (line 703) | inline static default_real_t BetaBLAS(void) { return 1.0f; } type op (line 705) | typedef op::plus OPType; type minimum (line 1108) | struct minimum { type DType (line 1167) | typedef float DType; type DType (line 1173) | typedef double DType; type mshadow (line 1179) | typedef mshadow::half::half_t DType; type mshadow (line 1185) | typedef mshadow::bfloat::bf16_t DType; type DType (line 1191) | typedef uint8_t DType; type DType (line 1197) | typedef int8_t DType; type DType (line 1203) | typedef int32_t DType; type DType (line 1209) | typedef int64_t DType; function mshadow_sizeof (line 1804) | inline size_t mshadow_sizeof(int type) { function std (line 1811) | inline std::string dtype_string(const int dtype) { FILE: 3rdparty/mshadow/mshadow/bfloat.h function namespace (line 31) | namespace mshadow { function MSHADOW_XINLINE (line 78) | static MSHADOW_XINLINE bf16_t Binary(uint16_t value) { function MSHADOW_XINLINE (line 84) | MSHADOW_XINLINE bf16_t() {} function MSHADOW_XINLINE (line 86) | MSHADOW_XINLINE bf16_t(const float& value) { constructor(value); } function MSHADOW_XINLINE (line 87) | MSHADOW_XINLINE explicit bf16_t(const double& value) { constructor(value... function MSHADOW_XINLINE (line 88) | MSHADOW_XINLINE explicit bf16_t(const int8_t& value) { constructor(value... function MSHADOW_XINLINE (line 89) | MSHADOW_XINLINE explicit bf16_t(const uint8_t& value) { constructor(valu... function MSHADOW_XINLINE (line 90) | MSHADOW_XINLINE explicit bf16_t(const int32_t& value) { constructor(valu... function MSHADOW_XINLINE (line 91) | MSHADOW_XINLINE explicit bf16_t(const uint32_t& value) { constructor(val... function MSHADOW_XINLINE (line 92) | MSHADOW_XINLINE explicit bf16_t(const int64_t& value) { constructor(valu... function MSHADOW_XINLINE (line 93) | MSHADOW_XINLINE explicit bf16_t(const uint64_t& value) { constructor(val... function MSHADOW_BF16_ASSIGNOP (line 95) | MSHADOW_BF16_CONVERSIONOP(float) FILE: 3rdparty/mshadow/mshadow/dot_engine-inl.h function namespace (line 36) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/expr_engine-inl.h function namespace (line 33) | namespace mshadow { function MSHADOW_XINLINE (line 105) | MSHADOW_XINLINE DType Eval(index_t y, index_t x) const { function explicit (line 117) | explicit Plan(const Plan &src) : src_(src) {} function MSHADOW_XINLINE (line 118) | MSHADOW_XINLINE DstDType Eval(index_t y, index_t x) const { function MSHADOW_XINLINE (line 133) | MSHADOW_XINLINE DType Eval(index_t y, index_t x) const { function explicit (line 146) | explicit Plan(const Plan &lhs, const Plan &rhs) function MSHADOW_XINLINE (line 148) | MSHADOW_XINLINE DType Eval(index_t y, index_t x) const { function explicit (line 160) | explicit Plan(const Plan &src) : src_(src) {} function MSHADOW_XINLINE (line 161) | MSHADOW_XINLINE DType Eval(index_t y, index_t x) const { function src_ (line 172) | src_(src) {} function MSHADOW_XINLINE (line 173) | MSHADOW_XINLINE DType Eval(index_t y, index_t x) const { function MSHADOW_XINLINE (line 185) | MSHADOW_XINLINE DType Eval(index_t y, index_t x) const { type TypeCheckPass (line 333) | struct TypeCheckPass type TypeCheckPass (line 335) | struct TypeCheckPass function Error_All_Tensor_in_Exp_Must_Have_Same_Type (line 336) | inline static void Error_All_Tensor_in_Exp_Must_Have_Same_Type(void) {} function Error_TypeCheck_Not_Pass_For_Reduce_Exp (line 337) | inline static void Error_TypeCheck_Not_Pass_For_Reduce_Exp(void) {} function Error_Expression_Does_Not_Meet_Dimension_Req (line 338) | inline static void Error_Expression_Does_Not_Meet_Dimension_Req(void) {} function namespace (line 451) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/expr_scalar-inl.h function namespace (line 34) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/expression.h function namespace (line 29) | namespace mshadow { function explicit (line 136) | explicit TransposeExp(const EType &e) : exp(e) {} function EType (line 138) | inline const EType &T(void) const { function Container (line 178) | inline Container &__assign(DType s) { function explicit (line 341) | explicit BinaryMapExp(const TA &lhs, const TB &rhs) function explicit (line 409) | explicit UnaryMapExp(const TA &src) : src_(src) {} FILE: 3rdparty/mshadow/mshadow/extension/broadcast.h function namespace (line 28) | namespace mshadow { function MSHADOW_XINLINE (line 145) | MSHADOW_XINLINE DType Eval(index_t y, index_t x) const { function explicit (line 158) | explicit Plan(const Broadcast1DExp &e) function MSHADOW_XINLINE (line 160) | MSHADOW_XINLINE DType Eval(index_t y, index_t x) const { function explicit (line 172) | explicit Plan(const BroadcastScalarExp &e) function MSHADOW_XINLINE (line 174) | MSHADOW_XINLINE DType Eval(index_t y, index_t x) const { FILE: 3rdparty/mshadow/mshadow/extension/broadcast_with_axis.h function namespace (line 31) | namespace mshadow { function src_ (line 148) | src_(src) { function MSHADOW_XINLINE (line 240) | MSHADOW_XINLINE DType Eval(index_t i, index_t j) const { FILE: 3rdparty/mshadow/mshadow/extension/channel_pool.h function namespace (line 29) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/extension/channel_unpool.h function namespace (line 29) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/extension/choose.h function namespace (line 30) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/extension/complex.h function namespace (line 30) | namespace mshadow { type exchange (line 76) | struct exchange { type pad_imag (line 90) | struct pad_imag { type toreal (line 104) | struct toreal { type abs_square (line 113) | struct abs_square { type sum_real_imag (line 123) | struct sum_real_imag { function namespace (line 135) | namespace expr { function explicit (line 173) | explicit ComplexUnitaryExp(const TA &src) : src_(src) {} function explicit (line 390) | explicit Plan(const Plan &lhs, const Plan &rhs) function MSHADOW_XINLINE (line 392) | MSHADOW_XINLINE DType Eval(index_t y, index_t x) const { function explicit (line 412) | explicit Plan(const Plan &lhs, const Plan &rhs) function MSHADOW_XINLINE (line 414) | MSHADOW_XINLINE DType Eval(index_t y, index_t x) const { function explicit (line 435) | explicit Plan(const Plan &lhs, const Plan &rhs) function MSHADOW_XINLINE (line 437) | MSHADOW_XINLINE DType Eval(index_t y, index_t x) const { function MSHADOW_XINLINE (line 459) | MSHADOW_XINLINE DType Eval(index_t y, index_t x) const { function MSHADOW_XINLINE (line 477) | MSHADOW_XINLINE DType Eval(index_t y, index_t x) const { function MSHADOW_XINLINE (line 498) | MSHADOW_XINLINE DType Eval(index_t y, index_t x) const { FILE: 3rdparty/mshadow/mshadow/extension/concat.h function namespace (line 29) | namespace mshadow { function MSHADOW_XINLINE (line 162) | MSHADOW_XINLINE DType &REval(index_t i, index_t j) { function MSHADOW_XINLINE (line 190) | MSHADOW_XINLINE DType Eval(index_t y, index_t x) const { function MSHADOW_XINLINE (line 197) | MSHADOW_XINLINE DType &REval(index_t y, index_t x) { FILE: 3rdparty/mshadow/mshadow/extension/crop.h function namespace (line 28) | namespace mshadow { function MSHADOW_XINLINE (line 121) | MSHADOW_XINLINE DType Eval(index_t i, index_t j) const { FILE: 3rdparty/mshadow/mshadow/extension/fill.h function namespace (line 31) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/extension/flip.h function namespace (line 30) | namespace mshadow { function MSHADOW_XINLINE (line 125) | MSHADOW_XINLINE DType Eval(index_t i, index_t j) const { function MSHADOW_XINLINE (line 134) | MSHADOW_XINLINE DType &REval(index_t i, index_t j) const { FILE: 3rdparty/mshadow/mshadow/extension/implicit_gemm.h function namespace (line 31) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/extension/mask.h function namespace (line 30) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/extension/mirror.h function namespace (line 28) | namespace mshadow { function explicit (line 68) | explicit Plan(const MirroringExp &e) function MSHADOW_XINLINE (line 70) | MSHADOW_XINLINE DType Eval(index_t i, index_t j) const { FILE: 3rdparty/mshadow/mshadow/extension/one_hot.h function namespace (line 31) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/extension/pack_col2patch.h function namespace (line 29) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/extension/pad.h function namespace (line 28) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/extension/range.h function namespace (line 30) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/extension/reduce_with_axis.h function namespace (line 30) | namespace mshadow { function MSHADOW_XINLINE (line 122) | MSHADOW_XINLINE DType Eval(index_t i, index_t j) const { FILE: 3rdparty/mshadow/mshadow/extension/reduceto1d.h function namespace (line 28) | namespace mshadow { function Eval (line 102) | inline static void Eval(Tensor *dst, FILE: 3rdparty/mshadow/mshadow/extension/reshape.h function namespace (line 28) | namespace mshadow { function MSHADOW_XINLINE (line 79) | MSHADOW_XINLINE DType Eval(index_t y, index_t x) const { function explicit (line 92) | explicit Plan(const ReshapeExp &e) function MSHADOW_XINLINE (line 95) | MSHADOW_XINLINE DType Eval(index_t y, index_t x) const { FILE: 3rdparty/mshadow/mshadow/extension/slice.h function namespace (line 29) | namespace mshadow { function MSHADOW_XINLINE (line 139) | MSHADOW_XINLINE DType &REval(index_t i, index_t j) { function explicit (line 158) | explicit Plan(const SliceExp &e) function MSHADOW_XINLINE (line 161) | MSHADOW_XINLINE DType Eval(index_t y, index_t x) const { function MSHADOW_XINLINE (line 164) | MSHADOW_XINLINE DType &REval(index_t y, index_t x) { FILE: 3rdparty/mshadow/mshadow/extension/slice_ex.h function namespace (line 29) | namespace mshadow { function MSHADOW_XINLINE (line 124) | MSHADOW_XINLINE DType Eval(index_t i, index_t j) const { function MSHADOW_XINLINE (line 135) | MSHADOW_XINLINE DType &REval(index_t i, index_t j) { FILE: 3rdparty/mshadow/mshadow/extension/spatial_pool.h function namespace (line 29) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/extension/spatial_unpool.h function namespace (line 29) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/extension/spatial_upsampling_nearest.h function namespace (line 29) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/extension/swapaxis.h function namespace (line 30) | namespace mshadow { function MSHADOW_XINLINE (line 113) | MSHADOW_XINLINE DType Eval(index_t i, index_t x) const { FILE: 3rdparty/mshadow/mshadow/extension/take.h function namespace (line 30) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/extension/take_grad.h function namespace (line 30) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/extension/transpose.h function namespace (line 29) | namespace mshadow { function MSHADOW_XINLINE (line 88) | MSHADOW_XINLINE DType Eval(index_t i, index_t j) const { function MSHADOW_XINLINE (line 176) | MSHADOW_XINLINE DType Eval(index_t i, index_t j) const { FILE: 3rdparty/mshadow/mshadow/extension/unpack_patch2col.h function namespace (line 28) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/half.h function MSHADOW_XINLINE (line 45) | MSHADOW_XINLINE float __half2float_warp(const volatile __half& h) { /* N... function namespace (line 60) | namespace mshadow { function half_t (line 82) | half_t operator AOP (const volatile T& a) volatile { \ function MSHADOW_XINLINE (line 121) | static MSHADOW_XINLINE half_t Binary(uint16_t value) { function MSHADOW_XINLINE (line 127) | MSHADOW_XINLINE half_t() {} function MSHADOW_XINLINE (line 130) | MSHADOW_XINLINE explicit half_t(const __half& value) { function MSHADOW_XINLINE (line 135) | MSHADOW_XINLINE half_t(const float& value) { constructor(value); } function MSHADOW_XINLINE (line 136) | MSHADOW_XINLINE explicit half_t(const double& value) { constructor(value... function MSHADOW_XINLINE (line 137) | MSHADOW_XINLINE explicit half_t(const int8_t& value) { constructor(value... function MSHADOW_XINLINE (line 138) | MSHADOW_XINLINE explicit half_t(const uint8_t& value) { constructor(valu... function MSHADOW_XINLINE (line 139) | MSHADOW_XINLINE explicit half_t(const int32_t& value) { constructor(valu... function MSHADOW_XINLINE (line 140) | MSHADOW_XINLINE explicit half_t(const uint32_t& value) { constructor(val... function MSHADOW_XINLINE (line 141) | MSHADOW_XINLINE explicit half_t(const int64_t& value) { constructor(valu... function MSHADOW_XINLINE (line 142) | MSHADOW_XINLINE explicit half_t(const uint64_t& value) { constructor(val... function MSHADOW_HALF_ASSIGNOP (line 144) | MSHADOW_HALF_CONVERSIONOP(float) function MSHADOW_XINLINE (line 215) | MSHADOW_XINLINE uint16_t float2half(const float& value) const { function MSHADOW_XINLINE (line 263) | MSHADOW_XINLINE uint16_t float2half(const volatile float& value) const v... function MSHADOW_XINLINE (line 303) | MSHADOW_XINLINE float half2float(const uint16_t& value) const { function MSHADOW_XINLINE (line 321) | MSHADOW_XINLINE float half2float(const volatile uint16_t& value) const v... function constructor (line 340) | void constructor(const T& value) { FILE: 3rdparty/mshadow/mshadow/io.h function namespace (line 29) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/packet-inl.h function namespace (line 37) | namespace mshadow { function namespace (line 69) | namespace mshadow { function MSHADOW_CINLINE (line 208) | MSHADOW_CINLINE static void Save(TFloat *dst, const Packet... function MSHADOW_CINLINE (line 216) | MSHADOW_CINLINE static void Save(TFloat *dst, const Packet... function namespace (line 228) | namespace mshadow { function explicit (line 265) | explicit PacketPlan(DType scalar) : scalar_(scalar) {} function MSHADOW_CINLINE (line 269) | MSHADOW_CINLINE DType Eval(index_t y, index_t x) const { function MSHADOW_CINLINE (line 285) | MSHADOW_CINLINE DType Eval(index_t y, index_t x) const { function src_ (line 297) | src_(src) {} function MSHADOW_CINLINE (line 298) | MSHADOW_CINLINE packet::Packet EvalPacket(index_t y, index_t x) c... function MSHADOW_CINLINE (line 301) | MSHADOW_CINLINE DType Eval(index_t y, index_t x) const { function Check (line 380) | inline static bool Check(const E &exp) { FILE: 3rdparty/mshadow/mshadow/packet/plain-inl.h function namespace (line 30) | namespace mshadow { function MSHADOW_CINLINE (line 61) | MSHADOW_CINLINE void Store(DType* dst) const { FILE: 3rdparty/mshadow/mshadow/packet/sse-inl.h function namespace (line 32) | namespace mshadow { function MSHADOW_CINLINE (line 63) | MSHADOW_CINLINE void Store(float* dst) const { function MSHADOW_CINLINE (line 67) | MSHADOW_CINLINE float Sum() const { function LoadUnAligned (line 98) | double, kSSE2> LoadUnAligned(const double* src) { function MSHADOW_CINLINE (line 107) | MSHADOW_CINLINE void Store(double* dst) const { function Sum (line 111) | inline double Sum(void) const { FILE: 3rdparty/mshadow/mshadow/random.h function namespace (line 38) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/stream_gpu-inl.h function namespace (line 32) | namespace mshadow { FILE: 3rdparty/mshadow/mshadow/tensor.h function namespace (line 37) | namespace mshadow { function MSHADOW_XINLINE (line 220) | MSHADOW_XINLINE Shape<1> Shape1(index_t s0) { function MSHADOW_XINLINE (line 230) | MSHADOW_XINLINE Shape<2> Shape2(index_t s0, index_t s1) { function MSHADOW_XINLINE (line 241) | MSHADOW_XINLINE Shape<3> Shape3(index_t s0, index_t s1, index_t s2) { function MSHADOW_XINLINE (line 254) | MSHADOW_XINLINE Shape<4> Shape4(index_t s0, index_t s1, function MSHADOW_XINLINE (line 269) | MSHADOW_XINLINE Shape<5> Shape5(index_t s0, index_t s1, index_t s2, function Shape (line 283) | inline Shape<3> ConvertLayout(const Shape<3>& src, int src_layout, int d... function Shape (line 320) | inline Shape<4> ConvertLayout(const Shape<4>& src, int src_layout, int d... function Shape (line 360) | inline Shape<5> ConvertLayout(const Shape<5>& src, int src_layout, int d... function Wait (line 495) | inline void Wait(void) {} function CheckIdle (line 500) | inline bool CheckIdle(void) { function CreateBlasHandle (line 504) | inline void CreateBlasHandle() {} function MSHADOW_XINLINE (line 556) | MSHADOW_XINLINE Tensor(void) : stream_(NULL) {} function MSHADOW_XINLINE (line 558) | MSHADOW_XINLINE Tensor(const Shape &shape) function index_t (line 584) | index_t MemSize(void) const { function MSHADOW_XINLINE (line 596) | MSHADOW_XINLINE bool CheckContiguous(void) const { function MSHADOW_XINLINE (line 602) | MSHADOW_XINLINE index_t MSize(void) const { function MSHADOW_XINLINE (line 610) | MSHADOW_XINLINE index_t size(int idx) const { function MSHADOW_XINLINE (line 681) | MSHADOW_XINLINE Tensor(void) : stream_(NULL) {} function MSHADOW_XINLINE (line 682) | MSHADOW_XINLINE Tensor(const Shape<1> &shape) function MSHADOW_XINLINE (line 705) | MSHADOW_XINLINE bool CheckContiguous(void) const { function MSHADOW_XINLINE (line 708) | MSHADOW_XINLINE index_t MSize(void) const { function MSHADOW_XINLINE (line 711) | MSHADOW_XINLINE index_t size(index_t i) const { function MSHADOW_XINLINE (line 714) | MSHADOW_XINLINE DType &operator[](index_t idx) { function MSHADOW_XINLINE (line 717) | MSHADOW_XINLINE const DType &operator[](index_t idx) const { FILE: 3rdparty/mshadow/mshadow/tensor_container.h function namespace (line 30) | namespace mshadow { function Resize (line 99) | inline void Resize(const Shape &shape) { function Resize (line 117) | inline void Resize(const Shape &shape, DType initv) { function set_pad (line 122) | inline void set_pad(bool pad) { function Release (line 190) | inline void Release(void) { function AllocByShape (line 212) | inline void AllocByShape(const Shape& shape) { FILE: 3rdparty/mshadow/mshadow/tensor_cpu-inl.h function namespace (line 36) | namespace mshadow { function size (line 78) | size_t size) { function size (line 90) | size_t size) { type Shape (line 260) | typedef Shape::kDim> EShape; FILE: 3rdparty/mshadow/mshadow/tensor_gpu-inl.h function namespace (line 30) | namespace mshadow { function namespace (line 118) | namespace mshadow { type Shape (line 160) | typedef Shape::kDim> EShape; function alpha (line 215) | float alpha) { FILE: benchmark/opperf/custom_operations/custom_operations.py class CustomAddOne (line 29) | class CustomAddOne(mx.operator.CustomOp): method forward (line 30) | def forward(self, is_train, req, in_data, out_data, aux): method backward (line 33) | def backward(self, req, out_grad, in_data, out_data, in_grad, aux): class CustomAddOneProp (line 38) | class CustomAddOneProp(mx.operator.CustomOpProp): method __init__ (line 39) | def __init__(self): method list_arguments (line 42) | def list_arguments(self): method list_outputs (line 45) | def list_outputs(self): method infer_shape (line 48) | def infer_shape(self, in_shape): method create_operator (line 52) | def create_operator(self, ctx, shapes, dtypes): FILE: benchmark/opperf/nd_operations/array_manipulation_operators.py function run_rearrange_operators_benchmarks (line 72) | def run_rearrange_operators_benchmarks(ctx=mx.cpu(), dtype='float32', pr... function run_shape_operators_benchmarks (line 104) | def run_shape_operators_benchmarks(ctx=mx.cpu(), dtype='float32', profil... function run_expanding_operators_benchmarks (line 136) | def run_expanding_operators_benchmarks(ctx=mx.cpu(), dtype='float32', pr... function run_rounding_operators_benchmarks (line 168) | def run_rounding_operators_benchmarks(ctx=mx.cpu(), dtype='float32', pro... function run_join_split_operators_benchmarks (line 200) | def run_join_split_operators_benchmarks(ctx=mx.cpu(), dtype='float32', p... FILE: benchmark/opperf/nd_operations/array_rearrange.py function run_rearrange_operators_benchmarks (line 32) | def run_rearrange_operators_benchmarks(ctx=mx.cpu(), dtype='float32', pr... FILE: benchmark/opperf/nd_operations/binary_operators.py function run_mx_binary_misc_operators_benchmarks (line 41) | def run_mx_binary_misc_operators_benchmarks(ctx=mx.cpu(), dtype='float32... function run_mx_binary_broadcast_operators_benchmarks (line 72) | def run_mx_binary_broadcast_operators_benchmarks(ctx=mx.cpu(), dtype='fl... function run_mx_binary_element_wise_operators_benchmarks (line 103) | def run_mx_binary_element_wise_operators_benchmarks(ctx=mx.cpu(), dtype=... FILE: benchmark/opperf/nd_operations/gemm_operators.py function run_gemm_operators_benchmarks (line 38) | def run_gemm_operators_benchmarks(ctx=mx.cpu(), dtype='float32', profile... FILE: benchmark/opperf/nd_operations/indexing_routines.py function run_indexing_routines_benchmarks (line 38) | def run_indexing_routines_benchmarks(ctx=mx.cpu(), dtype='float32', prof... FILE: benchmark/opperf/nd_operations/linalg_operators.py function run_linalg_operators_benchmarks (line 37) | def run_linalg_operators_benchmarks(ctx=mx.cpu(), dtype='float32', profi... FILE: benchmark/opperf/nd_operations/misc_operators.py function run_mx_misc_operators_benchmarks (line 40) | def run_mx_misc_operators_benchmarks(ctx=mx.cpu(), dtype='float32', prof... FILE: benchmark/opperf/nd_operations/nn_activation_operators.py function run_activation_operators_benchmarks (line 48) | def run_activation_operators_benchmarks(ctx=mx.cpu(), dtype='float32', p... FILE: benchmark/opperf/nd_operations/nn_basic_operators.py function run_nn_basic_operators_benchmarks (line 47) | def run_nn_basic_operators_benchmarks(ctx=mx.cpu(), dtype='float32', pro... FILE: benchmark/opperf/nd_operations/nn_conv_operators.py function run_pooling_operators_benchmarks (line 55) | def run_pooling_operators_benchmarks(ctx=mx.cpu(), dtype='float32', prof... function run_convolution_operators_benchmarks (line 153) | def run_convolution_operators_benchmarks(ctx=mx.cpu(), dtype='float32', ... function run_transpose_convolution_operators_benchmarks (line 249) | def run_transpose_convolution_operators_benchmarks(ctx=mx.cpu(), profile... FILE: benchmark/opperf/nd_operations/nn_loss_operators.py function run_loss_operators_benchmarks (line 31) | def run_loss_operators_benchmarks(ctx=mx.cpu(), dtype='float32', profile... FILE: benchmark/opperf/nd_operations/nn_optimizer_operators.py function run_optimizer_operators_benchmarks (line 57) | def run_optimizer_operators_benchmarks(ctx=mx.cpu(), dtype='float32', pr... FILE: benchmark/opperf/nd_operations/random_sampling_operators.py function run_mx_random_sampling_operators_benchmarks (line 37) | def run_mx_random_sampling_operators_benchmarks(ctx=mx.cpu(), dtype='flo... FILE: benchmark/opperf/nd_operations/reduction_operators.py function run_mx_reduction_operators_benchmarks (line 34) | def run_mx_reduction_operators_benchmarks(ctx=mx.cpu(), dtype='float32',... FILE: benchmark/opperf/nd_operations/sorting_searching_operators.py function run_sorting_searching_operators_benchmarks (line 32) | def run_sorting_searching_operators_benchmarks(ctx=mx.cpu(), dtype='floa... FILE: benchmark/opperf/nd_operations/unary_operators.py function run_mx_unary_operators_benchmarks (line 41) | def run_mx_unary_operators_benchmarks(ctx=mx.cpu(), dtype='float32', pro... FILE: benchmark/opperf/opperf.py function run_all_mxnet_operator_benchmarks (line 56) | def run_all_mxnet_operator_benchmarks(ctx=mx.cpu(), dtype='float32', pro... function _parse_mxnet_context (line 146) | def _parse_mxnet_context(ctx): function main (line 157) | def main(): FILE: benchmark/opperf/utils/benchmark_operators_pytest.py function generate_test_cases (line 56) | def generate_test_cases(): function generate_test_ids (line 63) | def generate_test_ids(): function test (line 105) | def test(op_name, shape, params): FILE: benchmark/opperf/utils/benchmark_utils.py function _prepare_op_inputs (line 33) | def _prepare_op_inputs(inputs, run_backward, dtype, ctx, module): function get_mx_np_ndarray (line 56) | def get_mx_np_ndarray(ctx, in_tensor, dtype, initializer, attach_grad=Tr... function adjust_op_name (line 104) | def adjust_op_name(module, name): function parse_input_ndarray (line 123) | def parse_input_ndarray(input_dict): function _run_operator_performance_test (line 173) | def _run_operator_performance_test(op, inputs, run_backward, warmup, run... function run_performance_test (line 206) | def run_performance_test(ops, inputs, run_backward=True, function run_benchmark_operator (line 257) | def run_benchmark_operator(name, size = (128,128), additional_inputs = {}, function run_op_benchmarks (line 283) | def run_op_benchmarks(ops, dtype, ctx, profiler, int64_tensor, warmup, r... FILE: benchmark/opperf/utils/common_utils.py function merge_map_list (line 26) | def merge_map_list(map_list): function save_to_file (line 52) | def save_to_file(inp_dict, out_filepath, out_format='json', runtime_feat... function get_json (line 82) | def get_json(inp_dict): function _prepare_op_benchmark_result (line 98) | def _prepare_op_benchmark_result(op, op_bench_result, profiler): function _prepare_markdown (line 135) | def _prepare_markdown(results, runtime_features=None, profiler='native'): FILE: benchmark/opperf/utils/ndarray_utils.py function nd_forward_backward_and_profile (line 23) | def nd_forward_backward_and_profile(op, runs, **kwargs): function nd_forward_and_profile (line 64) | def nd_forward_and_profile(op, runs, **kwargs): function get_mx_ndarray (line 102) | def get_mx_ndarray(ctx, in_tensor, dtype, initializer, attach_grad=True): FILE: benchmark/opperf/utils/op_registry_utils.py function _select_ops (line 26) | def _select_ops(operator_names, filters=("_contrib", "_"), merge_op_forw... function _set_op_arguments (line 80) | def _set_op_arguments(mx_operators): function _get_all_mxnet_operators (line 90) | def _get_all_mxnet_operators(): function prepare_op_inputs (line 100) | def prepare_op_inputs(arg_params, arg_values): function prepare_op_inputs (line 112) | def prepare_op_inputs(op, arg_params, int64_tensor): function get_all_unary_operators (line 214) | def get_all_unary_operators(): function get_all_broadcast_binary_operators (line 237) | def get_all_broadcast_binary_operators(): function get_all_misc_binary_operators (line 257) | def get_all_misc_binary_operators(): function get_all_elemen_wise_binary_operators (line 277) | def get_all_elemen_wise_binary_operators(): function get_all_random_sampling_operators (line 299) | def get_all_random_sampling_operators(): function get_all_linalg_operators (line 320) | def get_all_linalg_operators(): function get_all_reduction_operators (line 343) | def get_all_reduction_operators(): function get_all_nn_basic_operators (line 362) | def get_all_nn_basic_operators(): function get_all_nn_activation_operators (line 384) | def get_all_nn_activation_operators(): function get_all_optimizer_operators (line 404) | def get_all_optimizer_operators(): function get_all_sorting_searching_operators (line 426) | def get_all_sorting_searching_operators(): function get_all_rearrange_operators (line 446) | def get_all_rearrange_operators(): function get_remaining_miscellaneous_operators (line 467) | def get_remaining_miscellaneous_operators(): function get_all_indexing_routines (line 486) | def get_all_indexing_routines(): function get_all_loss_operators (line 512) | def get_all_loss_operators(): function get_all_shape_operators (line 532) | def get_all_shape_operators(): function get_all_expanding_operators (line 553) | def get_all_expanding_operators(): function get_all_rounding_operators (line 574) | def get_all_rounding_operators(): function get_operators_with_no_benchmark (line 595) | def get_operators_with_no_benchmark(operators_with_benchmark): function get_current_runtime_features (line 615) | def get_current_runtime_features(): FILE: benchmark/opperf/utils/profiler_utils.py function _get_memory_profile (line 34) | def _get_memory_profile(memory_profile_results): function _get_operator_profile (line 45) | def _get_operator_profile(operator_name, operator_profile_results): function parse_profiler_dump (line 84) | def parse_profiler_dump(operator_name, profiler_dump): function cpp_profile (line 171) | def cpp_profile(func): function python_profile (line 223) | def python_profile(func): FILE: benchmark/python/control_flow/rnn.py class ForeachRNN (line 39) | class ForeachRNN(gluon.HybridBlock): method __init__ (line 40) | def __init__(self, cell, length): method forward (line 45) | def forward(self, inputs, states): class WhileRNN (line 50) | class WhileRNN(gluon.HybridBlock): method __init__ (line 51) | def __init__(self, cell, length): method forward (line 56) | def forward(self, inputs, states): function _zeros (line 73) | def _zeros(shape, ctx): function _array (line 77) | def _array(shape, ctx): function _get_gpus (line 81) | def _get_gpus(): function run_benchmark (line 84) | def run_benchmark(cell_type, ctx, seq_len, batch_size, hidden_dim): function main (line 119) | def main(): FILE: benchmark/python/dnnl/fc_add.py function dump_graph_fn (line 42) | def dump_graph_fn(net, postfix): function operator_string (line 46) | def operator_string(elemwise_add): function print_header (line 49) | def print_header(header): function print_value (line 60) | def print_value(shape, hidden, mean): function measure (line 67) | def measure(net, data0, data1, data2, shape, nhid): class FCWithSum (line 82) | class FCWithSum(nn.HybridBlock): method __init__ (line 83) | def __init__(self, num_in, num_hidden, elemwise_add, **kwargs): method forward (line 89) | def forward(self, data0, data1, data2): function benchmark_float (line 100) | def benchmark_float(elemwise_add, broadcast=False): class CalibIter (line 118) | class CalibIter(mx.io.DataIter): method __init__ (line 119) | def __init__(self, batch, data_shape, batch_size): method __iter__ (line 129) | def __iter__(self): function benchmark_int8 (line 132) | def benchmark_int8(quantize_mode, quantize_granularity, elemwise_add, br... FILE: benchmark/python/einsum/benchmark_einsum.py function measure_cost (line 22) | def measure_cost(repeat, func_name, *args, **kwargs): function test_np_einsum (line 35) | def test_np_einsum(): FILE: benchmark/python/ffi/benchmark_ffi.py class OpArgMngr (line 22) | class OpArgMngr(object): method add_workload (line 27) | def add_workload(funcname, *args, **kwargs): function generate_workloads (line 38) | def generate_workloads(): function prepare_workloads (line 51) | def prepare_workloads(): function benchmark_helper (line 215) | def benchmark_helper(f, *args, **kwargs): function get_op (line 220) | def get_op(module, funcname): function run_benchmark (line 227) | def run_benchmark(packages): function show_results (line 242) | def show_results(results): FILE: benchmark/python/metric/benchmark_metric.py class MetricDataGen (line 26) | class MetricDataGen(object): method __init__ (line 28) | def __init__(self, n, c, pred_ctx, label_ctx): method data (line 34) | def data(self): method batch_size (line 41) | def batch_size(self): method output_dim (line 45) | def output_dim(self): class F1MetricDataGen (line 49) | class F1MetricDataGen(MetricDataGen): method __init__ (line 51) | def __init__(self, n, c, pred_ctx, label_ctx): class PearsonMetricDataGen (line 55) | class PearsonMetricDataGen(MetricDataGen): method __init__ (line 57) | def __init__(self, n, c, pred_ctx, label_ctx): method data (line 60) | def data(self): function run_metric (line 67) | def run_metric(name, data_gen_cls, i, n, c, pred_ctx, label_ctx, **kwargs): function test_metric_performance (line 84) | def test_metric_performance(): FILE: benchmark/python/quantization/benchmark_op.py function quantize_int8_helper (line 23) | def quantize_int8_helper(data): function benchmark_convolution (line 29) | def benchmark_convolution(data_shape, kernel, num_filter, pad, stride, n... FILE: benchmark/python/sparse/cast_storage.py function measure_cost (line 32) | def measure_cost(repeat, f, *args, **kwargs): function run_cast_storage_synthetic (line 42) | def run_cast_storage_synthetic(): FILE: benchmark/python/sparse/dot.py function measure_cost (line 110) | def measure_cost(repeat, scipy_trans_lhs, scipy_dns_lhs, func_name, *arg... function _get_iter (line 128) | def _get_iter(path, data_shape, batch_size): function _line_count (line 136) | def _line_count(path): function _compare_sparse_dense (line 140) | def _compare_sparse_dense(data_dir, file_name, mini_file_name, feature_dim, function test_dot_real (line 199) | def test_dot_real(data_dict): function test_dot_synthetic (line 259) | def test_dot_synthetic(data_dict): FILE: benchmark/python/sparse/memory_benchmark.py function parse_args (line 28) | def parse_args(): function main (line 62) | def main(): function bench_dot (line 79) | def bench_dot(lhs_row_dim, lhs_col_dim, rhs_col_dim, density, FILE: benchmark/python/sparse/sparse_op.py function measure_cost (line 58) | def measure_cost(repeat, f, *args, **kwargs): function test_dot_real (line 71) | def test_dot_real(data_dict): function test_dot_synthetic (line 136) | def test_dot_synthetic(): FILE: benchmark/python/sparse/util.py function estimate_density (line 21) | def estimate_density(DATA_PATH, feature_size): FILE: benchmark/python/tvmop/benchmark_tvmop.py function measure_cost (line 23) | def measure_cost(repeat, func_name, *args, **kwargs): function test_tvm_dot (line 36) | def test_tvm_dot(): FILE: cd/python/pypi/pypi_publish.py function post_wheel (line 31) | def post_wheel(path): function get_secret (line 60) | def get_secret(): FILE: cd/utils/artifact_repository.py function config_logging (line 47) | def config_logging(): function s3_upload (line 56) | def s3_upload(bucket: str, s3_key_prefix: str, paths: List[str]): function write_libmxnet_meta (line 71) | def write_libmxnet_meta(args: argparse.Namespace, destination: str): function try_s3_download (line 87) | def try_s3_download(bucket, s3_key_prefix, destination) -> bool: function get_commit_id_from_cmd (line 128) | def get_commit_id_from_cmd() -> Optional[str]: function probe_commit_id (line 144) | def probe_commit_id() -> str: function get_linux_os_release_properties (line 164) | def get_linux_os_release_properties() -> Optional[Dict[str, str]]: function get_linux_distribution_and_version (line 185) | def get_linux_distribution_and_version() -> Optional[str]: function probe_operating_system (line 204) | def probe_operating_system() -> str: function get_libmxnet_features (line 219) | def get_libmxnet_features(libmxnet_path: str) -> Optional[Dict[str, bool]]: function get_cuda_version (line 259) | def get_cuda_version() -> Optional[str]: function probe_cpu_variant (line 287) | def probe_cpu_variant(mxnet_features: Dict[str, bool]) -> str: function probe_gpu_variant (line 302) | def probe_gpu_variant(mxnet_features: Dict[str, bool]) -> Optional[str]: function probe_mxnet_variant (line 323) | def probe_mxnet_variant(limxnet_path: str) -> Optional[str]: function probe_artifact_repository_bucket (line 340) | def probe_artifact_repository_bucket() -> Optional[str]: function probe (line 352) | def probe(args: argparse.Namespace) -> argparse.Namespace: function get_s3_key_prefix (line 392) | def get_s3_key_prefix(args: argparse.Namespace, subdir: str = '') -> str: function push_artifact (line 405) | def push_artifact(args: argparse.Namespace): function pull_artifact (line 450) | def pull_artifact(args: argparse.Namespace): function is_file (line 480) | def is_file(path: str) -> str: function sanitize_path_array (line 492) | def sanitize_path_array(paths: List[str]) -> List[str]: function main (line 503) | def main() -> int: FILE: cd/utils/test_artifact_repository.py class TestArtifactRepositoryTool (line 26) | class TestArtifactRepositoryTool(unittest.TestCase): method create_argparse_namespace (line 29) | def create_argparse_namespace(libmxnet_path: Optional[str] = 'path_to_... method test_get_commit_id_from_cmd_returns_none_on_fail (line 53) | def test_get_commit_id_from_cmd_returns_none_on_fail(self, mock): method test_probe_commit_id_mxnet_sha (line 61) | def test_probe_commit_id_mxnet_sha(self): method test_probe_commit_id_git_commit (line 68) | def test_probe_commit_id_git_commit(self): method test_probe_commit_id_git_cmd (line 80) | def test_probe_commit_id_git_cmd(self, mock): method test_get_linux_os_release_properties (line 88) | def test_get_linux_os_release_properties(self): method test_get_linux_os_release_properties_with_quotes (line 101) | def test_get_linux_os_release_properties_with_quotes(self): method test_probe_operating_system_windows (line 116) | def test_probe_operating_system_windows(self, mock): method test_probe_operating_system_darwin (line 121) | def test_probe_operating_system_darwin(self, mock): method test_probe_operating_system_linux (line 127) | def test_probe_operating_system_linux(self, mock_props, mock_sys): method test_get_cuda_version (line 138) | def test_get_cuda_version(self, mock): method test_get_cuda_version_not_found (line 152) | def test_get_cuda_version_not_found(self, mock): method test_probe_variant_native (line 162) | def test_probe_variant_native(self, mock_features): method test_probe_variant_cpu (line 170) | def test_probe_variant_cpu(self, mock_features): method test_probe_variant_cuda (line 179) | def test_probe_variant_cuda(self, mock_cuda_version, mock_features): method test_probe_variant_cuda_returns_none_on_no_features (line 188) | def test_probe_variant_cuda_returns_none_on_no_features(self, mock_fea... method test_probe_variant_cuda_mkl (line 197) | def test_probe_variant_cuda_mkl(self, mock_cuda_version, mock_features): method test_probe_artifact_repository_bucket (line 206) | def test_probe_artifact_repository_bucket(self): method test_probe_no_commit_id (line 214) | def test_probe_no_commit_id(self, mock): method test_probe_no_commit_id_failed (line 225) | def test_probe_no_commit_id_failed(self, mock): method test_probe_no_operating_system (line 236) | def test_probe_no_operating_system(self, mock): method test_probe_no_operating_system_failed (line 247) | def test_probe_no_operating_system_failed(self, mock): method test_probe_no_variant (line 257) | def test_probe_no_variant(self, mock): method test_probe_no_mxnet_variant_failed (line 268) | def test_probe_no_mxnet_variant_failed(self, mock): method test_probe_no_bucket (line 278) | def test_probe_no_bucket(self, mock): method test_probe_no_bucket_failed (line 289) | def test_probe_no_bucket_failed(self, mock): method test_get_s3_key_prefix (line 298) | def test_get_s3_key_prefix(self): method test_get_s3_key_prefix_with_subdir (line 309) | def test_get_s3_key_prefix_with_subdir(self): method test_try_s3_download_fails_on_bad_response (line 321) | def test_try_s3_download_fails_on_bad_response(self, mock_s3): method test_try_s3_download_returns_false_on_no_keys (line 334) | def test_try_s3_download_returns_false_on_no_keys(self, mock_s3): method test_try_s3_download_with_destination (line 346) | def test_try_s3_download_with_destination(self, mock_s3, mock_makedirs): method test_try_s3_download (line 385) | def test_try_s3_download(self, mock_s3, mock_makedirs): method test_s3_upload (line 423) | def test_s3_upload(self, mock_s3): method test_is_file_is_file (line 447) | def test_is_file_is_file(self, mock_exists, mock_isfile): method test_is_file_not_file (line 457) | def test_is_file_not_file(self, mock_exists, mock_isfile): method test_is_file_not_found (line 466) | def test_is_file_not_found(self, mock_exists): method test_sanitize_path_array_empty_paths (line 475) | def test_sanitize_path_array_empty_paths(self): method test_sanitize_path_array_directories (line 483) | def test_sanitize_path_array_directories(self, mock_glob, mock_isfile): method test_write_libmxnet_meta (line 491) | def test_write_libmxnet_meta(self): method test_push_artifact_throws_no_license_error (line 506) | def test_push_artifact_throws_no_license_error(self): FILE: ci/build.py function get_platforms (line 40) | def get_platforms() -> List[str]: function get_docker_tag (line 46) | def get_docker_tag(platform: str, registry: str) -> str: function build_docker (line 52) | def build_docker(platform: str, registry: str, num_retries: int, no_cach... function buildir (line 83) | def buildir() -> str: function default_ccache_dir (line 87) | def default_ccache_dir() -> str: function container_run (line 106) | def container_run(platform: str, function list_platforms (line 181) | def list_platforms() -> str: function load_docker_cache (line 185) | def load_docker_cache(platform, tag, docker_registry) -> None: function log_environment (line 197) | def log_environment(): function main (line 205) | def main() -> int: FILE: ci/build_windows.py class BuildFlavour (line 49) | class BuildFlavour(Enum): function windows_build (line 141) | def windows_build(args): function windows_package (line 202) | def windows_package(args): function nix_build (line 229) | def nix_build(args): function main (line 245) | def main(): FILE: ci/dev_menu.py class Confirm (line 41) | class Confirm(object): method __init__ (line 42) | def __init__(self, cmds): method __call__ (line 45) | def __call__(self): class CMake (line 57) | class CMake(object): method __init__ (line 58) | def __init__(self, cmake_options_yaml=DEFAULT_CMAKE_OPTIONS, cmake_opt... method cmake_command (line 67) | def cmake_command(self) -> str: method __call__ (line 75) | def __call__(self, build_dir='build', generator='Ninja', build_cmd='ni... function create_virtualenv (line 89) | def create_virtualenv(venv_exe, pyexe, venv) -> None: function create_virtualenv_default (line 97) | def create_virtualenv_default(): function provision_virtualenv (line 102) | def provision_virtualenv(venv_path=DEFAULT_PYENV): function clip (line 163) | def clip(x, mini, maxi): function show_menu (line 167) | def show_menu(items: List[str], header=None) -> int: function handle_commands (line 182) | def handle_commands(cmds) -> None: function use_menu_ui (line 197) | def use_menu_ui(args) -> None: function build (line 205) | def build(args) -> None: function main (line 221) | def main(): FILE: ci/docker_login.py function _get_dockerhub_credentials (line 34) | def _get_dockerhub_credentials(secret_name: str, secret_endpoint_url: st... function login_dockerhub (line 64) | def login_dockerhub(secret_name: str, secret_endpoint_url: str, secret_e... function logout_dockerhub (line 89) | def logout_dockerhub(): function main (line 99) | def main(command_line_arguments): FILE: ci/publish/scala/buildkey.py function getCredentials (line 37) | def getCredentials(): function importASC (line 75) | def importASC(key, gpgPassphrase): function encryptMasterPSW (line 85) | def encryptMasterPSW(password): function encryptPSW (line 98) | def encryptPSW(password): function masterPSW (line 111) | def masterPSW(password): function serverPSW (line 117) | def serverPSW(username, password, gpgPassphrase): FILE: ci/test_docker_login.py function mock_boto (line 41) | def mock_boto(num_calls: int = 1): class TestDockerLogin (line 59) | class TestDockerLogin(unittest.TestCase): method test_docker_login_success (line 62) | def test_docker_login_success(self, mock_run): method test_docker_login_retry (line 95) | def test_docker_login_retry(self, mock_sleep, mock_run): method test_docker_login_retry_exhausted (line 134) | def test_docker_login_retry_exhausted(self, mock_sleep, mock_run): method test_docker_login_failed (line 166) | def test_docker_login_failed(self, mock_run): method test_logout (line 185) | def test_logout(self, mock_call): method test_main_exit (line 195) | def test_main_exit(self, mock_login): method test_main_default_argument_values (line 204) | def test_main_default_argument_values(self, mock_login): FILE: ci/util.py function get_mxnet_root (line 28) | def get_mxnet_root() -> str: function remember_cwd (line 43) | def remember_cwd(): function retry (line 52) | def retry(target_exception, tries=4, delay_s=1, backoff=2): function under_ci (line 92) | def under_ci() -> bool: function ec2_instance_info (line 97) | def ec2_instance_info() -> str: function chdir_to_script_directory (line 120) | def chdir_to_script_directory(): function script_name (line 127) | def script_name() -> str: function config_logging (line 132) | def config_logging(): function download_file (line 143) | def download_file(url, dest_path): function run_command (line 160) | def run_command(args, shell=False): FILE: conftest.py function pytest_configure (line 33) | def pytest_configure(config): function pytest_sessionfinish (line 41) | def pytest_sessionfinish(session, exitstatus): function pytest_runtest_makereport (line 47) | def pytest_runtest_makereport(item, call): function module_scope_waitall (line 62) | def module_scope_waitall(request): function module_scope_seed (line 76) | def module_scope_seed(request): function function_scope_seed (line 157) | def function_scope_seed(request): FILE: contrib/tvmop/basic/ufunc.py function compute_add (line 23) | def compute_add(dtype, ndim): function vadd (line 34) | def vadd(dtype, ndim): function vadd_gpu (line 45) | def vadd_gpu(dtype, ndim): function compute_backward_vadd (line 56) | def compute_backward_vadd(dtype, ndim, reduce1st, req): function backward_vadd (line 77) | def backward_vadd(dtype, ndim, reduce1st, req): function backward_vadd_gpu (line 89) | def backward_vadd_gpu(dtype, ndim, reduce1st, req): function compute_degandrad (line 103) | def compute_degandrad(dtype, ndim, n): function deg2rad (line 118) | def deg2rad(dtype, ndim): function rad2deg (line 128) | def rad2deg(dtype, ndim): function deg2rad_gpu (line 138) | def deg2rad_gpu(dtype, ndim): function rad2deg_gpu (line 151) | def rad2deg_gpu(dtype, ndim): function compute_backward_degandrad (line 162) | def compute_backward_degandrad(dtype, ndim, req, n): function backward_deg2rad (line 183) | def backward_deg2rad(dtype, ndim, req): function backward_rad2deg (line 195) | def backward_rad2deg(dtype, ndim, req): function cuda_backward_deg2rad (line 207) | def cuda_backward_deg2rad(dtype, ndim, req): function cuda_backward_rad2deg (line 224) | def cuda_backward_rad2deg(dtype, ndim, req): FILE: contrib/tvmop/compile.py function create_shared (line 37) | def create_shared(output, function _linux_compile (line 60) | def _linux_compile(output, objects, options, compile_cmd="g++"): function get_target (line 84) | def get_target(device): function get_cuda_arch (line 92) | def get_cuda_arch(arch): FILE: contrib/tvmop/core/fromnumeric.py function _compute_sum (line 24) | def _compute_sum(itype, otype, ndim, reduce1st_dim, req): function _sum_cpu (line 37) | def _sum_cpu(itype, otype, ndim, reduce1st_dim, req): function _sum_gpu (line 51) | def _sum_gpu(itype, otype, ndim, reduce1st_dim, req): FILE: contrib/tvmop/core/multiarray.py function compute_dot (line 24) | def compute_dot(A, B): function dot (line 36) | def dot(dtype, fallback): FILE: contrib/tvmop/core/umath.py function _compute_binary_logic (line 34) | def _compute_binary_logic(op, dtype, ndim): function _binary_logic_cpu (line 60) | def _binary_logic_cpu(compute_func, op, itype, ndim): function _binary_logic_gpu (line 68) | def _binary_logic_gpu(compute_func, op, itype, ndim): function _compute_binary_scalar_logic (line 99) | def _compute_binary_scalar_logic(op, dtype, ndim): FILE: contrib/tvmop/opdef.py class OpDef (line 26) | class OpDef: method __init__ (line 52) | def __init__(self, func, name, target, auto_broadcast, **kwargs): method __call__ (line 75) | def __call__(self, *args, **kwargs): method invoke_all (line 78) | def invoke_all(self): method get_op_name (line 104) | def get_op_name(self, name, args): method get_config_spaces (line 107) | def get_config_spaces(self): method get_binds (line 117) | def get_binds(self, args): function defop (line 124) | def defop(name, target=None, auto_broadcast=False, **kwargs): FILE: contrib/tvmop/space.py class OtherOptionSpace (line 23) | class OtherOptionSpace(object): method __init__ (line 25) | def __init__(self, entities): method from_tvm (line 29) | def from_tvm(cls, x): method __len__ (line 32) | def __len__(self): method __repr__ (line 35) | def __repr__(self): class OtherOptionEntity (line 39) | class OtherOptionEntity(object): method __init__ (line 41) | def __init__(self, val): method from_tvm (line 45) | def from_tvm(cls, x): method __repr__ (line 62) | def __repr__(self): class ConfigSpace (line 66) | class ConfigSpace(object): method __init__ (line 68) | def __init__(self, space_map, _entity_map): method from_tvm (line 74) | def from_tvm(cls, x): method __len__ (line 93) | def __len__(self): method __repr__ (line 99) | def __repr__(self): method to_json_dict (line 105) | def to_json_dict(self): method from_json_dict (line 129) | def from_json_dict(cls, json_dict): class ConfigSpaces (line 163) | class ConfigSpaces(object): method __init__ (line 165) | def __init__(self): method __setitem__ (line 168) | def __setitem__(self, name, space): method __len__ (line 171) | def __len__(self): method __repr__ (line 174) | def __repr__(self): method to_json_dict (line 180) | def to_json_dict(self): method from_json_dict (line 194) | def from_json_dict(cls, json_dict): FILE: contrib/tvmop/utils.py function assign_by_req (line 26) | def assign_by_req(a, req, otype=None): function reduce_axes (line 36) | def reduce_axes(X, axes, reducer, atype=None): FILE: cpp-package/example/alexnet.cpp function Symbol (line 32) | Symbol AlexnetSymbol(int num_classes) { function NDArray (line 199) | NDArray ResizeInput(NDArray data, const Shape new_shape) { function main (line 213) | int main(int argc, char const *argv[]) { FILE: cpp-package/example/charRNN.cpp type LSTMState (line 51) | struct LSTMState { type LSTMParam (line 56) | struct LSTMParam { function LSTMState (line 66) | LSTMState LSTM(int num_hidden, const Symbol& indata, const LSTMState& pr... function Symbol (line 87) | Symbol LSTMUnroll(int num_lstm_layer, int sequence_length, int input_dim, function Symbol (line 150) | Symbol LSTMWithBuiltInRNNOp(int num_lstm_layer, int sequence_length, int... class Shuffler (line 194) | class Shuffler { method Shuffler (line 197) | explicit Shuffler(int size) : sequence(size) { method shuffle (line 202) | void shuffle(std::function lambda = nullptr) { class BucketSentenceIter (line 216) | class BucketSentenceIter : public DataIter { method BucketSentenceIter (line 226) | BucketSentenceIter(std::string filename, int minibatch, Context contex... method maxSequenceLength (line 248) | unsigned int maxSequenceLength() { method characterSize (line 252) | size_t characterSize() { method Next (line 256) | virtual bool Next(void) { method NDArray (line 259) | virtual NDArray GetData(void) { method NDArray (line 274) | virtual NDArray GetLabel(void) { method GetPadNum (line 289) | virtual int GetPadNum(void) { method GetIndex (line 292) | virtual std::vector GetIndex(void) { method BeforeFirst (line 297) | virtual void BeforeFirst(void) { method readContent (line 302) | std::wstring readContent(const std::string file) { method buildCharIndex (line 312) | void buildCharIndex(const std::wstring& content) { method wchar_t (line 340) | inline wchar_t character(int i) { method mx_float (line 344) | inline mx_float index(wchar_t c) { method saveCharIndices (line 348) | void saveCharIndices(const std::string file) { method loadCharIndices (line 356) | static std::tuple, std::vector> function OutputPerplexity (line 389) | void OutputPerplexity(NDArray* labels, NDArray* output) { function SaveCheckpoint (line 407) | void SaveCheckpoint(const std::string filepath, Symbol net, Executor* ex... function LoadCheckpoint (line 419) | void LoadCheckpoint(const std::string filepath, Executor* exe) { function train (line 441) | void train(const std::string file, int batch_size, int max_epoch, int st... class RNNXavier (line 521) | class RNNXavier : public Xavier { method RNNXavier (line 523) | RNNXavier(RandType rand_type = gaussian, FactorType factor_type = avg, method InitDefault (line 528) | virtual void InitDefault(NDArray* arr) { function trainWithBuiltInRNNOp (line 533) | void trainWithBuiltInRNNOp(const std::string file, int batch_size, int m... function predict (line 596) | void predict(std::wstring* ptext, int sequence_length, const std::string... function predictWithBuiltInRNNOp (line 660) | void predictWithBuiltInRNNOp(std::wstring* ptext, int sequence_length, c... function main (line 716) | int main(int argc, char** argv) { FILE: cpp-package/example/feature_extract/feature_extract.cpp class FeatureExtractor (line 41) | class FeatureExtractor { method GetFeatureSymbol (line 51) | void GetFeatureSymbol() { method LoadParameters (line 65) | void LoadParameters() { method GetMeanImg (line 81) | void GetMeanImg() { method FeatureExtractor (line 90) | FeatureExtractor() { method Extract (line 97) | void Extract(NDArray data) { function NDArray (line 117) | NDArray Data2NDArray() { function main (line 128) | int main() { FILE: cpp-package/example/feature_extract/prepare_data_with_opencv.cpp function Mat2Array (line 31) | void Mat2Array() { function main (line 52) | int main(int argc, char *argv[]) { FILE: cpp-package/example/googlenet.cpp function Symbol (line 31) | Symbol ConvFactory(Symbol data, int num_filter, function Symbol (line 45) | Symbol InceptionFactory(Symbol data, int num_1x1, int num_3x3red, function Symbol (line 78) | Symbol GoogleNetSymbol(int num_classes) { function main (line 116) | int main(int argc, char const *argv[]) { FILE: cpp-package/example/inception_bn.cpp function Symbol (line 31) | Symbol ConvFactoryBN(Symbol data, int num_filter, function Symbol (line 49) | Symbol InceptionFactoryA(Symbol data, int num_1x1, int num_3x3red, function Symbol (line 79) | Symbol InceptionFactoryB(Symbol data, int num_3x3red, int num_3x3, function Symbol (line 103) | Symbol InceptionSymbol(int num_classes) { function NDArray (line 145) | NDArray ResizeInput(NDArray data, const Shape new_shape) { function main (line 159) | int main(int argc, char const *argv[]) { FILE: cpp-package/example/inference/imagenet_inference.cpp function ms_now (line 47) | double ms_now() { type TypeFlag (line 62) | enum TypeFlag { class Predictor (line 78) | class Predictor { method Predictor (line 80) | Predictor() {} method FileExists (line 111) | inline bool FileExists(const std::string &name) { function createVectorFromString (line 525) | std::vector createVectorFromString(const std::string& input_string) { function printUsage (line 548) | void printUsage() { function main (line 570) | int main(int argc, char** argv) { FILE: cpp-package/example/inference/multi_threaded_inference/get_model.py function download (line 27) | def download(url, fname=None, dirname=None, overwrite=False, retries=5): function download_model (line 97) | def download_model(model_name, dst_dir='./', meta_info=None): function main (line 163) | def main(): FILE: cpp-package/example/inference/multi_threaded_inference/multi_threaded_inference.cc function trim (line 43) | static std::string trim(const std::string& input) { function LoadSynset (line 51) | std::vector LoadSynset(const std::string& synset_file) { function PrintOutputResult (line 72) | void PrintOutputResult(const float* data, size_t size, const std::vector... function GetImageFile (line 92) | void GetImageFile(const std::string& image_file, function prepare_input_data (line 128) | void prepare_input_data(const mxnet::cpp::Shape& shape, function run_inference (line 145) | void run_inference(const std::string& model_name, function main (line 305) | int main(int argc, char* argv[]) { FILE: cpp-package/example/inference/sentiment_analysis_rnn.cpp class Predictor (line 55) | class Predictor { method Predictor (line 57) | Predictor() {} method FileExists (line 70) | inline bool FileExists(const std::string& name) { function printUsage (line 396) | void printUsage() { function DownloadFiles (line 413) | void DownloadFiles(const std::vector model_files) { function main (line 426) | int main(int argc, char** argv) { FILE: cpp-package/example/lenet.cpp function ctx_dev (line 39) | ctx_dev(Context(DeviceType::kGPU, 0)) function Run (line 43) | void Run(int max_epoch) { function GetData (line 189) | size_t GetData(std::vector *data, std::vector *label) { function ValAccuracy (line 209) | float ValAccuracy(int batch_size, Symbol lenet) { function main (line 260) | int main(int argc, char const *argv[]) { FILE: cpp-package/example/lenet_with_mxdataiter.cpp function Symbol (line 33) | Symbol LenetSymbol() { function NDArray (line 69) | NDArray ResizeInput(NDArray data, const Shape new_shape) { function main (line 79) | int main(int argc, char const *argv[]) { FILE: cpp-package/example/mlp.cpp function OutputAccuracy (line 37) | void OutputAccuracy(mx_float* pred, mx_float* target) { function MLP (line 53) | void MLP(int max_epoch) { function main (line 175) | int main(int argc, char** argv) { FILE: cpp-package/example/mlp_cpu.cpp function Symbol (line 29) | Symbol mlp(const std::vector &layers) { function main (line 51) | int main(int argc, char** argv) { FILE: cpp-package/example/mlp_csv.cpp function Symbol (line 37) | Symbol mlp(const std::vector &hidden_units) { function getLayers (line 61) | std::vector getLayers(const std::string& hidden_units_string) { function printUsage (line 73) | void printUsage() { function main (line 83) | int main(int argc, char** argv) { FILE: cpp-package/example/mlp_gpu.cpp function Symbol (line 29) | Symbol mlp(const std::vector &layers) { function main (line 51) | int main(int argc, char** argv) { FILE: cpp-package/example/mnist_to_csv.py function convert_to_csv (line 26) | def convert_to_csv(args): FILE: cpp-package/example/resnet.cpp function Symbol (line 32) | Symbol ConvolutionNoBias(const std::string& symbol_name, function Symbol (line 56) | Symbol getConv(const std::string & name, Symbol data, function Symbol (line 81) | Symbol makeBlock(const std::string & name, Symbol data, int num_filter, function Symbol (line 114) | Symbol getBody(Symbol data, int num_level, int num_block, int num_filter... function Symbol (line 125) | Symbol ResNetSymbol(int num_class, int num_level = 3, int num_block = 9, function NDArray (line 156) | NDArray ResizeInput(NDArray data, const Shape new_shape) { function main (line 170) | int main(int argc, char const *argv[]) { FILE: cpp-package/example/test_kvstore.cpp function test_single_key (line 24) | static bool test_single_key(const Context &context, const std::string &c... function test_multiple_key (line 83) | static bool test_multiple_key(const Context &context, const std::string ... function main (line 175) | int main(int argc, char** argv) { FILE: cpp-package/example/test_ndarray_copy.cpp type TypeFlag (line 26) | enum TypeFlag { function main (line 41) | int main(int argc, char** argv) { FILE: cpp-package/example/test_optimizer.cpp function main (line 27) | int main(int argc, char** argv) { FILE: cpp-package/example/test_regress_label.cpp function main (line 31) | int main() { FILE: cpp-package/example/test_score.cpp function Symbol (line 34) | Symbol mlp(const std::vector &layers) { function main (line 56) | int main(int argc, char** argv) { FILE: cpp-package/example/utils.h function isFileExists (line 39) | bool isFileExists(const std::string& filename) { function check_datafiles (line 44) | bool check_datafiles(const std::vector& data_files) { function setDataIter (line 54) | bool setDataIter(MXDataIter* iter, FILE: cpp-package/include/mxnet-cpp/base.h function namespace (line 33) | namespace mxnet { FILE: cpp-package/include/mxnet-cpp/contrib.h function namespace (line 34) | namespace mxnet { FILE: cpp-package/include/mxnet-cpp/executor.h function namespace (line 37) | namespace mxnet { FILE: cpp-package/include/mxnet-cpp/executor.hpp type mxnet (line 36) | namespace mxnet { type cpp (line 37) | namespace cpp { FILE: cpp-package/include/mxnet-cpp/initializer.h function class (line 38) | class Initializer { function class (line 119) | class Constant : public Initializer { function class (line 130) | class Zero : public Constant { function class (line 135) | class One : public Constant { function class (line 140) | class Uniform : public Initializer { FILE: cpp-package/include/mxnet-cpp/io.h function namespace (line 36) | namespace mxnet { FILE: cpp-package/include/mxnet-cpp/io.hpp type mxnet (line 32) | namespace mxnet { type cpp (line 33) | namespace cpp { function MXDataIterMap (line 35) | inline MXDataIterMap*& MXDataIter::mxdataiter_map() { function NDArray (line 57) | inline NDArray MXDataIter::GetData() { function NDArray (line 64) | inline NDArray MXDataIter::GetLabel() { function MXDataIter (line 88) | inline MXDataIter MXDataIter::CreateDataIter() { FILE: cpp-package/include/mxnet-cpp/kvstore.h function namespace (line 33) | namespace mxnet { FILE: cpp-package/include/mxnet-cpp/kvstore.hpp type mxnet (line 38) | namespace mxnet { type cpp (line 39) | namespace cpp { function KVStoreHandle (line 59) | inline KVStoreHandle& KVStore::get_handle() { function KVStore (line 69) | inline KVStore*& KVStore::get_kvstore() { FILE: cpp-package/include/mxnet-cpp/lr_scheduler.h function namespace (line 30) | namespace mxnet { FILE: cpp-package/include/mxnet-cpp/metric.h function namespace (line 37) | namespace cpp { FILE: cpp-package/include/mxnet-cpp/model.h function namespace (line 35) | namespace mxnet { FILE: cpp-package/include/mxnet-cpp/ndarray.h function namespace (line 37) | namespace mxnet { type NDBlob (line 92) | struct NDBlob { FILE: cpp-package/include/mxnet-cpp/ndarray.hpp type mxnet (line 38) | namespace mxnet { type cpp (line 39) | namespace cpp { function NDArray (line 96) | inline NDArray NDArray::operator+(mx_float scalar) { function NDArray (line 101) | inline NDArray NDArray::operator-(mx_float scalar) { function NDArray (line 106) | inline NDArray NDArray::operator*(mx_float scalar) { function NDArray (line 111) | inline NDArray NDArray::operator/(mx_float scalar) { function NDArray (line 116) | inline NDArray NDArray::operator%(mx_float scalar) { function NDArray (line 121) | inline NDArray NDArray::operator+(const NDArray &rhs) { function NDArray (line 126) | inline NDArray NDArray::operator-(const NDArray &rhs) { function NDArray (line 131) | inline NDArray NDArray::operator*(const NDArray &rhs) { function NDArray (line 136) | inline NDArray NDArray::operator/(const NDArray &rhs) { function NDArray (line 141) | inline NDArray NDArray::operator%(const NDArray &rhs) { function NDArray (line 146) | inline NDArray &NDArray::operator=(mx_float scalar) { function NDArray (line 150) | inline NDArray &NDArray::operator+=(mx_float scalar) { function NDArray (line 154) | inline NDArray &NDArray::operator-=(mx_float scalar) { function NDArray (line 158) | inline NDArray &NDArray::operator*=(mx_float scalar) { function NDArray (line 162) | inline NDArray &NDArray::operator/=(mx_float scalar) { function NDArray (line 166) | inline NDArray &NDArray::operator%=(mx_float scalar) { function NDArray (line 170) | inline NDArray &NDArray::operator+=(const NDArray &rhs) { function NDArray (line 174) | inline NDArray &NDArray::operator-=(const NDArray &rhs) { function NDArray (line 178) | inline NDArray &NDArray::operator*=(const NDArray &rhs) { function NDArray (line 182) | inline NDArray &NDArray::operator/=(const NDArray &rhs) { function NDArray (line 186) | inline NDArray &NDArray::operator%=(const NDArray &rhs) { function NDArray (line 191) | inline NDArray NDArray::ArgmaxChannel() { function NDArray (line 211) | inline NDArray NDArray::Copy(const Context &ctx) const { function NDArray (line 216) | inline NDArray NDArray::CopyTo(NDArray * other) const { function NDArray (line 220) | inline NDArray NDArray::Slice(mx_uint begin, mx_uint end) const { function NDArray (line 225) | inline NDArray NDArray::Reshape(const Shape &new_shape) const { function mx_float (line 390) | inline mx_float NDArray::At(size_t h, size_t w) const { function mx_float (line 394) | inline mx_float NDArray::At(size_t c, size_t h, size_t w) const { function mx_float (line 398) | inline mx_float NDArray::At(size_t index) const { function mx_float (line 428) | inline const mx_float *NDArray::GetData() const { function Context (line 437) | inline Context NDArray::GetContext() const { FILE: cpp-package/include/mxnet-cpp/op_map.h function namespace (line 34) | namespace mxnet { FILE: cpp-package/include/mxnet-cpp/op_suppl.h function namespace (line 37) | namespace mxnet { FILE: cpp-package/include/mxnet-cpp/op_util.h function namespace (line 36) | namespace mxnet { FILE: cpp-package/include/mxnet-cpp/operator.h function namespace (line 36) | namespace mxnet { FILE: cpp-package/include/mxnet-cpp/operator.hpp type mxnet (line 37) | namespace mxnet { type cpp (line 38) | namespace cpp { function Operator (line 45) | inline Operator& Operator::SetParam(int pos, const NDArray ... function Operator (line 50) | inline Operator& Operator::SetParam(int pos, const Symbol &v... function OpMap (line 55) | inline OpMap*& Operator::op_map() { function Symbol (line 82) | inline Symbol Operator::CreateSymbol(const std::string &name) { function Operator (line 163) | inline Operator &Operator::SetInput(const std::string &name, const S... function Operator (line 171) | inline Operator &Operator::SetInput(const std::string &name, const N... FILE: cpp-package/include/mxnet-cpp/optimizer.h function namespace (line 41) | namespace mxnet { FILE: cpp-package/include/mxnet-cpp/optimizer.hpp function _clip (line 44) | inline void _clip(mxnet::cpp::NDArray &data, float limit) { function _sqrt (line 51) | inline mxnet::cpp::NDArray _sqrt(mxnet::cpp::NDArray data) { type mxnet (line 59) | namespace mxnet { type cpp (line 60) | namespace cpp { function OpMap (line 73) | inline OpMap*& Optimizer::op_map() { function Optimizer (line 128) | inline Optimizer* OptimizerRegistry::Find(const std::string& name) { FILE: cpp-package/include/mxnet-cpp/shape.h function namespace (line 35) | namespace mxnet { function ndim_ (line 170) | Shape(const Shape& s) : ndim_(s.ndim_) { function CopyFrom (line 207) | void CopyFrom(RandomAccessIterator begin, RandomAccessIterator end) { function index_t (line 232) | inline const index_t* data() const { function index_t (line 236) | inline index_t* data() { function index_t (line 240) | inline index_t ndim(void) const { function index_t (line 248) | inline index_t& operator[](index_t i) { function index_t (line 256) | inline const index_t& operator[](index_t i) const { function Size (line 260) | inline size_t Size(void) const { function operator (line 272) | inline bool operator==(const Shape& s) const { function operator (line 292) | inline bool operator!=(const Shape& s) const { function SetDim (line 317) | inline void SetDim(index_t dim) { FILE: cpp-package/include/mxnet-cpp/symbol.h function namespace (line 36) | namespace mxnet { FILE: cpp-package/include/mxnet-cpp/symbol.hpp type mxnet (line 39) | namespace mxnet { type cpp (line 40) | namespace cpp { function OpMap (line 41) | inline OpMap*& Symbol::op_map() { function Symbol (line 54) | inline Symbol Symbol::Variable(const std::string &name) { return Sym... function Symbol (line 55) | inline Symbol Symbol::operator+(const Symbol &rhs) const { return _P... function Symbol (line 56) | inline Symbol Symbol::operator-(const Symbol &rhs) const { return _M... function Symbol (line 57) | inline Symbol Symbol::operator*(const Symbol &rhs) const { return _M... function Symbol (line 58) | inline Symbol Symbol::operator/(const Symbol &rhs) const { return _D... function Symbol (line 59) | inline Symbol Symbol::operator%(const Symbol &rhs) const { return _M... function Symbol (line 60) | inline Symbol Symbol::operator+(mx_float scalar) const { function Symbol (line 63) | inline Symbol Symbol::operator-(mx_float scalar) const { function Symbol (line 66) | inline Symbol Symbol::operator*(mx_float scalar) const { function Symbol (line 69) | inline Symbol Symbol::operator/(mx_float scalar) const { function Symbol (line 72) | inline Symbol Symbol::operator%(mx_float scalar) const { function Symbol (line 75) | inline Symbol Symbol::operator[](int index) { function Symbol (line 80) | inline Symbol Symbol::operator[](const std::string &index) { function Symbol (line 90) | inline Symbol Symbol::Group(const std::vector &symbols) { function Symbol (line 99) | inline Symbol Symbol::Load(const std::string &file_name) { function Symbol (line 105) | inline Symbol Symbol::LoadJSON(const std::string &json_str) { function Symbol (line 119) | inline Symbol Symbol::GetInternals() const { function Symbol (line 138) | inline Symbol Symbol::Copy() const { function mx_uint (line 210) | inline mx_uint Symbol::GetNumOutputs() const { function Executor (line 382) | inline Executor *Symbol::SimpleBind( function Executor (line 400) | inline Executor *Symbol::Bind(const Context &context, function Symbol (line 410) | inline Symbol operator+(mx_float lhs, const Symbol &rhs) { return rh... function Symbol (line 411) | inline Symbol operator-(mx_float lhs, const Symbol &rhs) { function Symbol (line 414) | inline Symbol operator*(mx_float lhs, const Symbol &rhs) { return rh... function Symbol (line 415) | inline Symbol operator/(mx_float lhs, const Symbol &rhs) { function Symbol (line 418) | inline Symbol operator%(mx_float lhs, const Symbol &rhs) { FILE: cpp-package/scripts/OpWrapperGenerator.py function gen_enum_value (line 35) | def gen_enum_value(value): class EnumType (line 38) | class EnumType: method __init__ (line 41) | def __init__(self, typeName = 'ElementWiseOpType', \ method GetDefinitionString (line 52) | def GetDefinitionString(self, indent = 0): method GetDefaultValueString (line 62) | def GetDefaultValueString(self, value = ''): method GetEnumStringArray (line 64) | def GetEnumStringArray(self, indent = 0): method GetConvertEnumVariableToString (line 74) | def GetConvertEnumVariableToString(self, variable=''): class Arg (line 78) | class Arg: method __init__ (line 112) | def __init__(self, opName = '', argName = '', typeString = '', descStr... method MakeCString (line 151) | def MakeCString(self, str): method ConstructEnumTypeName (line 156) | def ConstructEnumTypeName(self, opName = '', argName = ''): class Op (line 166) | class Op: method __init__ (line 171) | def __init__(self, name = '', description = '', args = []): method WrapDescription (line 190) | def WrapDescription(self, desc = ''): method GenDescription (line 209) | def GenDescription(self, desc = '', \ method GetOpDefinitionString (line 222) | def GetOpDefinitionString(self, use_name, indent=0): method GetArgString (line 302) | def GetArgString(self, arg): function ParseAllOps (line 309) | def ParseAllOps(): FILE: cpp-package/scripts/lint.py class LintHelper (line 36) | class LintHelper(object): method _print_summary_map (line 40) | def _print_summary_map(strm, result_map, ftype): method __init__ (line 52) | def __init__(self): method process_cpp (line 77) | def process_cpp(self, path, suffix): method process_python (line 89) | def process_python(self, path): method print_summary (line 107) | def print_summary(self, strm): function get_header_guard_dmlc (line 122) | def get_header_guard_dmlc(filename): function process (line 147) | def process(fname, allow_type): function main (line 161) | def main(): FILE: docs/python_docs/_static/autodoc.js function auto_index (line 21) | function auto_index() { FILE: docs/python_docs/python/scripts/conf.py function setup (line 254) | def setup(app): FILE: docs/python_docs/python/scripts/md2ipynb.py function md2ipynb (line 24) | def md2ipynb(): FILE: docs/python_docs/python/scripts/process_rst.py function has_token (line 22) | def has_token(token, lines): function get_next_title_mark (line 28) | def get_next_title_mark(lines): function add_hidden_title (line 37) | def add_hidden_title(inputs): FILE: docs/python_docs/python/tutorials/getting-started/crash-course/prepare_dataset.py function split_file_list (line 30) | def split_file_list(file_list, train_split=0.7, val_split=0.2, test_spli... function process_dataset (line 41) | def process_dataset(root_directory, splits=splits, classes=targets, trai... FILE: docs/python_docs/themes/mx-theme/mxtheme/__init__.py function get_path (line 9) | def get_path(): function setup (line 12) | def setup(app): FILE: docs/python_docs/themes/mx-theme/mxtheme/card.py class card (line 5) | class card(nodes.General, nodes.Element): class CardDirective (line 8) | class CardDirective(Directive): method run (line 21) | def run(self): FILE: docs/python_docs/themes/mx-theme/mxtheme/static/sphinx_materialdesign_theme.js function f (line 1) | function f(t,n){if(!r[t]){if(!e[t]){var i="function"==typeof parcelRequi... function e (line 6) | function e(t){return(e="function"==typeof Symbol&&"symbol"==typeof Symbo... function t (line 6) | function t(e,t){if(e){if(t.element_.classList.contains(t.CssClasses_.MDL... function s (line 6) | function s(e,t,s,i){function n(){var n=e.href.split("#")[1],a=i.content_... function t (line 6) | function t(e,t){for(var s=0;s>1,a... function R (line 486) | function R(t,n,r){var e,i=8*r-n-1,o=(1<>1,f=i-7,s=r-1,c=t[s--]... function k (line 486) | function k(t){return t[3]<<24|t[2]<<16|t[1]<<8|t[0]} function z (line 486) | function z(t){return[255&t]} function C (line 486) | function C(t){return[255&t,t>>8&255]} function G (line 486) | function G(t){return[255&t,t>>8&255,t>>16&255,t>>24&255]} function H (line 486) | function H(t){return O(t,52,8)} function J (line 486) | function J(t){return O(t,23,4)} function K (line 486) | function K(t,n,r){l(t[w],n,{get:function(){return this[r]}})} function P (line 486) | function P(t,n,r,e){var i=a(+r);if(i+n>t[D])throw U(b);var o=t[m]._b,u=i... function Q (line 486) | function Q(t,n,r,e,i,o){var u=a(+r);if(u+n>t[D])throw U(b);for(var f=t[m... function e (line 515) | function e(){} function a (line 523) | function a(i,c){var v,g,l=arguments.length<3?i:arguments[2];return u(i)=... function c (line 539) | function c(u,l,n){var q,s,_=arguments.length<4?u:arguments[3],b=r.f(o(u)... function u (line 545) | function u(s,a,n,c,f,l,q,_){for(var d,h,p=f,v=0,b=!!q&&t(q,_,3);v... function MXReturnValue (line 96) | MXReturnValue backward(const std::unordered_map* inputs, method MXReturnValue (line 202) | MXReturnValue Backward(std::vector* inputs, function MXReturnValue (line 213) | MXReturnValue createOpState(const std::unordered_map* inputs, function MXReturnValue (line 95) | MXReturnValue MyStatefulReluCPU::Backward(std::vector* inputs, function MXReturnValue (line 104) | MXReturnValue MyStatefulReluGPU::Forward(std::vector* inputs, function MXReturnValue (line 110) | MXReturnValue MyStatefulReluGPU::Backward(std::vector* inputs, function MXReturnValue (line 116) | MXReturnValue createOpStateCPU(const std::unordered_map... function MXReturnValue (line 86) | MXReturnValue backward(const std::unordered_map* inputs, method MXReturnValue (line 165) | MXReturnValue Backward(std::vector* inputs, function MXReturnValue (line 176) | MXReturnValue createOpState(const std::unordered_map... function MXReturnValue (line 87) | MXReturnValue backward(const std::unordered_map* inputs, method MXReturnValue (line 166) | MXReturnValue Backward(std::vector* inputs, function MXReturnValue (line 177) | MXReturnValue createOpState(const std::unordered_map* inputs, class MyStatefulOp (line 142) | class MyStatefulOp : public CustomStatefulOp { method MyStatefulOp (line 144) | explicit MyStatefulOp(std::string json, const std::unordered_map* inputs, function MXReturnValue (line 166) | MXReturnValue createOpState(const std::unordered_map& candidates, std::vector& ke... method Reset (line 293) | void Reset() override {} function MXReturnValue (line 300) | MXReturnValue createSelector(const mxnet::ext::Graph* graph, function MXReturnValue (line 314) | MXReturnValue addInputPass(mxnet::ext::Graph* graph, function MXReturnValue (line 341) | MXReturnValue initialize(int version) { FILE: example/extensions/lib_subgraph/test_subgraph.py function test (line 51) | def test(backend): FILE: example/gluon/actor_critic/actor_critic.py class Policy (line 47) | class Policy(gluon.Block): method __init__ (line 48) | def __init__(self, **kwargs): method forward (line 54) | def forward(self, x): FILE: example/gluon/data.py function get_cifar10_iterator (line 33) | def get_cifar10_iterator(batch_size, data_shape, resize=-1, num_parts=1,... function get_imagenet_transforms (line 60) | def get_imagenet_transforms(data_shape=224, dtype='float32'): function get_imagenet_iterator (line 76) | def get_imagenet_iterator(root, batch_size, num_workers, data_shape=224,... function get_caltech101_data (line 93) | def get_caltech101_data(): function get_caltech101_iterator (line 110) | def get_caltech101_iterator(batch_size, num_workers, dtype): class DummyIter (line 128) | class DummyIter(mx.io.DataIter): method __init__ (line 129) | def __init__(self, batch_size, data_shape, batches = 100): method next (line 140) | def next(self): function dummy_iterator (line 148) | def dummy_iterator(batch_size, data_shape): class ImagePairIter (line 151) | class ImagePairIter(mx.io.DataIter): method __init__ (line 152) | def __init__(self, path, data_shape, label_shape, batch_size=64, flag=... method next (line 166) | def next(self): method reset (line 195) | def reset(self): FILE: example/gluon/house_prices/kaggle_k_fold_cross_validation.py function get_rmse_log (line 66) | def get_rmse_log(net, X_train, y_train): function get_net (line 73) | def get_net(): function train (line 81) | def train(net, X_train, y_train, epochs, verbose_epoch, learning_rate, function k_fold_cross_valid (line 103) | def k_fold_cross_valid(k, epochs, verbose_epoch, X_train, y_train, function learn (line 150) | def learn(epochs, verbose_epoch, X_train, y_train, test, learning_rate, FILE: example/gluon/image_classification.py function get_model (line 117) | def get_model(model, device, opt): function get_data_iters (line 138) | def get_data_iters(dataset, batch_size, opt): function test (line 162) | def test(device, val_data): function update_learning_rate (line 174) | def update_learning_rate(lr, trainer, epoch, ratio, steps): function save_checkpoint (line 180) | def save_checkpoint(epoch, top1, best_acc): function train (line 191) | def train(opt, device): function main (line 256) | def main(): FILE: example/gluon/mnist/mnist.py function transformer (line 57) | def transformer(data, label): function test (line 71) | def test(ctx): function train (line 82) | def train(epochs, ctx): FILE: example/gluon/super_resolution/super_resolution.py function get_dataset (line 70) | def get_dataset(prefetch=False): class SuperResolutionNet (line 139) | class SuperResolutionNet(gluon.HybridBlock): method __init__ (line 140) | def __init__(self, upscale_factor): method forward (line 148) | def forward(self, x): function test (line 159) | def test(device): function train (line 177) | def train(epoch, device): function resolve (line 208) | def resolve(device): FILE: example/profiler/profiler_imageiter.py function run_imageiter (line 26) | def run_imageiter(path_rec, n, batch_size=32): FILE: example/profiler/profiler_matmul.py function parse_args (line 24) | def parse_args(): FILE: example/profiler/profiler_ndarray.py function _np_reduce (line 24) | def _np_reduce(dat, axis, keepdims, numpy_reduce_func): function reldiff (line 40) | def reldiff(a, b): function same (line 47) | def same(a, b): function check_with_uniform (line 51) | def check_with_uniform(uf, arg_shapes, dim=None, npuf=None, rmin=-10, ty... function random_ndarray (line 80) | def random_ndarray(dim): function test_ndarray_elementwise (line 86) | def test_ndarray_elementwise(): function test_ndarray_negate (line 104) | def test_ndarray_negate(): function test_ndarray_choose (line 116) | def test_ndarray_choose(): function test_ndarray_fill (line 127) | def test_ndarray_fill(): function test_ndarray_onehot (line 142) | def test_ndarray_onehot(): function test_ndarray_copy (line 155) | def test_ndarray_copy(): function test_ndarray_scalar (line 161) | def test_ndarray_scalar(): function test_ndarray_pickle (line 176) | def test_ndarray_pickle(): function test_ndarray_saveload (line 192) | def test_ndarray_saveload(): function test_ndarray_slice (line 216) | def test_ndarray_slice(): function test_ndarray_slice_along_axis (line 226) | def test_ndarray_slice_along_axis(): function test_clip (line 238) | def test_clip(): function test_dot (line 248) | def test_dot(): function test_reduce (line 258) | def test_reduce(): function test_broadcast (line 294) | def test_broadcast(): FILE: example/quantization/imagenet_gen_qsym_onednn.py function download_calib_dataset (line 37) | def download_calib_dataset(dataset_url, calib_dataset, logger=None): function get_from_gluon (line 43) | def get_from_gluon(model_name, classes=1000, logger=None): function regex_find_excluded_symbols (line 53) | def regex_find_excluded_symbols(patterns_dict, model_name): function get_exclude_symbols (line 60) | def get_exclude_symbols(model_name, exclude_first_conv): FILE: example/quantization/imagenet_inference.py function download_dataset (line 29) | def download_dataset(dataset_url, dataset_dir, logger=None): function score (line 35) | def score(symblock, data, ctx, max_num_examples, skip_num_batches, logge... function initialize_block_params (line 64) | def initialize_block_params(block, initializer): function benchmark_score (line 72) | def benchmark_score(symblock, ctx, batch_size, warmup_batches, num_batch... FILE: example/quantization_inc/custom_strategy.py function calc_approx_error (line 25) | def calc_approx_error(expected_tensor: np.ndarray, observed_tensor: np.n... function get_approx_errors (line 37) | def get_approx_errors(expected_tensors, observed_tensors): class MyCustomTuneStrategy (line 50) | class MyCustomTuneStrategy(TuneStrategy): method __init__ (line 52) | def __init__(self, model, conf, q_dataloader, q_func=None, method get_qtensors (line 65) | def get_qtensors(self, quant_cfg, node_list): method next_tune_cfg (line 73) | def next_tune_cfg(self): method bayesian_params_to_tune_configs (line 156) | def bayesian_params_to_tune_configs(self, params): method bayesian_configurations (line 168) | def bayesian_configurations(self, cfg_base, params_base): FILE: example/quantization_inc/resnet_measurement.py function test_accuracy (line 24) | def test_accuracy(net, data_loader, description): FILE: example/quantization_inc/resnet_mse.py function eval_func (line 45) | def eval_func(model): FILE: example/quantization_inc/resnet_tuning.py function save_model (line 30) | def save_model(net, data_loader, description, time_spend): function eval_func (line 98) | def eval_func(model): FILE: example/recommenders/matrix_fact.py function evaluate_network (line 28) | def evaluate_network(network, data_iterator, ctx): function train (line 40) | def train(network, train_data, test_data, epochs, learning_rate=0.01, op... FILE: example/recommenders/movielens_data.py function load_mldataset (line 25) | def load_mldataset(filename): function ensure_local_data (line 45) | def ensure_local_data(prefix): function get_dataset (line 56) | def get_dataset(prefix='ml-100k'): function max_id (line 63) | def max_id(fname): FILE: include/mxnet/api_registry.h function namespace (line 33) | namespace mxnet { FILE: include/mxnet/base.h function namespace (line 75) | namespace mxnet { function operator (line 132) | inline bool operator==(const Context& b) const { function operator (line 140) | inline bool operator!=(const Context& b) const { function Save (line 147) | inline void Save(dmlc::Stream* strm) const { function Load (line 156) | inline bool Load(dmlc::Stream* strm) { function class (line 234) | class GPUAuxStream { function PreAuxStreamUseSync (line 266) | void PreAuxStreamUseSync() { function PostAuxStreamUseSync (line 274) | void PostAuxStreamUseSync() { function StreamSync (line 289) | static void StreamSync(mshadow::Stream* s1, mshadow::Stream* s... function class (line 308) | class SyncedGPUAuxStream { type RunContext (line 343) | struct RunContext { function namespace (line 384) | namespace mxnet { function namespace (line 550) | namespace std { FILE: include/mxnet/c_api.h type mx_uint (line 65) | typedef uint32_t mx_uint; type mx_float (line 67) | typedef float mx_float; type dim_t (line 69) | typedef int64_t dim_t; type NativeOpInfo (line 129) | struct NativeOpInfo { type NDArrayOpInfo (line 143) | struct NDArrayOpInfo { type MXCallbackList (line 161) | struct MXCallbackList { type LibFeature (line 167) | struct LibFeature { type CustomOpCallbacks (line 172) | enum CustomOpCallbacks { kCustomOpDelete, kCustomOpForward, kCustomOpBac... type CustomOpPropCallbacks (line 174) | enum CustomOpPropCallbacks { type MXCallbackList (line 216) | struct MXCallbackList type MXCallbackList (line 222) | struct MXCallbackList type CustomFunctionCallbacks (line 224) | enum CustomFunctionCallbacks { kCustomFunctionBackward, kCustomFunctionD... type LibFeature (line 263) | struct LibFeature type OtherOptionEntity (line 575) | struct OtherOptionEntity { type OtherOptionSpace (line 579) | struct OtherOptionSpace { type ConfigSpace (line 584) | struct ConfigSpace { type ConfigSpaces (line 593) | typedef struct ConfigSpaces { type MXCallbackList (line 2922) | struct MXCallbackList FILE: include/mxnet/c_api_error.h function namespace (line 72) | namespace mxnet { FILE: include/mxnet/engine.h function namespace (line 36) | namespace mxnet { function class (line 169) | class CallbackOnComplete { function FnProperty (line 191) | enum class FnProperty { FILE: include/mxnet/executor.h function virtual (line 84) | virtual void Print(std::ostream& os) const {} FILE: include/mxnet/expr_operator.h function namespace (line 34) | namespace mxnet { FILE: include/mxnet/graph_attr_types.h function namespace (line 30) | namespace mxnet { FILE: include/mxnet/imperative.h type class (line 40) | enum class type NumpyShape (line 57) | enum NumpyShape { Off, ThreadLocalOn, GlobalOn } type NumpyShape (line 58) | typedef NumpyShape NumpyDefaultDtype; function Clear (line 76) | static void Clear(const nnvm::ObjectPtr& node) { function AGInfo (line 85) | static AGInfo& Get(const nnvm::ObjectPtr& node) { function AGInfo (line 89) | static AGInfo& Create(const nnvm::ObjectPtr& node) { function IsNone (line 94) | static bool IsNone(const NDArray& arr) { function IsVariable (line 98) | static bool IsVariable(const nnvm::ObjectPtr& node) { function class (line 105) | class DCInfo { function set_is_training (line 179) | bool set_is_training(bool is_train) { function set_is_recording (line 189) | bool set_is_recording(bool is_recording) { function set_is_deferred_compute (line 199) | bool set_is_deferred_compute(bool is_deferred_compute) { function set_is_np_shape (line 214) | bool set_is_np_shape(int is_np_shape) { function set_is_np_default_dtype (line 241) | bool set_is_np_default_dtype(bool is_np_default_dtype) { function OptConstraint (line 255) | OptConstraint set_opt_constraints(OptConstraint constraints) { function PreferBulkExecInference (line 308) | static bool PreferBulkExecInference() { function PreferBulkExecTrain (line 312) | static bool PreferBulkExecTrain() { function BulkExecMaxNodeTrainFwd (line 316) | static int BulkExecMaxNodeTrainFwd() { function BulkExecMaxNodeTrainBwd (line 321) | static int BulkExecMaxNodeTrainBwd() { function is_np_shape_global_ (line 357) | bool is_np_shape_global_{false}; FILE: include/mxnet/io.h function namespace (line 36) | namespace mxnet { FILE: include/mxnet/ir/expr.h function class (line 40) | class BaseExprNode : public Object { function class (line 50) | class BaseExpr : public ObjectRef { function class (line 75) | class PrimExprNode : public BaseExprNode { function class (line 101) | class PrimExpr : public BaseExpr { function class (line 152) | class IntImm : public PrimExpr { function class (line 183) | class FloatImmNode : public PrimExprNode { FILE: include/mxnet/kvstore.h type class (line 48) | enum class function class (line 56) | class KVStore { FILE: include/mxnet/lib_api.h type DLDeviceType (line 101) | typedef enum { type DLContext (line 132) | typedef struct { type DLDataTypeCode (line 142) | typedef enum { type DLDataType (line 156) | typedef struct { type DLTensor (line 174) | typedef struct { function namespace (line 216) | namespace mxnet { FILE: include/mxnet/libinfo.h function namespace (line 131) | namespace mxnet { FILE: include/mxnet/ndarray.h function namespace (line 47) | namespace dnnl { function namespace (line 51) | namespace mxnet { function InitDetached (line 196) | void InitDetached(const NDArray* src) { function ReInit (line 200) | inline void ReInit() { function IsSame (line 236) | inline bool IsSame(const NDArray& other) const { function mxnet (line 264) | inline const mxnet::TShape& aux_shape(size_t index) const { function set_aux_shape (line 289) | inline void set_aux_shape(size_t index, const mxnet::TShape& shape) const { function NDArray (line 307) | NDArray grad() const; function aux_type (line 338) | inline int aux_type(size_t i) const { function WaitToWrite (line 403) | void WaitToWrite() const; function NDArray (line 586) | inline NDArray AsArray(const mxnet::TShape& shape, int dtype) const { function InitAsArray (line 599) | inline void InitAsArray(const NDArray& src, const mxnet::TShape& shape, ... function SparseUpdateChunk (line 639) | inline void SparseUpdateChunk(const NDArray& arr) const { function NDArrayFunctionReg (line 1396) | inline NDArrayFunctionReg& set_function(void (*fsetvalue)(const real_t& ... function NDArrayFunctionReg (line 1414) | inline NDArrayFunctionReg& set_function( function NDArrayFunctionReg (line 1438) | inline NDArrayFunctionReg& set_function(void (*fbinary)(const NDArray& lhs, function NDArrayFunctionReg (line 1462) | inline NDArrayFunctionReg& set_function(void (*fscalar)(const NDArray& lhs, function NDArrayFunctionReg (line 1485) | inline NDArrayFunctionReg& set_function(void (*funary)(const NDArray& sr... function NDArrayFunctionReg (line 1504) | inline NDArrayFunctionReg& set_function( function NDArrayFunctionReg (line 1528) | inline NDArrayFunctionReg& set_num_use_vars(unsigned n) { function NDArrayFunctionReg (line 1537) | inline NDArrayFunctionReg& set_num_mutate_vars(unsigned n) { function NDArrayFunctionReg (line 1546) | inline NDArrayFunctionReg& set_num_scalars(unsigned n) { function NDArrayFunctionReg (line 1555) | inline NDArrayFunctionReg& set_type_mask(int tmask) { function namespace (line 1577) | namespace dmlc { FILE: include/mxnet/node/container.h function class (line 39) | class ArrayNode : public Object { FILE: include/mxnet/node/node.h function namespace (line 47) | namespace mxnet { FILE: include/mxnet/op_attr_types.h function namespace (line 40) | namespace mxnet { type class (line 98) | enum class type class (line 122) | enum class type class (line 135) | enum class function class (line 148) | class OpStatePtr { FILE: include/mxnet/operator.h function namespace (line 41) | namespace mxnet { function class (line 127) | class OperatorProperty { function virtual (line 221) | virtual bool InferType(std::vector* in_type, function virtual (line 261) | virtual Operator* CreateOperatorEx(Context ctx, function virtual (line 290) | virtual std::vector ForwardResource(const mxnet::ShapeV... function virtual (line 300) | virtual std::vector BackwardResource(const mxnet::Shape... function virtual (line 325) | virtual std::vector DeclareBackwardDependency(const std::vector OperatorPropertyFactory; type OperatorPropertyReg (line 454) | struct OperatorPropertyReg function OperatorPropertyReg (line 468) | inline OperatorPropertyReg& set_key_var_num_args(const std::string& key)... function OperatorPropertyReg (line 475) | inline OperatorPropertyReg& check_name() { FILE: include/mxnet/operator_util.h function namespace (line 49) | namespace mxnet { FILE: include/mxnet/random_generator.h function namespace (line 36) | namespace mxnet { FILE: include/mxnet/resource.h function namespace (line 33) | namespace mxnet { function namespace (line 65) | namespace { type Resource (line 90) | struct Resource { function class (line 239) | class ResourceManager { FILE: include/mxnet/rtc.h function namespace (line 35) | namespace mxnet { FILE: include/mxnet/runtime/c_runtime_api.h type MXNetTypeCode (line 41) | typedef enum { type MXNetValue (line 72) | typedef union { type MXNetByteArray (line 85) | typedef struct { FILE: include/mxnet/runtime/container.h function namespace (line 36) | namespace mxnet { function class (line 209) | class ADT : public ObjectRef { FILE: include/mxnet/runtime/container_ext.h function namespace (line 39) | namespace mxnet { type mxnet (line 677) | struct mxnet function memncmp (line 878) | inline int String::memncmp(const char* lhs, const char* rhs, size_t lhs_... function const (line 897) | inline size_t ObjectRefHash::operator()(const ObjectRef& a) const { function const (line 904) | inline bool ObjectRefEqual::operator()(const ObjectRef& a, const ObjectR... FILE: include/mxnet/runtime/data_type.h function namespace (line 32) | namespace mxnet { FILE: include/mxnet/runtime/ffi_helper.h function ObjectRef (line 44) | inline ObjectRef CreateEllipsis() { function SliceNoneValue (line 80) | int64_t inline SliceNoneValue() { function class (line 109) | class Float : public ObjectRef { FILE: include/mxnet/runtime/memory.h function namespace (line 32) | namespace mxnet { FILE: include/mxnet/runtime/ndarray.h function namespace (line 28) | namespace mxnet { FILE: include/mxnet/runtime/ndarray_handle.h function class (line 40) | class NDArrayHandle : public ObjectRef { FILE: include/mxnet/runtime/object.h function namespace (line 47) | namespace mxnet { function class (line 500) | class ObjectRef { function const (line 620) | struct ObjectHash { function const (line 632) | struct ObjectEqual { function IncRef (line 727) | inline void Object::IncRef() { function DecRef (line 731) | inline void Object::DecRef() { function IncRef (line 746) | inline void Object::IncRef() { function DecRef (line 750) | inline void Object::DecRef() { function IsInstance (line 765) | bool Object::IsInstance() const { function ObjectType (line 804) | const ObjectType* ObjectRef::as() const { function RefType (line 813) | RefType GetRef(const ObjType* ptr) { function SubRef (line 830) | SubRef Downcast(BaseRef ref) { FILE: include/mxnet/runtime/packed_func.h function namespace (line 52) | namespace mxnet { function class (line 322) | class MXNetArgs { function Check (line 385) | static bool Check(const Object* ptr) { function std (line 391) | static std::string TypeName() { function class (line 401) | class MXNetPODValue_ { function type_code_ (line 465) | type_code_(kNull) {} function class (line 480) | class MXNetArgValue : public MXNetPODValue_ { function operator (line 526) | operator MXNetDataType() const { function class (line 555) | class MXNetRetValue : public MXNetPODValue_ { function MXNetPODValue_ (line 582) | MXNetRetValue(const MXNetRetValue& other) : MXNetPODValue_() { function operator (line 586) | operator std::string() const { function operator (line 600) | operator MXNetDataType() const { function MoveToCHost (line 714) | void MoveToCHost(MXNetValue* ret_value, int* ret_type_code) { function SwitchToPOD (line 759) | void SwitchToPOD(int type_code) { function SwitchToObject (line 775) | void SwitchToObject(int type_code, ObjectPtr other) { function Clear (line 786) | void Clear() { function DLDataType (line 805) | inline DLDataType String2DLDataType(std::string s) { function String2MXNetTypeWithBool (line 881) | inline int String2MXNetTypeWithBool(const std::string& s) { function String2MXNetType (line 915) | inline int String2MXNetType(const std::string& s) { function MXNetArgValue (line 971) | inline MXNetArgValue MXNetArgs::operator[](int i) const { function CallPacked (line 981) | inline void PackedFunc::CallPacked(MXNetArgs args, MXNetRetValue* rv) co... function namespace (line 990) | namespace detail { function class (line 1013) | class MXNetArgsSetter { function const (line 1022) | void operator()(size_t i, uint64_t value) const { function const (line 1027) | void operator()(size_t i, double value) const { function const (line 1031) | void operator()(size_t i, std::nullptr_t value) const { function const (line 1035) | void operator()(size_t i, const MXNetArgValue& value) const { function const (line 1039) | void operator()(size_t i, void* value) const { function const (line 1043) | void operator()(size_t i, const char* value) const { function const (line 1050) | void operator()(size_t i, const std::string& value) const { // NOLINT(*) function const (line 1054) | void operator()(size_t i, DLDataType value) const { function const (line 1058) | void operator()(size_t i, MXNetDataType dtype) const { function const (line 1061) | void operator()(size_t i, const MXNetByteArray& value) const { // NOLIN... function const (line 1069) | void operator()(size_t i, const ObjectRef& value) const { // NOLINT(*) function const (line 1077) | void operator()(size_t i, const MXNetRetValue& value) const { // NOLINT(*) function MXNetRetValue (line 1096) | MXNetRetValue PackedFunc::operator()(Args&&... args) const { function namespace (line 1107) | namespace detail { function run (line 1134) | void run(const F& f, function unpack_call (line 1143) | void unpack_call(const F& f, const MXNetArgs& args, MXNetRetValue* rv) { function R (line 1148) | R call_packed(const PackedFunc& pf, Args&&... args) { function R (line 1155) | inline R run(const PackedFunc& pf, Args&&... args) { function void (line 1161) | struct typed_packed_call_dispatcher { function packed_ (line 1170) | packed_(packed) {} function namespace (line 1194) | namespace detail { function TObjectRef (line 1221) | static TObjectRef From(const MXNetArgValue& val) { function TObjectRef (line 1229) | static TObjectRef From(const MXNetRetValue& val) { function String (line 1235) | struct PackedFuncValueConverter<::mxnet::runtime::String> { function IsObjectRef (line 1283) | bool MXNetPODValue_::IsObjectRef() const { FILE: include/mxnet/runtime/py_arg.h function namespace (line 26) | namespace mxnet { FILE: include/mxnet/runtime/registry.h function namespace (line 51) | namespace mxnet { FILE: include/mxnet/storage.h type SyncObj (line 45) | struct SyncObj { type Handle (line 56) | struct Handle { function size (line 64) | size_t size{0} function shared_pid (line 72) | int shared_pid{-1}; FILE: include/mxnet/tensor_blob.h function namespace (line 39) | namespace mxnet { function CheckContiguous (line 186) | inline bool CheckContiguous(void) const { function TBlob (line 194) | inline TBlob reshape(const mxnet::TShape& shape) const { function ndim (line 231) | inline int ndim(void) const { function index_t (line 240) | inline index_t size(index_t idx) const { function Size (line 244) | inline size_t Size(void) const { function DType (line 249) | DType* dptr() const { type FieldEntryBase (line 488) | typedef FieldEntryBase, mxnet::TShape> Parent; function virtual (line 490) | virtual void Check(void* head) const { function FieldEntry (line 510) | inline FieldEntry& enforce_nonzero() { function FieldEntry (line 514) | inline FieldEntry& set_expect_ndim(int ndim) { FILE: include/mxnet/tuple.h function namespace (line 41) | namespace mxnet { function explicit (line 120) | inline explicit Tuple(const runtime::ObjectRef& src) { function assign (line 136) | void assign(RandomAccessIterator begin, RandomAccessIterator end) { function swap (line 145) | inline void swap(Tuple& other) { // NOLINT(*) function s (line 186) | inline bool operator==(const Tuple& s) const { function s (line 197) | inline bool operator!=(const Tuple& s) const { function ValueType (line 201) | inline const ValueType* begin() const { function ValueType (line 205) | inline ValueType* begin() { function ValueType (line 209) | inline const ValueType* end() const { function ValueType (line 213) | inline ValueType* end() { function ValueType (line 225) | inline ValueType& operator[](int i) { function ValueType (line 239) | inline const ValueType& operator[](int i) const { function Save (line 252) | inline void Save(dmlc::JSONWriter* writer) const { function Load (line 260) | inline void Load(dmlc::JSONReader* reader) { function ndim_ (line 392) | int ndim_{0} function num_heap_allocated_ (line 394) | int num_heap_allocated_{0} function ValueType (line 398) | ValueType* data_heap_{nullptr}; function ndim_is_known (line 416) | inline bool ndim_is_known(const int ndim) { function dim_size_is_known (line 422) | inline bool dim_size_is_known(const dim_t dim_size) { function class (line 440) | class TShape : public Tuple { function explicit (line 499) | inline explicit TShape(const ObjectRef& src) : Tuple(src) {} function Size (line 523) | inline size_t Size() const { function ProdShape (line 538) | inline size_t ProdShape(int dimstart, int dimend) const { function dim_t (line 552) | inline const dim_t* data() const { function dim_t (line 556) | inline dim_t* data() { function mshadow (line 599) | inline mshadow::Shape<2> FlatTo2D(void) const { function mshadow (line 619) | inline mshadow::Shape<3> FlatTo3D(int axis_begin, int axis_end) const { function mshadow (line 646) | inline mshadow::Shape<3> FlatTo3D(int axis) const { function operator (line 649) | inline bool operator==(const TShape& s) const { function operator (line 654) | inline bool operator!=(const TShape& s) const { function ndim_is_known (line 686) | inline bool ndim_is_known(const TShape& x) { function dim_size_is_known (line 691) | inline bool dim_size_is_known(const TShape& x, const int idx) { function shape_is_known (line 699) | inline bool shape_is_known(const TShape& x) { function shape_is_known (line 709) | inline bool shape_is_known(const std::vector& shapes) { function DstIter (line 719) | DstIter ShapeTypeCast(const SrcIter begin, const SrcIter end, DstIter ds... function TShape (line 728) | TShape ShapeTypeCast(const SrcIter begin, const SrcIter end) { function namespace (line 771) | namespace std { function namespace (line 801) | namespace dmlc { function namespace (line 816) | namespace mxnet { FILE: plugin/opencv/cv_api.cc function get_jpeg_size (line 36) | bool get_jpeg_size(const unsigned char* data, mx_uint data_size, mx_uint... function get_png_size (line 74) | bool get_png_size(const unsigned char* data, mx_uint data_size, mx_uint*... function MXNET_DLL (line 86) | MXNET_DLL int MXCVImdecode(const unsigned char* img, function MXNET_DLL (line 124) | MXNET_DLL int MXCVResize(NDArrayHandle src, function MXNET_DLL (line 156) | MXNET_DLL int MXCVcopyMakeBorder(NDArrayHandle src, FILE: plugin/opencv/opencv.py function imdecode (line 29) | def imdecode(str_img, flag=1): function resize (line 51) | def resize(src, size, interpolation=cv2.INTER_LINEAR): function copyMakeBorder (line 74) | def copyMakeBorder(src, top, bot, left, right, border_type=cv2.BORDER_CO... function scale_down (line 97) | def scale_down(src_size, size): function fixed_crop (line 107) | def fixed_crop(src, x0, y0, w, h, size=None, interpolation=cv2.INTER_CUB... function random_crop (line 114) | def random_crop(src, size): function color_normalize (line 125) | def color_normalize(src, mean, std): function random_size_crop (line 131) | def random_size_crop(src, size, min_area=0.25, ratio=(3.0/4.0, 4.0/3.0)): class ImageListIter (line 155) | class ImageListIter(mx.io.DataIter): method __init__ (line 157) | def __init__(self, root, flist, batch_size, size, mean=None): method reset (line 169) | def reset(self): method next (line 173) | def next(self): FILE: plugin/sframe/iter_sframe.cc type mxnet (line 44) | namespace mxnet { type io (line 45) | namespace io { type SFrameParam (line 47) | struct SFrameParam : public dmlc::Parameter { method DMLC_DECLARE_PARAMETER (line 54) | DMLC_DECLARE_PARAMETER(SFrameParam) { class SFrameIterBase (line 69) | class SFrameIterBase : public IIterator { method SFrameIterBase (line 71) | SFrameIterBase() {} method Init (line 73) | void Init(const std::vector >&... method BeforeFirst (line 82) | virtual void BeforeFirst() { method DataInst (line 88) | virtual const DataInst& Value(void) const { method Copy_ (line 113) | void Copy_(mshadow::Tensor tensor, const graphlab::flex_... class SFrameImageIter (line 123) | class SFrameImageIter : public SFrameIterBase { method SFrameImageIter (line 125) | SFrameImageIter() : augmenter_(new ImageAugmenter()), prnd_(new co... method Init (line 127) | void Init(const std::vector >&... method Next (line 133) | bool Next(void) override { class SFrameDataIter (line 184) | class SFrameDataIter : public SFrameIterBase { method Next (line 186) | bool Next() override { FILE: plugin/torch/torch_base.cc type mxnet (line 27) | namespace mxnet { function TorchState (line 47) | TorchState* TorchState::ThreadSharedLuaState() { FILE: plugin/torch/torch_base.h function namespace (line 47) | namespace mxnet { FILE: plugin/torch/torch_criterion-inl.h function namespace (line 40) | namespace mxnet { FILE: plugin/torch/torch_criterion.cc type mxnet (line 28) | namespace mxnet { type op (line 29) | namespace op { function Operator (line 31) | Operator* CreateOp(TorchCriterionParam param) { function Operator (line 36) | Operator* TorchCriterionProp::CreateOperator(Context ctx) const { FILE: plugin/torch/torch_function.cc type mxnet (line 27) | namespace mxnet { type TorchMMShape (line 92) | struct TorchMMShape { method GetShape (line 93) | static std::vector GetShape(NDArray** u, type TorchMVShape (line 108) | struct TorchMVShape { method GetShape (line 109) | static std::vector GetShape(NDArray** u, type TorchBMMShape (line 124) | struct TorchBMMShape { method GetShape (line 125) | static std::vector GetShape(NDArray** u, type TorchGERShape (line 141) | struct TorchGERShape { method GetShape (line 142) | static std::vector GetShape(NDArray** u, FILE: plugin/torch/torch_function.h function namespace (line 37) | namespace mxnet { type TorchFirstShape (line 174) | struct TorchFirstShape { FILE: plugin/torch/torch_module-inl.h function namespace (line 40) | namespace mxnet { FILE: plugin/torch/torch_module.cc type mxnet (line 28) | namespace mxnet { type op (line 29) | namespace op { function Operator (line 31) | Operator* CreateOp(TorchModuleParam param, TorchState* torchSta... function Operator (line 36) | Operator* TorchModuleProp::CreateOperator(Context ctx) const { FILE: plugin/warpctc/warpctc-inl.h function namespace (line 41) | namespace mxnet { FILE: plugin/warpctc/warpctc.cc type mxnet (line 29) | namespace mxnet { type op (line 30) | namespace op { function Operator (line 32) | Operator* CreateOp(WarpCTCParam param) { function Operator (line 36) | Operator* WarpCTCProp::CreateOperator(Context ctx) const { FILE: python/mxnet/_ctypes/cached_op.py function _monitor_callback_wrapper (line 33) | def _monitor_callback_wrapper(callback): class CachedOp (line 40) | class CachedOp(object): method __init__ (line 44) | def __init__(self, sym, flags=(), thread_safe=False): method __del__ (line 57) | def __del__(self): method get_optimized_symbol (line 60) | def get_optimized_symbol(self): method __call__ (line 73) | def __call__(self, *args, **kwargs): method _register_op_hook (line 148) | def _register_op_hook(self, callback, monitor_all=False): FILE: python/mxnet/_ctypes/ndarray.py class NDArrayBase (line 31) | class NDArrayBase(object): method __init__ (line 36) | def __init__(self, handle, writable=True): method __del__ (line 50) | def __del__(self): method __reduce__ (line 54) | def __reduce__(self): function _imperative_invoke (line 58) | def _imperative_invoke(handle, ndargs, keys, vals, out, is_np_op, output... FILE: python/mxnet/_ctypes/space.py class COtherOptionEntity (line 26) | class COtherOptionEntity(ctypes.Structure): class COtherOptionSpace (line 31) | class COtherOptionSpace(ctypes.Structure): class CConfigSpace (line 37) | class CConfigSpace(ctypes.Structure): class CConfigSpaces (line 47) | class CConfigSpaces(ctypes.Structure): function c_other_option_entity (line 54) | def c_other_option_entity(x): function c_other_option_space (line 61) | def c_other_option_space(x): function c_config_space (line 70) | def c_config_space(x): function c_config_spaces (line 84) | def c_config_spaces(x): function _set_tvm_op_config (line 93) | def _set_tvm_op_config(x): FILE: python/mxnet/_ctypes/symbol.py class SymbolBase (line 32) | class SymbolBase(object): method __init__ (line 36) | def __init__(self, handle): method __del__ (line 47) | def __del__(self): method _compose (line 51) | def _compose(self, *args, **kwargs): method _set_attr (line 93) | def _set_attr(self, **kwargs): method _set_handle (line 107) | def _set_handle(self, handle): method __reduce__ (line 111) | def __reduce__(self): function _set_symbol_class (line 115) | def _set_symbol_class(cls): function _set_np_symbol_class (line 121) | def _set_np_symbol_class(cls): function _symbol_creator (line 127) | def _symbol_creator(handle, args, kwargs, keys, vals, name, is_np_op, ou... FILE: python/mxnet/_deferred_compute.py function is_deferred_compute (line 27) | def is_deferred_compute(): function set_deferred_compute (line 33) | def set_deferred_compute(state): function context (line 50) | def context(state=True): function get_symbol (line 64) | def get_symbol(output_arrays, *, sym_cls=Symbol): function set_variable (line 87) | def set_variable(arrays, variables): function clear (line 109) | def clear(arrays): FILE: python/mxnet/_ffi/_ctypes/function.py function _make_packed_func (line 38) | def _make_packed_func(handle, is_global): function _get_global_func (line 45) | def _get_global_func(name, allow_missing=False): function _make_mxnet_args (line 56) | def _make_mxnet_args(args, temp_args): class FunctionBase (line 105) | class FunctionBase(object): method __init__ (line 109) | def __init__(self, handle, is_global): method __del__ (line 123) | def __del__(self): method __call__ (line 128) | def __call__(self, *args): function __init_handle_by_constructor__ (line 148) | def __init_handle_by_constructor__(fconstructor, args): function _set_class_packed_func (line 169) | def _set_class_packed_func(packed_func_class): function _set_node_generic (line 174) | def _set_node_generic(func_convert_to_node): FILE: python/mxnet/_ffi/_ctypes/object.py function _set_class_object (line 34) | def _set_class_object(object_class): function _register_object (line 39) | def _register_object(index, cls): function _return_object (line 47) | def _return_object(x): class PyNativeObject (line 66) | class PyNativeObject: method __init_mxnet_object_by_constructor__ (line 71) | def __init_mxnet_object_by_constructor__(self, fconstructor, *args): class ObjectBase (line 92) | class ObjectBase(object): method __del__ (line 96) | def __del__(self): method __init_handle_by_constructor__ (line 100) | def __init_handle_by_constructor__(self, fconstructor, *args): method same_as (line 124) | def same_as(self, other): FILE: python/mxnet/_ffi/_ctypes/types.py class TypeCode (line 27) | class TypeCode(object): class MXNetValue (line 44) | class MXNetValue(ctypes.Union): FILE: python/mxnet/_ffi/base.py function c_str (line 40) | def c_str(string): function c_array (line 55) | def c_array(ctype, values): FILE: python/mxnet/_ffi/function.py class Function (line 47) | class Function(_FunctionBase): function get_global_func (line 72) | def get_global_func(name, allow_missing=False): function list_global_func_names (line 91) | def list_global_func_names(): function _get_api (line 110) | def _get_api(f): function _init_api (line 116) | def _init_api(namespace, target_module_name=None): function _init_api_prefix (line 133) | def _init_api_prefix(module_name, prefix): FILE: python/mxnet/_ffi/node_generic.py function _scalar_type_inference (line 26) | def _scalar_type_inference(value): function convert_to_node (line 43) | def convert_to_node(value): function const (line 79) | def const(value, dtype=None): FILE: python/mxnet/_ffi/object.py function _new_object (line 42) | def _new_object(cls): class Object (line 47) | class Object(_ObjectBase): function register_object (line 51) | def register_object(type_key=None): function getitem_helper (line 90) | def getitem_helper(obj, elem_getter, length, idx): FILE: python/mxnet/_ffi/runtime_ctypes.py class TVMByteArray (line 24) | class TVMByteArray(ctypes.Structure): FILE: python/mxnet/_global_var.py function _set_ndarray_class (line 23) | def _set_ndarray_class(cls): function _set_np_ndarray_class (line 28) | def _set_np_ndarray_class(cls): FILE: python/mxnet/_numpy_op_doc.py function _np_sometrue (line 23) | def _np_sometrue(a, axis=None, keepdims=False, out=None): function _npx_nonzero (line 36) | def _npx_nonzero(a): function _np_repeat (line 83) | def _np_repeat(a, repeats, axis=None): function _np_dot (line 130) | def _np_dot(a, b, out=None): function _np_copy (line 192) | def _np_copy(a, out=None): function _np_reshape (line 239) | def _np_reshape(a, newshape, order='C', out=None): function _np_squeeze (line 300) | def _np_squeeze(a, axis=None, out=None): function _np_prod (line 351) | def _np_prod(a, axis=None, dtype=None, out=None, keepdims=False): function _np_product (line 434) | def _np_product(a, axis=None, dtype=None, out=None, keepdims=False): function _np_moveaxis (line 445) | def _np_moveaxis(a, source, destination): function _np__random_shuffle (line 488) | def _np__random_shuffle(x): function _npx_constraint_check (line 524) | def _npx_constraint_check(x, msg): function _npx_reshape (line 563) | def _npx_reshape(a, newshape, reverse=False, order='C'): function _npx_index_add (line 629) | def _npx_index_add(a, ind, val): function _npx_index_update (line 705) | def _npx_index_update(a, ind, val): function _np_diag (line 774) | def _np_diag(array, k=0): function _np_diagonal (line 809) | def _np_diagonal(a, offset=0, axis1=0, axis2=1): function _np_diagflat (line 861) | def _np_diagflat(array, k=0): FILE: python/mxnet/amp/amp.py function _cast_symbol_NDArray (line 57) | def _cast_symbol_NDArray(s, dtype, is_numpy_module=False): function _get_nd_fun_to_wrap (line 68) | def _get_nd_fun_to_wrap(name, module, submodule_dict): function _get_np_fun_to_wrap (line 86) | def _get_np_fun_to_wrap(name, ns_prefix): function _wrap_module_functions (line 106) | def _wrap_module_functions(module, is_numpy_module, target_dtype, get_al... function _wrap_loss_output_functions (line 255) | def _wrap_loss_output_functions(module, ls, target_dtype): function scale_loss (line 291) | def scale_loss(loss, optimizer_or_trainer): function warn_if_model_exists (line 301) | def warn_if_model_exists(): function init (line 309) | def init(target_dtype='float16', target_precision_ops=None, function init_trainer (line 379) | def init_trainer(optimizer_or_trainer): function unscale (line 407) | def unscale(optimizer_or_trainer): function convert_symbol (line 431) | def convert_symbol(sym, input_dtypes, param_dtypes, target_dtype, target... function convert_model (line 574) | def convert_model(sym, arg_params, aux_params, input_dtypes, target_dtype, function convert_hybrid_block (line 646) | def convert_hybrid_block(block, data_example, target_dtype, target_dtype... function list_lp16_ops (line 722) | def list_lp16_ops(target_dtype): function list_fp32_ops (line 731) | def list_fp32_ops(target_dtype): function list_lp16_fp32_ops (line 740) | def list_lp16_fp32_ops(target_dtype): function list_conditional_fp32_ops (line 749) | def list_conditional_fp32_ops(target_dtype): function list_widest_type_cast (line 758) | def list_widest_type_cast(target_dtype): function list_loss_output_functions (line 767) | def list_loss_output_functions(target_dtype): function list_lp16_use_fp32_params (line 776) | def list_lp16_use_fp32_params(target_dtype): FILE: python/mxnet/amp/loss_scaler.py class LossScaler (line 26) | class LossScaler(object): method __init__ (line 34) | def __init__(self): method loss_scale (line 42) | def loss_scale(self): method has_overflow (line 45) | def has_overflow(self, params): FILE: python/mxnet/attribute.py class AttrScope (line 23) | class AttrScope: method __init__ (line 35) | def __init__(self, **kwargs): method get (line 42) | def get(self, attr): method __enter__ (line 64) | def __enter__(self): # pylint: disable=protected-access method __exit__ (line 73) | def __exit__(self, ptype, value, trace): function current (line 81) | def current(): FILE: python/mxnet/autograd.py function set_recording (line 34) | def set_recording(is_recording): #pylint: disable=redefined-outer-name function set_training (line 51) | def set_training(train_mode): #pylint: disable=redefined-outer-name function is_recording (line 69) | def is_recording(): function is_training (line 80) | def is_training(): class _RecordingStateScope (line 92) | class _RecordingStateScope(object): method __init__ (line 102) | def __init__(self, is_record, train_mode): #pylint: disable=redefined-... method __enter__ (line 108) | def __enter__(self): method __exit__ (line 114) | def __exit__(self, ptype, value, trace): function record (line 121) | def record(train_mode=True): #pylint: disable=redefined-outer-name function pause (line 145) | def pause(train_mode=False): #pylint: disable=redefined-outer-name function train_mode (line 165) | def train_mode(): function predict_mode (line 180) | def predict_mode(): function mark_variables (line 196) | def mark_variables(variables, gradients, grad_reqs='write'): function _parse_head (line 225) | def _parse_head(heads, head_grads): function backward (line 245) | def backward(heads, head_grads=None, retain_graph=False, train_mode=True... function grad (line 272) | def grad(heads, variables, head_grads=None, retain_graph=None, create_gr... function get_symbol (line 349) | def get_symbol(x): class Function (line 369) | class Function(object): class _Registry (line 410) | class _Registry(object): method __init__ (line 412) | def __init__(self): method inc (line 417) | def inc(self): method __init__ (line 427) | def __init__(self): method save_for_backward (line 431) | def save_for_backward(self, *args): method __call__ (line 434) | def __call__(self, *inputs): method forward (line 515) | def forward(self, *inputs): method backward (line 519) | def backward(self, *output_grads): FILE: python/mxnet/base.py function data_dir_default (line 64) | def data_dir_default(): function data_dir (line 76) | def data_dir(): class _NullType (line 84) | class _NullType(object): method __repr__ (line 86) | def __repr__(self): class MXNetError (line 93) | class MXNetError(RuntimeError): function register_error (line 99) | def register_error(func_name=None, cls=None): function _valid_error_name (line 140) | def _valid_error_name(name): function _find_error_type (line 145) | def _find_error_type(line): function c2pyerror (line 166) | def c2pyerror(err_msg): class NotImplementedForSymbol (line 208) | class NotImplementedForSymbol(MXNetError): method __init__ (line 210) | def __init__(self, function, alias, *args): method __str__ (line 216) | def __str__(self): function get_last_ffi_error (line 226) | def get_last_ffi_error(): function check_call (line 241) | def check_call(ret): class NotSupportedForSparseNDArray (line 256) | class NotSupportedForSparseNDArray(MXNetError): method __init__ (line 258) | def __init__(self, function, alias, *args): method __str__ (line 264) | def __str__(self): class MXCallbackList (line 274) | class MXCallbackList(ctypes.Structure): function _load_lib (line 284) | def _load_lib(): function c_str (line 350) | def c_str(string): function c_str_array (line 371) | def c_str_array(strings): function c_array (line 389) | def c_array(ctype, values): function c_array_buf (line 418) | def c_array_buf(ctype, buf): function c_handle_array (line 447) | def c_handle_array(objs): function ctypes2buffer (line 465) | def ctypes2buffer(cptr, length): function ctypes2numpy_shared (line 489) | def ctypes2numpy_shared(cptr, shape): function build_param_doc (line 516) | def build_param_doc(arg_names, arg_types, arg_descs, remove_dup=True): function _notify_shutdown (line 555) | def _notify_shutdown(): function add_fileline_to_docstring (line 563) | def add_fileline_to_docstring(module, incursive=True): function _as_list (line 599) | def _as_list(obj): function _get_op_name_prefix (line 621) | def _get_op_name_prefix(op_name): function _init_op_module (line 633) | def _init_op_module(root_namespace, module_name, make_op_func): function _generate_op_module_signature (line 706) | def _generate_op_module_signature(root_namespace, module_name, op_code_g... function _is_np_op (line 838) | def _is_np_op(op_name): function _output_is_list (line 843) | def _output_is_list(op_name): function _get_op_submodule_name (line 859) | def _get_op_submodule_name(op_name, op_name_prefix, submodule_name_list): function _init_np_op_module (line 868) | def _init_np_op_module(root_module_name, np_module_name, mx_module_name,... FILE: python/mxnet/callback.py function do_checkpoint (line 26) | def do_checkpoint(prefix, period=1): function log_train_metric (line 64) | def log_train_metric(period, auto_reset=False): class Speedometer (line 91) | class Speedometer(object): method __init__ (line 113) | def __init__(self, batch_size, frequent=50, auto_reset=True): method __call__ (line 121) | def __call__(self, param): class ProgressBar (line 155) | class ProgressBar(object): method __init__ (line 172) | def __init__(self, total, length=80): method __call__ (line 176) | def __call__(self, param): class LogValidationMetricsCallback (line 185) | class LogValidationMetricsCallback(object): method __call__ (line 188) | def __call__(self, param): FILE: python/mxnet/container.py class ADT (line 26) | class ADT(Object): method __init__ (line 37) | def __init__(self, tag, fields): method tag (line 44) | def tag(self): method __getitem__ (line 47) | def __getitem__(self, idx): method __len__ (line 51) | def __len__(self): class Map (line 55) | class Map(Object): method __getitem__ (line 63) | def __getitem__(self, k): method __contains__ (line 66) | def __contains__(self, k): method items (line 69) | def items(self): method __len__ (line 74) | def __len__(self): method get (line 77) | def get(self, key, default=None): class String (line 96) | class String(str, PyNativeObject): method __new__ (line 107) | def __new__(cls, content): method __from_mxnet_object__ (line 114) | def __from_mxnet_object__(cls, obj): FILE: python/mxnet/context.py function Context (line 23) | def Context(*args, **kwargs): function current_context (line 29) | def current_context(): FILE: python/mxnet/contrib/io.py class DataLoaderIter (line 24) | class DataLoaderIter(DataIter): method __init__ (line 52) | def __init__(self, loader, data_name='data', label_name='softmax_label... method reset (line 64) | def reset(self): method iter_next (line 67) | def iter_next(self): method getdata (line 74) | def getdata(self): method getlabel (line 82) | def getlabel(self): method getpad (line 90) | def getpad(self): method getindex (line 93) | def getindex(self): FILE: python/mxnet/contrib/onnx/__init__.py function export_model (line 21) | def export_model(*args, **kwargs): FILE: python/mxnet/contrib/quantization.py function _multilist_iterator (line 36) | def _multilist_iterator(arg, func): function _quantize_params (line 50) | def _quantize_params(qsym, params, min_max_dict): function _quantize_symbol (line 105) | def _quantize_symbol(sym, device, excluded_symbols=None, excluded_operat... class CalibrationCollector (line 179) | class CalibrationCollector(object): method __init__ (line 183) | def __init__(self): method collect (line 188) | def collect(self, name, op_name, arr): method post_collect (line 203) | def post_collect(self): class _LayerHistogramCollector (line 210) | class _LayerHistogramCollector(CalibrationCollector): method __init__ (line 215) | def __init__(self, quantized_dtype, num_bins=8001, include_layers=None... method collect (line 223) | def collect(self, name, op_name, arr): method post_collect (line 239) | def post_collect(self): method combine_histogram (line 244) | def combine_histogram(old_hist, arr, new_min, new_max, new_th): method get_optimal_threshold (line 263) | def get_optimal_threshold(hist_data, quantized_dtype, num_quantized_bi... method get_optimal_thresholds (line 287) | def get_optimal_thresholds(hist_dict, quantized_dtype, num_quantized_b... class _LayerOutputMinMaxCollector (line 311) | class _LayerOutputMinMaxCollector(CalibrationCollector): method __init__ (line 315) | def __init__(self, quantized_dtype, include_layers=None, logger=None): method collect (line 322) | def collect(self, name, op_name, arr): function _calibrate_quantized_sym (line 339) | def _calibrate_quantized_sym(qsym, min_max_dict): function _collect_layer_statistics (line 364) | def _collect_layer_statistics(sym_block, data, collector, num_inputs, nu... function _generate_list_of_data_desc (line 382) | def _generate_list_of_data_desc(data_shapes, data_types): function quantize_model (line 423) | def quantize_model(sym, arg_params, aux_params, data_names=('data',), function quantize_model_onednn (line 571) | def quantize_model_onednn(sym, arg_params, aux_params, data_names=('data... function quantize_graph (line 613) | def quantize_graph(sym, arg_params, aux_params, device=cpu(), function calib_graph (line 740) | def calib_graph(qsym, arg_params, aux_params, collector, function quantize_net (line 799) | def quantize_net(network, quantized_dtype='auto', quantize_mode='full', ... FILE: python/mxnet/contrib/tensorboard.py class LogMetricsCallback (line 24) | class LogMetricsCallback(object): method __init__ (line 56) | def __init__(self, logging_dir, prefix=None): method __call__ (line 64) | def __call__(self, param): FILE: python/mxnet/contrib/tensorrt.py function set_use_fp16 (line 21) | def set_use_fp16(status): function get_use_fp16 (line 30) | def get_use_fp16(): function init_tensorrt_params (line 37) | def init_tensorrt_params(sym, arg_params, aux_params): FILE: python/mxnet/contrib/text/embedding.py function register (line 40) | def register(embedding_cls): function create (line 63) | def create(embedding_name, **kwargs): function get_pretrained_file_names (line 90) | def get_pretrained_file_names(embedding_name=None): class _TokenEmbedding (line 133) | class _TokenEmbedding(vocab.Vocabulary): method __init__ (line 183) | def __init__(self, **kwargs): method _get_download_file_name (line 187) | def _get_download_file_name(cls, pretrained_file_name): method _get_pretrained_file_url (line 191) | def _get_pretrained_file_url(cls, pretrained_file_name): method _get_pretrained_file (line 200) | def _get_pretrained_file(cls, embedding_root, pretrained_file_name): method _load_embedding (line 232) | def _load_embedding(self, pretrained_file_path, elem_delim, init_unkno... method _index_tokens_from_vocabulary (line 306) | def _index_tokens_from_vocabulary(self, vocabulary): method _set_idx_to_vec_by_embeddings (line 315) | def _set_idx_to_vec_by_embeddings(self, token_embeddings, vocab_len, v... method _build_embedding_for_vocabulary (line 347) | def _build_embedding_for_vocabulary(self, vocabulary): method vec_len (line 361) | def vec_len(self): method idx_to_vec (line 365) | def idx_to_vec(self): method get_vecs_by_tokens (line 368) | def get_vecs_by_tokens(self, tokens, lower_case_backup=False): method update_token_vectors (line 413) | def update_token_vectors(self, tokens, new_vectors): method _check_pretrained_file_names (line 460) | def _check_pretrained_file_names(cls, pretrained_file_name): class GloVe (line 477) | class GloVe(_TokenEmbedding): method _get_download_file_name (line 527) | def _get_download_file_name(cls, pretrained_file_name): method __init__ (line 534) | def __init__(self, pretrained_file_name='glove.840B.300d.txt', class FastText (line 549) | class FastText(_TokenEmbedding): method _get_download_file_name (line 613) | def _get_download_file_name(cls, pretrained_file_name): method __init__ (line 617) | def __init__(self, pretrained_file_name='wiki.simple.vec', class CustomEmbedding (line 631) | class CustomEmbedding(_TokenEmbedding): method __init__ (line 664) | def __init__(self, pretrained_file_path, elem_delim=' ', encoding='utf8', class CompositeEmbedding (line 673) | class CompositeEmbedding(_TokenEmbedding): method __init__ (line 692) | def __init__(self, vocabulary, token_embeddings): FILE: python/mxnet/contrib/text/utils.py function count_tokens_from_str (line 26) | def count_tokens_from_str(source_str, token_delim=' ', seq_delim='\n', FILE: python/mxnet/contrib/text/vocab.py class Vocabulary (line 28) | class Vocabulary(object): method __init__ (line 73) | def __init__(self, counter=None, most_freq_count=None, min_freq=1, unk... method _index_unknown_and_reserved_tokens (line 92) | def _index_unknown_and_reserved_tokens(self, unknown_token, reserved_t... method _index_counter_keys (line 107) | def _index_counter_keys(self, counter, unknown_token, reserved_tokens,... method __len__ (line 135) | def __len__(self): method token_to_idx (line 139) | def token_to_idx(self): method idx_to_token (line 146) | def idx_to_token(self): method unknown_token (line 153) | def unknown_token(self): method reserved_tokens (line 157) | def reserved_tokens(self): method to_indices (line 160) | def to_indices(self, tokens): method to_tokens (line 186) | def to_tokens(self, indices): FILE: python/mxnet/cuda/__init__.py function cuda_profiler_start (line 22) | def cuda_profiler_start(): function cuda_profiler_stop (line 26) | def cuda_profiler_stop(): FILE: python/mxnet/cuda/nvtx.py function range_push (line 34) | def range_push(name, color=ORANGE): function range_pop (line 40) | def range_pop(): class range (line 44) | class range: method __init__ (line 45) | def __init__(self, name, color=ORANGE): method __enter__ (line 49) | def __enter__(self): method __exit__ (line 52) | def __exit__(self, exc_type, exc_val, exc_tb): FILE: python/mxnet/device.py class Device (line 24) | class Device: method __init__ (line 67) | def __init__(self, device_type, device_id=0): method device_type (line 77) | def device_type(self): method __hash__ (line 93) | def __hash__(self): method __eq__ (line 97) | def __eq__(self, other): method __str__ (line 105) | def __str__(self): method __repr__ (line 108) | def __repr__(self): method __enter__ (line 111) | def __enter__(self): method __exit__ (line 117) | def __exit__(self, ptype, value, trace): method empty_cache (line 120) | def empty_cache(self): function cpu (line 139) | def cpu(device_id=0): function cpu_pinned (line 169) | def cpu_pinned(device_id=0): function gpu (line 199) | def gpu(device_id=0): function num_gpus (line 231) | def num_gpus(): function gpu_memory_info (line 249) | def gpu_memory_info(device_id=0): function current_device (line 275) | def current_device(): FILE: python/mxnet/dlpack.py function _dlpack_deleter (line 36) | def _dlpack_deleter(pycapsule): class DLDeviceType (line 45) | class DLDeviceType(enum.IntEnum): class DLContext (line 57) | class DLContext(ctypes.Structure): class DLDataType (line 61) | class DLDataType(ctypes.Structure): class DLTensor (line 78) | class DLTensor(ctypes.Structure): class DLManagedTensor (line 87) | class DLManagedTensor(ctypes.Structure): function dl_managed_tensor_deleter (line 99) | def dl_managed_tensor_deleter(dl_managed_tensor_handle): function ndarray_from_dlpack (line 104) | def ndarray_from_dlpack(array_cls): function ndarray_to_dlpack_for_read (line 139) | def ndarray_to_dlpack_for_read(): function ndarray_to_dlpack_for_write (line 153) | def ndarray_to_dlpack_for_write(): function ndarray_from_numpy (line 168) | def ndarray_from_numpy(array_cls, array_create_fn): FILE: python/mxnet/engine.py function set_bulk_size (line 25) | def set_bulk_size(size): class _BulkScope (line 48) | class _BulkScope(object): method __init__ (line 50) | def __init__(self, size): method __enter__ (line 54) | def __enter__(self): method __exit__ (line 58) | def __exit__(self, ptype, value, trace): function bulk (line 62) | def bulk(size): FILE: python/mxnet/error.py class InternalError (line 31) | class InternalError(MXNetError): method __init__ (line 46) | def __init__(self, msg): FILE: python/mxnet/executor.py class Executor (line 25) | class Executor: method __init__ (line 37) | def __init__(self, sym, device, args, args_grad, grad_req, aux_states,... method get_optimized_symbol (line 127) | def get_optimized_symbol(self): method forward (line 138) | def forward(self, is_train=False, **kwargs): method backward (line 190) | def backward(self, out_grads=None): method aux_arrays (line 233) | def aux_arrays(self): method arg_arrays (line 243) | def arg_arrays(self): method grad_arrays (line 253) | def grad_arrays(self): method arg_dict (line 273) | def arg_dict(self): method aux_dict (line 292) | def aux_dict(self): method grad_dict (line 311) | def grad_dict(self): method output_dict (line 326) | def output_dict(self): method copy_params_from (line 343) | def copy_params_from(self, arg_params, aux_params=None, allow_extra_pa... FILE: python/mxnet/gluon/block.py function _block_scope (line 55) | def _block_scope(block): function _gather_type_device_info (line 72) | def _gather_type_device_info(args): function _flatten (line 119) | def _flatten(args, inout_str): function _regroup (line 160) | def _regroup(args, fmt): class Block (line 204) | class Block: method __init__ (line 234) | def __init__(self): method __repr__ (line 240) | def __repr__(self): method __setattr__ (line 247) | def __setattr__(self, name, value): method _check_container_with_block (line 264) | def _check_container_with_block(self): method _alias (line 292) | def _alias(self): method params (line 296) | def params(self): method collect_params (line 301) | def collect_params(self, select=None): method _collect_params_with_prefix (line 329) | def _collect_params_with_prefix(self, prefix='', select=None): method save_parameters (line 342) | def save_parameters(self, filename, deduplicate=False): method load_parameters (line 381) | def load_parameters(self, filename, device=None, allow_missing=False, method load_dict (line 436) | def load_dict(self, param_dict, device=None, allow_missing=False, method register_child (line 494) | def register_child(self, block, name=None): method register_forward_pre_hook (line 501) | def register_forward_pre_hook(self, hook): method register_forward_hook (line 520) | def register_forward_hook(self, hook): method apply (line 539) | def apply(self, fn): method initialize (line 557) | def initialize(self, init=initializer.Uniform(), device=None, verbose=... method save (line 579) | def save(self, prefix): method load (line 650) | def load(self, prefix): method hybridize (line 716) | def hybridize(self, active=True, **kwargs): method cast (line 722) | def cast(self, dtype): method zero_grad (line 735) | def zero_grad(self): method reset_device (line 758) | def reset_device(self, device): method reset_ctx (line 771) | def reset_ctx(self, ctx): method setattr (line 777) | def setattr(self, name, value): method share_parameters (line 800) | def share_parameters(self, shared): method _shared_parameters (line 841) | def _shared_parameters(self, shared, shared_set, prefix=""): method __call__ (line 852) | def __call__(self, *args): method forward (line 865) | def forward(self, *args): method register_op_hook (line 877) | def register_op_hook(self, callback, monitor_all=False): method summary (line 894) | def summary(self, *inputs): class HybridBlock (line 1006) | class HybridBlock(Block): class OptConstraint (line 1048) | class OptConstraint: class Flag (line 1049) | class Flag(enum.Flag): method __init__ (line 1052) | def __init__(self, flag) -> None: method __enter__ (line 1056) | def __enter__(self): method __exit__ (line 1061) | def __exit__(self, ptype, value, trace): method disable_all (line 1065) | def disable_all(): method disable_amp (line 1071) | def disable_amp(): method __init__ (line 1074) | def __init__(self): method __setattr__ (line 1093) | def __setattr__(self, name, value): method generate_arg_names (line 1104) | def generate_arg_names(arg_num): method _get_graph (line 1107) | def _get_graph(self, *args): method _build_cache (line 1131) | def _build_cache(self, *args, update_graph=True): method _deferred_infer_shape (line 1249) | def _deferred_infer_shape(self, *args): method _call_cached_op (line 1257) | def _call_cached_op(self, *args): method optimize_for (line 1308) | def optimize_for(self, x, *args, backend=None, clear=False, method _clear_cached_op (line 1396) | def _clear_cached_op(self): method register_child (line 1401) | def register_child(self, block, name=None): method hybridize (line 1414) | def hybridize(self, active=True, method cast (line 1464) | def cast(self, dtype): method _infer_attrs (line 1472) | def _infer_attrs(self, infer_fn, attr, *args): method infer_shape (line 1488) | def infer_shape(self, *args): method infer_type (line 1502) | def infer_type(self, *args): method export (line 1506) | def export(self, path, epoch=0, remove_amp_cast=True): method register_op_hook (line 1583) | def register_op_hook(self, callback, monitor_all=False): method __call__ (line 1611) | def __call__(self, x, *args): method forward (line 1648) | def forward(self, x, *args): method reset_device (line 1654) | def reset_device(self, device): method reset_ctx (line 1672) | def reset_ctx(self, ctx): class SymbolBlock (line 1679) | class SymbolBlock(HybridBlock): method imports (line 1712) | def imports(symbol_file, input_names, param_file=None, device=None, al... method __repr__ (line 1767) | def __repr__(self): method __init__ (line 1776) | def __init__(self, outputs, inputs, params=None): method infer_shape (line 1840) | def infer_shape(self, *args): method __call__ (line 1844) | def __call__(self, x, *args): method forward (line 1856) | def forward(self, x, *args): method _clear_cached_op (line 1874) | def _clear_cached_op(self): method cast (line 1879) | def cast(self, dtype): function _infer_param_types (line 1905) | def _infer_param_types(in_params, out_params, arg_params, aux_params, de... function set_optimization_constraints (line 1972) | def set_optimization_constraints(state): function get_optimization_constraints (line 1978) | def get_optimization_constraints(): FILE: python/mxnet/gluon/contrib/data/vision/dataloader.py function create_image_augment (line 34) | def create_image_augment(data_shape, resize=0, rand_crop=False, rand_res... class ImageDataLoader (line 140) | class ImageDataLoader(object): method __init__ (line 186) | def __init__(self, batch_size, data_shape, path_imgrec=None, path_imgl... method __iter__ (line 240) | def __iter__(self): method __len__ (line 243) | def __len__(self): function create_bbox_augment (line 246) | def create_bbox_augment(data_shape, rand_crop=0, rand_pad=0, rand_gray=0, class ImageBboxDataLoader (line 364) | class ImageBboxDataLoader(object): method __init__ (line 405) | def __init__(self, batch_size, data_shape, path_imgrec=None, path_imgl... method __iter__ (line 468) | def __iter__(self): method __len__ (line 471) | def __len__(self): class BboxLabelTransform (line 474) | class BboxLabelTransform(Block): method __init__ (line 483) | def __init__(self, coord_normalized=True): method forward (line 487) | def forward(self, img, label): FILE: python/mxnet/gluon/contrib/data/vision/transforms/bbox/bbox.py class ImageBboxRandomFlipLeftRight (line 34) | class ImageBboxRandomFlipLeftRight(Block): method __init__ (line 55) | def __init__(self, p=0.5): method forward (line 59) | def forward(self, img, bbox): method _flip_image (line 75) | def _flip_image(self, img): method _flip_bbox (line 81) | def _flip_bbox(self, img, bbox): class ImageBboxCrop (line 90) | class ImageBboxCrop(Block): method __init__ (line 115) | def __init__(self, crop, allow_outside_center=False): method forward (line 130) | def forward(self, img, bbox): class ImageBboxRandomCropWithConstraints (line 146) | class ImageBboxRandomCropWithConstraints(Block): method __init__ (line 187) | def __init__(self, p=0.5, min_scale=0.3, max_scale=1, method forward (line 200) | def forward(self, img, bbox): class ImageBboxRandomExpand (line 216) | class ImageBboxRandomExpand(Block): method __init__ (line 248) | def __init__(self, p=0.5, max_ratio=4, fill=0, keep_ratio=True): method forward (line 255) | def forward(self, img, bbox): class ImageBboxResize (line 297) | class ImageBboxResize(Block): method __init__ (line 321) | def __init__(self, width, height, interp=1): method forward (line 326) | def forward(self, img, bbox): FILE: python/mxnet/gluon/contrib/data/vision/transforms/bbox/utils.py function _check_bbox_shape (line 26) | def _check_bbox_shape(bbox): function bbox_crop (line 30) | def bbox_crop(bbox, crop_box=None, allow_outside_center=True): function bbox_flip (line 85) | def bbox_flip(bbox, size, flip_x=False, flip_y=False): function bbox_resize (line 124) | def bbox_resize(bbox, in_size, out_size): function bbox_translate (line 159) | def bbox_translate(bbox, x_offset=0, y_offset=0): function bbox_iou (line 185) | def bbox_iou(bbox_a, bbox_b, offset=0): function bbox_xywh_to_xyxy (line 218) | def bbox_xywh_to_xyxy(xywh): function bbox_xyxy_to_xywh (line 252) | def bbox_xyxy_to_xywh(xyxy): function bbox_clip_xyxy (line 286) | def bbox_clip_xyxy(xyxy, width, height): function bbox_random_crop_with_constraints (line 330) | def bbox_random_crop_with_constraints(bbox, size, min_scale=0.3, max_sca... FILE: python/mxnet/gluon/contrib/estimator/batch_processor.py class BatchProcessor (line 28) | class BatchProcessor(object): method __init__ (line 40) | def __init__(self): method _get_data_and_label (line 43) | def _get_data_and_label(self, batch, ctx, batch_axis=0): method evaluate_batch (line 50) | def evaluate_batch(self, estimator, method fit_batch (line 70) | def fit_batch(self, estimator, FILE: python/mxnet/gluon/contrib/estimator/estimator.py class Estimator (line 42) | class Estimator(object): method __init__ (line 110) | def __init__(self, net, method _check_loss (line 141) | def _check_loss(self, loss): method _check_context (line 147) | def _check_context(self, context): method _check_devices (line 153) | def _check_devices(self, devices): method _check_batch_processor (line 186) | def _check_batch_processor(self, batch_processor): method _initialize (line 198) | def _initialize(self, initializer): method _check_trainer (line 218) | def _check_trainer(self, trainer): method _is_initialized (line 230) | def _is_initialized(self): method _get_data_and_label (line 239) | def _get_data_and_label(self, batch, device, batch_axis=0): method _add_default_training_metrics (line 246) | def _add_default_training_metrics(self): method _add_validation_metrics (line 259) | def _add_validation_metrics(self): method train_metrics (line 272) | def train_metrics(self): method val_metrics (line 276) | def val_metrics(self): method evaluate (line 279) | def evaluate(self, method fit (line 333) | def fit(self, train_data, method _prepare_default_handlers (line 430) | def _prepare_default_handlers(self, val_data, event_handlers): method _prepare_default_validation_handlers (line 468) | def _prepare_default_validation_handlers(self, event_handlers): method _categorize_handlers (line 491) | def _categorize_handlers(self, event_handlers): FILE: python/mxnet/gluon/contrib/estimator/event_handler.py class EventHandler (line 37) | class EventHandler(object): function _check_event_handlers (line 41) | def _check_event_handlers(handlers): class TrainBegin (line 52) | class TrainBegin(EventHandler): method train_begin (line 53) | def train_begin(self, estimator, *args, **kwargs): class TrainEnd (line 57) | class TrainEnd(EventHandler): method train_end (line 58) | def train_end(self, estimator, *args, **kwargs): class EpochBegin (line 62) | class EpochBegin(EventHandler): method epoch_begin (line 63) | def epoch_begin(self, estimator, *args, **kwargs): class EpochEnd (line 67) | class EpochEnd(EventHandler): method epoch_end (line 68) | def epoch_end(self, estimator, *args, **kwargs): class BatchBegin (line 72) | class BatchBegin(EventHandler): method batch_begin (line 73) | def batch_begin(self, estimator, *args, **kwargs): class BatchEnd (line 77) | class BatchEnd(EventHandler): method batch_end (line 78) | def batch_end(self, estimator, *args, **kwargs): class StoppingHandler (line 82) | class StoppingHandler(TrainBegin, BatchEnd, EpochEnd): method __init__ (line 96) | def __init__(self, max_epoch=None, max_batch=None): method train_begin (line 103) | def train_begin(self, estimator, *args, **kwargs): method batch_end (line 109) | def batch_end(self, estimator, *args, **kwargs): method epoch_end (line 115) | def epoch_end(self, estimator, *args, **kwargs): class MetricHandler (line 122) | class MetricHandler(EpochBegin, BatchEnd): method __init__ (line 138) | def __init__(self, metrics, priority=-1000): method epoch_begin (line 144) | def epoch_begin(self, estimator, *args, **kwargs): method batch_end (line 148) | def batch_end(self, estimator, *args, **kwargs): class ValidationHandler (line 160) | class ValidationHandler(TrainBegin, BatchEnd, EpochEnd): method __init__ (line 190) | def __init__(self, method train_begin (line 208) | def train_begin(self, estimator, *args, **kwargs): method batch_end (line 213) | def batch_end(self, estimator, *args, **kwargs): method epoch_end (line 219) | def epoch_end(self, estimator, *args, **kwargs): class LoggingHandler (line 226) | class LoggingHandler(TrainBegin, TrainEnd, EpochBegin, EpochEnd, BatchBe... method __init__ (line 246) | def __init__(self, log_interval='epoch', method train_begin (line 262) | def train_begin(self, estimator, *args, **kwargs): method train_end (line 280) | def train_end(self, estimator, *args, **kwargs): method batch_begin (line 289) | def batch_begin(self, estimator, *args, **kwargs): method batch_end (line 293) | def batch_end(self, estimator, *args, **kwargs): method epoch_begin (line 310) | def epoch_begin(self, estimator, *args, **kwargs): method epoch_end (line 324) | def epoch_end(self, estimator, *args, **kwargs): class CheckpointHandler (line 336) | class CheckpointHandler(TrainBegin, BatchEnd, EpochEnd): method __init__ (line 377) | def __init__(self, method train_begin (line 435) | def train_begin(self, estimator, *args, **kwargs): method batch_end (line 455) | def batch_end(self, estimator, *args, **kwargs): method epoch_end (line 463) | def epoch_end(self, estimator, *args, **kwargs): method _save_checkpoint (line 468) | def _save_checkpoint(self, estimator): method _save_symbol (line 513) | def _save_symbol(self, estimator): method _save_params_and_trainer (line 525) | def _save_params_and_trainer(self, estimator, file_prefix): method _resume_from_checkpoint (line 541) | def _resume_from_checkpoint(self, estimator): method _find_max_iteration (line 590) | def _find_max_iteration(self, dir, prefix, start, end, saved_checkpoin... class EarlyStoppingHandler (line 611) | class EarlyStoppingHandler(TrainBegin, EpochEnd, TrainEnd): method __init__ (line 630) | def __init__(self, method train_begin (line 685) | def train_begin(self, estimator, *args, **kwargs): method epoch_end (line 695) | def epoch_end(self, estimator, *args, **kwargs): method train_end (line 713) | def train_end(self, estimator, *args, **kwargs): class GradientUpdateHandler (line 719) | class GradientUpdateHandler(BatchEnd): method __init__ (line 731) | def __init__(self, priority=-2000): method batch_end (line 734) | def batch_end(self, estimator, *args, **kwargs): FILE: python/mxnet/gluon/contrib/estimator/utils.py function _check_metrics (line 25) | def _check_metrics(metrics): function _check_handler_metric_ref (line 37) | def _check_handler_metric_ref(handler, known_metrics): function _check_metric_known (line 49) | def _check_metric_known(handler, metric, known_metrics): function _suggest_metric_for_loss (line 58) | def _suggest_metric_for_loss(loss): FILE: python/mxnet/gluon/data/_internal.py class MXDataset (line 36) | class MXDataset(Dataset): method __init__ (line 45) | def __init__(self, handle, **kwargs): method __del__ (line 54) | def __del__(self): method __len__ (line 57) | def __len__(self): method __getitem__ (line 60) | def __getitem__(self, idx): class MXSampler (line 84) | class MXSampler(Sampler): method __init__ (line 93) | def __init__(self, name, **kwargs): method __len__ (line 100) | def __len__(self): method __iter__ (line 107) | def __iter__(self): class MXBatchifyFunction (line 120) | class MXBatchifyFunction(object): method __init__ (line 129) | def __init__(self, handle, **kwargs): method __del__ (line 133) | def __del__(self): method __getstate__ (line 137) | def __getstate__(self): method __setstate__ (line 144) | def __setstate__(self, d): method __call__ (line 153) | def __call__(self, data, num_out=1): function _make_internal_datasets (line 179) | def _make_internal_datasets(handle): function _init_internal_dataset_module (line 253) | def _init_internal_dataset_module(): function _make_internal_batchify_functions (line 266) | def _make_internal_batchify_functions(handle): function _init_internal_batchify_function_module (line 340) | def _init_internal_batchify_function_module(): FILE: python/mxnet/gluon/data/batchify.py class Stack (line 30) | class Stack(object): method __init__ (line 66) | def __init__(self, use_shared_mem=False): method __call__ (line 69) | def __call__(self, data): method __mx_handle__ (line 100) | def __mx_handle__(self): function _pad_arrs_to_max_length (line 104) | def _pad_arrs_to_max_length(arrs, pad_val, use_shared_mem, dtype, round_... class Pad (line 157) | class Pad(object): method __init__ (line 212) | def __init__(self, val=None, dtype=None, round_to=None, use_shared_mem... method __call__ (line 219) | def __call__(self, data): method __mx_handle__ (line 255) | def __mx_handle__(self): function _append_arrs (line 259) | def _append_arrs(arrs, use_shared_mem=False, expand=False, batch_axis=0): class Append (line 279) | class Append(object): method __init__ (line 299) | def __init__(self, expand=True, batch_axis=0, use_shared_mem=False): method __call__ (line 304) | def __call__(self, data): class Group (line 317) | class Group(object): method __init__ (line 347) | def __init__(self, fn, *args): method __call__ (line 360) | def __call__(self, data): method __mx_handle__ (line 379) | def __mx_handle__(self): class AsList (line 391) | class AsList(object): method __call__ (line 404) | def __call__(self, data): FILE: python/mxnet/gluon/data/dataloader.py function rebuild_ndarray (line 47) | def rebuild_ndarray(*args): function reduce_ndarray (line 52) | def reduce_ndarray(data): function rebuild_ndarray (line 56) | def rebuild_ndarray(pid, fd, shape, dtype): function reduce_ndarray (line 62) | def reduce_ndarray(data): function rebuild_np_ndarray (line 73) | def rebuild_np_ndarray(*args): function reduce_np_ndarray (line 78) | def reduce_np_ndarray(data): function rebuild_np_ndarray (line 82) | def rebuild_np_ndarray(pid, fd, shape, dtype): function reduce_np_ndarray (line 88) | def reduce_np_ndarray(data): class ConnectionWrapper (line 99) | class ConnectionWrapper(object): method __init__ (line 103) | def __init__(self, conn): method send (line 106) | def send(self, obj): method recv (line 112) | def recv(self): method __getattr__ (line 117) | def __getattr__(self, name): class Queue (line 123) | class Queue(multiprocessing.queues.Queue): method __init__ (line 125) | def __init__(self, *args, **kwargs): class SimpleQueue (line 133) | class SimpleQueue(multiprocessing.queues.SimpleQueue): method __init__ (line 137) | def __init__(self, *args, **kwargs): function default_batchify_fn (line 144) | def default_batchify_fn(data): function default_mp_batchify_fn (line 157) | def default_mp_batchify_fn(data): function _as_in_context (line 177) | def _as_in_context(data, ctx): function worker_loop_v1 (line 186) | def worker_loop_v1(dataset, key_queue, data_queue, batchify_fn): function fetcher_loop_v1 (line 195) | def fetcher_loop_v1(data_queue, data_buffer, pin_memory=False, class _MultiWorkerIterV1 (line 213) | class _MultiWorkerIterV1(object): method __init__ (line 215) | def __init__(self, num_workers, dataset, batchify_fn, batch_sampler, method __len__ (line 254) | def __len__(self): method __del__ (line 257) | def __del__(self): method _push_next (line 260) | def _push_next(self): method __next__ (line 268) | def __next__(self): method next (line 283) | def next(self): method __iter__ (line 286) | def __iter__(self): method shutdown (line 289) | def shutdown(self): class DataLoaderV1 (line 307) | class DataLoaderV1(object): method __init__ (line 355) | def __init__(self, dataset, batch_size=None, shuffle=False, sampler=None, method __iter__ (line 391) | def __iter__(self): method __len__ (line 406) | def __len__(self): function _thread_worker_initializer (line 410) | def _thread_worker_initializer(active_shape, active_array): function _worker_initializer (line 416) | def _worker_initializer(dataset, active_shape, active_array): function _worker_fn (line 425) | def _worker_fn(samples, batchify_fn, dataset=None): function _thread_worker_fn (line 436) | def _thread_worker_fn(samples, batchify_fn, dataset): class _MultiWorkerIter (line 440) | class _MultiWorkerIter(object): method __init__ (line 442) | def __init__(self, worker_pool, batchify_fn, batch_sampler, pin_memory... method __len__ (line 462) | def __len__(self): method _push_next (line 465) | def _push_next(self): method __next__ (line 475) | def __next__(self): method next (line 507) | def next(self): method __iter__ (line 510) | def __iter__(self): class DataLoader (line 514) | class DataLoader(object): method __init__ (line 591) | def __init__(self, dataset, batch_size=None, shuffle=False, sampler=None, method __iter__ (line 671) | def __iter__(self): method __len__ (line 692) | def __len__(self): method __del__ (line 695) | def __del__(self): function _check_mx_loader_capability (line 702) | def _check_mx_loader_capability(dataset, batch_sampler, batchify_fn): class _MXThreadedDataLoader (line 751) | class _MXThreadedDataLoader(object): method __init__ (line 781) | def __init__(self, dataset, batch_sampler, batchify_fn, method __iter__ (line 803) | def __iter__(self): method __len__ (line 815) | def __len__(self): FILE: python/mxnet/gluon/data/dataset.py class Dataset (line 30) | class Dataset(object): method __getitem__ (line 38) | def __getitem__(self, idx): method __len__ (line 41) | def __len__(self): method filter (line 44) | def filter(self, fn): method shard (line 68) | def shard(self, num_shards, index): method take (line 99) | def take(self, count): method sample (line 120) | def sample(self, sampler): method transform (line 138) | def transform(self, fn, lazy=True): method transform_first (line 163) | def transform_first(self, fn, lazy=True): class SimpleDataset (line 191) | class SimpleDataset(Dataset): method __init__ (line 199) | def __init__(self, data): method __len__ (line 203) | def __len__(self): method __getitem__ (line 206) | def __getitem__(self, idx): method __mx_handle__ (line 209) | def __mx_handle__(self): class _LazyTransformDataset (line 222) | class _LazyTransformDataset(Dataset): method __init__ (line 224) | def __init__(self, data, fn): method __len__ (line 229) | def __len__(self): method __getitem__ (line 232) | def __getitem__(self, idx): method __mx_handle__ (line 238) | def __mx_handle__(self): class _TransformFirstClosure (line 276) | class _TransformFirstClosure(object): method __init__ (line 278) | def __init__(self, fn): method __call__ (line 281) | def __call__(self, x, *args): class _FilteredDataset (line 286) | class _FilteredDataset(Dataset): method __init__ (line 288) | def __init__(self, dataset, fn): method __len__ (line 293) | def __len__(self): method __getitem__ (line 296) | def __getitem__(self, idx): method __mx_handle__ (line 299) | def __mx_handle__(self): class _SampledDataset (line 313) | class _SampledDataset(Dataset): method __init__ (line 315) | def __init__(self, dataset, sampler): method __len__ (line 321) | def __len__(self): method __getitem__ (line 324) | def __getitem__(self, idx): method __mx_handle__ (line 327) | def __mx_handle__(self): class ArrayDataset (line 341) | class ArrayDataset(Dataset): method __init__ (line 352) | def __init__(self, *args): method __getitem__ (line 365) | def __getitem__(self, idx): method __len__ (line 371) | def __len__(self): method __mx_handle__ (line 374) | def __mx_handle__(self): class RecordFileDataset (line 389) | class RecordFileDataset(Dataset): method __init__ (line 399) | def __init__(self, filename): method __getitem__ (line 404) | def __getitem__(self, idx): method __len__ (line 407) | def __len__(self): method __mx_handle__ (line 410) | def __mx_handle__(self): class _DownloadedDataset (line 415) | class _DownloadedDataset(Dataset): method __init__ (line 417) | def __init__(self, root, transform): method __getitem__ (line 433) | def __getitem__(self, idx): method __len__ (line 438) | def __len__(self): method _get_data (line 441) | def _get_data(self): method __mx_handle__ (line 444) | def __mx_handle__(self): FILE: python/mxnet/gluon/data/sampler.py class Sampler (line 26) | class Sampler(object): method __iter__ (line 32) | def __iter__(self): method __len__ (line 35) | def __len__(self): class SequentialSampler (line 39) | class SequentialSampler(Sampler): method __init__ (line 49) | def __init__(self, length, start=0): method __iter__ (line 53) | def __iter__(self): method __len__ (line 56) | def __len__(self): class RandomSampler (line 59) | class RandomSampler(Sampler): method __init__ (line 67) | def __init__(self, length): method __iter__ (line 70) | def __iter__(self): method __len__ (line 75) | def __len__(self): class FilterSampler (line 78) | class FilterSampler(Sampler): method __init__ (line 88) | def __init__(self, fn, dataset): method __iter__ (line 93) | def __iter__(self): method __len__ (line 96) | def __len__(self): class BatchSampler (line 100) | class BatchSampler(Sampler): method __init__ (line 128) | def __init__(self, sampler, batch_size, last_batch='keep'): method __iter__ (line 134) | def __iter__(self): method __len__ (line 153) | def __len__(self): class IntervalSampler (line 165) | class IntervalSampler(Sampler): method __init__ (line 189) | def __init__(self, length, interval, rollover=True): method __iter__ (line 196) | def __iter__(self): method __len__ (line 201) | def __len__(self): FILE: python/mxnet/gluon/data/vision/datasets.py class MNIST (line 39) | class MNIST(dataset._DownloadedDataset): method __init__ (line 57) | def __init__(self, root=os.path.join(base.data_dir(), 'datasets', 'mni... method _get_data (line 71) | def _get_data(self): class FashionMNIST (line 101) | class FashionMNIST(MNIST): method __init__ (line 121) | def __init__(self, root=os.path.join(base.data_dir(), 'datasets', 'fas... class CIFAR10 (line 136) | class CIFAR10(dataset._DownloadedDataset): method __init__ (line 154) | def __init__(self, root=os.path.join(base.data_dir(), 'datasets', 'cif... method _read_batch (line 167) | def _read_batch(self, filename): method _get_data (line 174) | def _get_data(self): class CIFAR100 (line 200) | class CIFAR100(CIFAR10): method __init__ (line 220) | def __init__(self, root=os.path.join(base.data_dir(), 'datasets', 'cif... method _read_batch (line 230) | def _read_batch(self, filename): class ImageRecordDataset (line 238) | class ImageRecordDataset(dataset.RecordFileDataset): method __init__ (line 257) | def __init__(self, filename, flag=1, transform=None): method __getitem__ (line 266) | def __getitem__(self, idx): method __mx_handle__ (line 273) | def __mx_handle__(self): class ImageFolderDataset (line 279) | class ImageFolderDataset(dataset.Dataset): method __init__ (line 311) | def __init__(self, root, flag=1, transform=None): method _list_images (line 323) | def _list_images(self, root): method __getitem__ (line 342) | def __getitem__(self, idx): method __len__ (line 349) | def __len__(self): method __mx_handle__ (line 352) | def __mx_handle__(self): class ImageListDataset (line 364) | class ImageListDataset(dataset.Dataset): method __init__ (line 400) | def __init__(self, root='.', imglist=None, flag=1): method __getitem__ (line 436) | def __getitem__(self, idx): method __len__ (line 442) | def __len__(self): method __mx_handle__ (line 445) | def __mx_handle__(self): FILE: python/mxnet/gluon/data/vision/transforms/__init__.py class Compose (line 34) | class Compose(Sequential): method __init__ (line 58) | def __init__(self, transforms): class HybridCompose (line 81) | class HybridCompose(HybridSequential): method __init__ (line 105) | def __init__(self, transforms): class Cast (line 115) | class Cast(HybridBlock): method __init__ (line 130) | def __init__(self, dtype='float32'): method forward (line 134) | def forward(self, *args): class RandomApply (line 138) | class RandomApply(Sequential): method __init__ (line 156) | def __init__(self, transforms, p=0.5): method forward (line 161) | def forward(self, x, *args): class HybridRandomApply (line 168) | class HybridRandomApply(HybridSequential): method __init__ (line 186) | def __init__(self, transforms, p=0.5): method forward (line 192) | def forward(self, x, *args): FILE: python/mxnet/gluon/data/vision/transforms/image.py function _append_return (line 35) | def _append_return(*args): class ToTensor (line 47) | class ToTensor(HybridBlock): method __init__ (line 82) | def __init__(self): method forward (line 85) | def forward(self, x, *args): class Normalize (line 90) | class Normalize(HybridBlock): method __init__ (line 134) | def __init__(self, mean=0.0, std=1.0): method forward (line 139) | def forward(self, x, *args): class Rotate (line 144) | class Rotate(Block): method __init__ (line 163) | def __init__(self, rotation_degrees, zoom_in=False, zoom_out=False): method forward (line 167) | def forward(self, x, *args): class RandomRotation (line 175) | class RandomRotation(Block): method __init__ (line 197) | def __init__(self, angle_limits, zoom_in=False, zoom_out=False, rotate... method forward (line 207) | def forward(self, x, *args): class RandomResizedCrop (line 217) | class RandomResizedCrop(HybridBlock): method __init__ (line 244) | def __init__(self, size, scale=(0.08, 1.0), ratio=(3.0/4.0, 4.0/3.0), method forward (line 255) | def forward(self, x, *args): class CropResize (line 260) | class CropResize(HybridBlock): method __init__ (line 304) | def __init__(self, x, y, width, height, size=None, interpolation=None): method forward (line 313) | def forward(self, x, *args): class RandomCrop (line 320) | class RandomCrop(HybridBlock): method __init__ (line 346) | def __init__(self, size, pad=None, pad_value=0, interpolation=1): method forward (line 363) | def forward(self, x, *args): class CenterCrop (line 370) | class CenterCrop(HybridBlock): method __init__ (line 397) | def __init__(self, size, interpolation=1): method forward (line 403) | def forward(self, x, *args): class Resize (line 409) | class Resize(HybridBlock): method __init__ (line 443) | def __init__(self, size, keep_ratio=False, interpolation=1): method forward (line 449) | def forward(self, x, *args): class RandomFlipLeftRight (line 453) | class RandomFlipLeftRight(HybridBlock): method __init__ (line 463) | def __init__(self, p=0.5): method forward (line 467) | def forward(self, x, *args): class RandomFlipTopBottom (line 477) | class RandomFlipTopBottom(HybridBlock): method __init__ (line 487) | def __init__(self, p=0.5): method forward (line 491) | def forward(self, x, *args): class RandomBrightness (line 501) | class RandomBrightness(HybridBlock): method __init__ (line 518) | def __init__(self, brightness): method forward (line 522) | def forward(self, x, *args): class RandomContrast (line 527) | class RandomContrast(HybridBlock): method __init__ (line 544) | def __init__(self, contrast): method forward (line 548) | def forward(self, x, *args): class RandomSaturation (line 553) | class RandomSaturation(HybridBlock): method __init__ (line 570) | def __init__(self, saturation): method forward (line 574) | def forward(self, x, *args): class RandomHue (line 579) | class RandomHue(HybridBlock): method __init__ (line 596) | def __init__(self, hue): method forward (line 600) | def forward(self, x, *args): class RandomColorJitter (line 605) | class RandomColorJitter(HybridBlock): method __init__ (line 631) | def __init__(self, brightness=0, contrast=0, saturation=0, hue=0): method forward (line 635) | def forward(self, x, *args): class RandomLighting (line 640) | class RandomLighting(HybridBlock): method __init__ (line 655) | def __init__(self, alpha): method forward (line 659) | def forward(self, x, *args): class RandomGray (line 664) | class RandomGray(HybridBlock): method __init__ (line 672) | def __init__(self, p=0.5): method forward (line 676) | def forward(self, x, *args): FILE: python/mxnet/gluon/loss.py function _apply_weighting (line 34) | def _apply_weighting(loss, weight=None, sample_weight=None): function _batch_mean (line 65) | def _batch_mean(loss, batch_axis): function _batch_sum (line 71) | def _batch_sum(loss, batch_axis): class Loss (line 80) | class Loss(HybridBlock): method __init__ (line 91) | def __init__(self, weight, batch_axis, **kwargs): method __repr__ (line 96) | def __repr__(self): method forward (line 100) | def forward(self, x, *args): class L2Loss (line 116) | class L2Loss(Loss): method __init__ (line 145) | def __init__(self, weight=1., batch_axis=0, **kwargs): method forward (line 148) | def forward(self, pred, label, sample_weight=None): class L1Loss (line 157) | class L1Loss(Loss): method __init__ (line 186) | def __init__(self, weight=None, batch_axis=0, **kwargs): method forward (line 189) | def forward(self, pred, label, sample_weight=None): class SigmoidBinaryCrossEntropyLoss (line 198) | class SigmoidBinaryCrossEntropyLoss(Loss): method __init__ (line 255) | def __init__(self, from_sigmoid=False, weight=None, batch_axis=0, **kw... method forward (line 260) | def forward(self, pred, label, sample_weight=None, pos_weight=None): class SoftmaxCrossEntropyLoss (line 291) | class SoftmaxCrossEntropyLoss(Loss): method __init__ (line 353) | def __init__(self, axis=-1, sparse_label=True, from_logits=False, weig... method forward (line 361) | def forward(self, pred, label, sample_weight=None): class KLDivLoss (line 377) | class KLDivLoss(Loss): method __init__ (line 438) | def __init__(self, from_logits=True, axis=-1, weight=None, batch_axis=0, method forward (line 444) | def forward(self, pred, label, sample_weight=None): class CTCLoss (line 453) | class CTCLoss(Loss): method __init__ (line 511) | def __init__(self, layout='NTC', label_layout='NT', weight=None, **kwa... method forward (line 521) | def forward(self, pred, label, pred_lengths=None, label_lengths=None, ... class HuberLoss (line 534) | class HuberLoss(Loss): method __init__ (line 571) | def __init__(self, rho=1, weight=None, batch_axis=0, **kwargs): method forward (line 575) | def forward(self, pred, label, sample_weight=None): class HingeLoss (line 585) | class HingeLoss(Loss): method __init__ (line 619) | def __init__(self, margin=1, weight=None, batch_axis=0, **kwargs): method forward (line 623) | def forward(self, pred, label, sample_weight=None): class SquaredHingeLoss (line 631) | class SquaredHingeLoss(Loss): method __init__ (line 665) | def __init__(self, margin=1, weight=None, batch_axis=0, **kwargs): method forward (line 669) | def forward(self, pred, label, sample_weight=None): class LogisticLoss (line 677) | class LogisticLoss(Loss): method __init__ (line 712) | def __init__(self, weight=None, batch_axis=0, label_format='signed', *... method forward (line 718) | def forward(self, pred, label, sample_weight=None): class TripletLoss (line 730) | class TripletLoss(Loss): method __init__ (line 763) | def __init__(self, margin=1, weight=None, batch_axis=0, **kwargs): method forward (line 768) | def forward(self, pred, positive, negative, sample_weight=None): class PoissonNLLLoss (line 777) | class PoissonNLLLoss(Loss): method __init__ (line 817) | def __init__(self, weight=None, from_logits=True, batch_axis=0, comput... method forward (line 822) | def forward(self, pred, target, sample_weight=None, epsilon=1e-08): class CosineEmbeddingLoss (line 840) | class CosineEmbeddingLoss(Loss): method __init__ (line 876) | def __init__(self, weight=None, batch_axis=0, margin=0, **kwargs): method forward (line 880) | def forward(self, input1, input2, label, sample_weight=None): method _cosine_similarity (line 891) | def _cosine_similarity(self, x, y, axis=-1): class SDMLLoss (line 901) | class SDMLLoss(Loss): method __init__ (line 937) | def __init__(self, smoothing_parameter=0.3, weight=1., batch_axis=0, *... method _compute_distances (line 943) | def _compute_distances(self, x1, x2): method _compute_labels (line 959) | def _compute_labels(self, batch_size): method forward (line 983) | def forward(self, x1, x2): FILE: python/mxnet/gluon/metric.py function check_label_shapes (line 33) | def check_label_shapes(labels, preds, wrap=False, shape=False): class EvalMetric (line 68) | class EvalMetric(object): method __init__ (line 88) | def __init__(self, name, output_names=None, method __str__ (line 96) | def __str__(self): method get_config (line 99) | def get_config(self): method update_dict (line 111) | def update_dict(self, label, pred): method update (line 134) | def update(self, labels, preds): method reset (line 147) | def reset(self): method get (line 152) | def get(self): method get_name_value (line 173) | def get_name_value(self): function create (line 195) | def create(metric, *args, **kwargs): class CompositeEvalMetric (line 239) | class CompositeEvalMetric(EvalMetric): method __init__ (line 269) | def __init__(self, metrics=None, name='composite', method add (line 277) | def add(self, metric): method get_metric (line 287) | def get_metric(self, index): method update_dict (line 301) | def update_dict(self, labels, preds): # pylint: disable=arguments-differ method update (line 312) | def update(self, labels, preds): method reset (line 326) | def reset(self): method get (line 334) | def get(self): method get_config (line 356) | def get_config(self): class Accuracy (line 370) | class Accuracy(EvalMetric): method __init__ (line 402) | def __init__(self, axis=1, name='accuracy', method update (line 409) | def update(self, labels, preds): class TopKAccuracy (line 444) | class TopKAccuracy(EvalMetric): method __init__ (line 478) | def __init__(self, top_k=1, name='top_k_accuracy', method update (line 487) | def update(self, labels, preds): function predict_with_threshold (line 524) | def predict_with_threshold(pred, threshold=0.5): function one_hot (line 546) | def one_hot(idx, num): class _ClassificationMetrics (line 551) | class _ClassificationMetrics(object): method __init__ (line 571) | def __init__(self, class_type="binary", threshold=0.5, beta=1): method _set (line 577) | def _set(self, num, device): method update_stats (line 588) | def update_stats(self, label, pred): method precision (line 649) | def precision(self): method micro_precision (line 656) | def micro_precision(self): method recall (line 664) | def recall(self): method micro_recall (line 671) | def micro_recall(self): method fscore (line 679) | def fscore(self): method micro_fscore (line 684) | def micro_fscore(self): method binary_matthewscc (line 691) | def binary_matthewscc(self): method total_examples (line 711) | def total_examples(self): method reset_stats (line 717) | def reset_stats(self): class F1 (line 727) | class F1(EvalMetric): method __init__ (line 776) | def __init__(self, name='f1', method update (line 783) | def update(self, labels, preds): method reset (line 807) | def reset(self): class Fbeta (line 816) | class Fbeta(F1): method __init__ (line 867) | def __init__(self, name='fbeta', class BinaryAccuracy (line 877) | class BinaryAccuracy(EvalMetric): method __init__ (line 903) | def __init__(self, name='binary_accuracy', method update (line 909) | def update(self, labels, preds): class MCC (line 940) | class MCC(EvalMetric): method __init__ (line 999) | def __init__(self, name='mcc', method update (line 1005) | def update(self, labels, preds): method reset (line 1024) | def reset(self): class MAE (line 1038) | class MAE(EvalMetric): method __init__ (line 1068) | def __init__(self, name='mae', method update (line 1073) | def update(self, labels, preds): class MSE (line 1099) | class MSE(EvalMetric): method __init__ (line 1128) | def __init__(self, name='mse', method update (line 1133) | def update(self, labels, preds): class RMSE (line 1159) | class RMSE(MSE): method __init__ (line 1188) | def __init__(self, name='rmse', method get (line 1193) | def get(self): class MeanPairwiseDistance (line 1202) | class MeanPairwiseDistance(EvalMetric): method __init__ (line 1233) | def __init__(self, name='mpd', method update (line 1239) | def update(self, labels, preds): class MeanCosineSimilarity (line 1269) | class MeanCosineSimilarity(EvalMetric): method __init__ (line 1302) | def __init__(self, name='cos_sim', method update (line 1308) | def update(self, labels, preds): class CrossEntropy (line 1343) | class CrossEntropy(EvalMetric): method __init__ (line 1388) | def __init__(self, eps=1e-12, ignore_label=None, axis=-1, from_logits=... method update (line 1397) | def update(self, labels, preds): class Perplexity (line 1431) | class Perplexity(CrossEntropy): method __init__ (line 1486) | def __init__(self, eps=1e-12, ignore_label=None, axis=-1, from_logits=... method get (line 1492) | def get(self): class PearsonCorrelation (line 1502) | class PearsonCorrelation(EvalMetric): method __init__ (line 1531) | def __init__(self, name='pearsonr', method reset (line 1537) | def reset(self): method update_variance (line 1549) | def update_variance(self, new_values, *aggregate): method update_cov (line 1559) | def update_cov(self, label, pred): method update (line 1562) | def update(self, labels, preds): method get (line 1585) | def get(self): class PCC (line 1595) | class PCC(EvalMetric): method __init__ (line 1648) | def __init__(self, name='pcc', method _grow (line 1654) | def _grow(self, inc): method _calc_mcc (line 1659) | def _calc_mcc(self, cmat): method update (line 1672) | def update(self, labels, preds): method sum_metric (line 1703) | def sum_metric(self): method reset (line 1706) | def reset(self): class Loss (line 1714) | class Loss(EvalMetric): method __init__ (line 1728) | def __init__(self, name='loss', method update (line 1733) | def update(self, _, preds): class Torch (line 1745) | class Torch(Loss): method __init__ (line 1747) | def __init__(self, name='torch', class CustomMetric (line 1755) | class CustomMetric(EvalMetric): method __init__ (line 1790) | def __init__(self, feval, name=None, allow_extra_outputs=False, method update (line 1803) | def update(self, labels, preds): method get_config (line 1830) | def get_config(self): function np (line 1835) | def np(numpy_feval, name=None, allow_extra_outputs=False): FILE: python/mxnet/gluon/model_zoo/model_store.py function short_hash (line 68) | def short_hash(name): function get_model_file (line 73) | def get_model_file(name, root=os.path.join(base.data_dir(), 'models')): function purge (line 126) | def purge(root=os.path.join(base.data_dir(), 'models')): FILE: python/mxnet/gluon/model_zoo/vision/__init__.py function get_model (line 91) | def get_model(name, **kwargs): FILE: python/mxnet/gluon/model_zoo/vision/alexnet.py class AlexNet (line 33) | class AlexNet(HybridBlock): method __init__ (line 41) | def __init__(self, classes=1000, **kwargs): method forward (line 65) | def forward(self, x): function alexnet (line 72) | def alexnet(pretrained=False, device=cpu(), FILE: python/mxnet/gluon/model_zoo/vision/densenet.py function _make_dense_block (line 32) | def _make_dense_block(num_layers, bn_size, growth_rate, dropout): function _make_dense_layer (line 38) | def _make_dense_layer(growth_rate, bn_size, dropout): function _make_transition (line 55) | def _make_transition(num_output_features): class DenseNet (line 65) | class DenseNet(HybridBlock): method __init__ (line 85) | def __init__(self, num_init_features, growth_rate, block_config, method forward (line 110) | def forward(self, x): function get_densenet (line 125) | def get_densenet(num_layers, pretrained=False, device=cpu(), function densenet121 (line 148) | def densenet121(**kwargs): function densenet161 (line 163) | def densenet161(**kwargs): function densenet169 (line 178) | def densenet169(**kwargs): function densenet201 (line 193) | def densenet201(**kwargs): FILE: python/mxnet/gluon/model_zoo/vision/inception.py function _make_basic_conv (line 32) | def _make_basic_conv(**kwargs): function _make_branch (line 39) | def _make_branch(use_pool, *conv_settings): function _make_A (line 54) | def _make_A(pool_features): function _make_B (line 69) | def _make_B(): function _make_C (line 80) | def _make_C(channels_7x7): function _make_D (line 98) | def _make_D(): function _make_E (line 111) | def _make_E(): function make_aux (line 143) | def make_aux(classes): class Inception3 (line 154) | class Inception3(HybridBlock): method __init__ (line 164) | def __init__(self, classes=1000, **kwargs): method forward (line 191) | def forward(self, x): function inception_v3 (line 198) | def inception_v3(pretrained=False, device=cpu(), FILE: python/mxnet/gluon/model_zoo/vision/mobilenet.py class RELU6 (line 39) | class RELU6(nn.HybridBlock): method __init__ (line 42) | def __init__(self, **kwargs): method forward (line 45) | def forward(self, x): function _add_conv (line 50) | def _add_conv(out, channels=1, kernel=1, stride=1, pad=0, function _add_conv_dw (line 58) | def _add_conv_dw(out, dw_channels, channels, stride, relu6=False): class LinearBottleneck (line 65) | class LinearBottleneck(nn.HybridBlock): method __init__ (line 83) | def __init__(self, in_channels, channels, t, stride, **kwargs): method forward (line 93) | def forward(self, x): class MobileNet (line 102) | class MobileNet(HybridBlock): method __init__ (line 117) | def __init__(self, multiplier=1.0, classes=1000, **kwargs): method forward (line 133) | def forward(self, x): class MobileNetV2 (line 140) | class MobileNetV2(nn.HybridBlock): method __init__ (line 155) | def __init__(self, multiplier=1.0, classes=1000, **kwargs): method forward (line 183) | def forward(self, x): function get_mobilenet (line 191) | def get_mobilenet(multiplier, pretrained=False, device=cpu(), function get_mobilenet_v2 (line 223) | def get_mobilenet_v2(multiplier, pretrained=False, device=cpu(), function mobilenet1_0 (line 256) | def mobilenet1_0(**kwargs): function mobilenet_v2_1_0 (line 272) | def mobilenet_v2_1_0(**kwargs): function mobilenet0_75 (line 289) | def mobilenet0_75(**kwargs): function mobilenet_v2_0_75 (line 305) | def mobilenet_v2_0_75(**kwargs): function mobilenet0_5 (line 322) | def mobilenet0_5(**kwargs): function mobilenet_v2_0_5 (line 338) | def mobilenet_v2_0_5(**kwargs): function mobilenet0_25 (line 355) | def mobilenet0_25(**kwargs): function mobilenet_v2_0_25 (line 371) | def mobilenet_v2_0_25(**kwargs): FILE: python/mxnet/gluon/model_zoo/vision/resnet.py function _conv3x3 (line 39) | def _conv3x3(channels, stride, in_channels): class BasicBlockV1 (line 46) | class BasicBlockV1(HybridBlock): method __init__ (line 62) | def __init__(self, channels, stride, downsample=False, in_channels=0, ... method forward (line 78) | def forward(self, x): class BottleneckV1 (line 92) | class BottleneckV1(HybridBlock): method __init__ (line 108) | def __init__(self, channels, stride, downsample=False, in_channels=0, ... method forward (line 127) | def forward(self, x): class BasicBlockV2 (line 140) | class BasicBlockV2(HybridBlock): method __init__ (line 157) | def __init__(self, channels, stride, downsample=False, in_channels=0, ... method forward (line 169) | def forward(self, x): class BottleneckV2 (line 185) | class BottleneckV2(HybridBlock): method __init__ (line 202) | def __init__(self, channels, stride, downsample=False, in_channels=0, ... method forward (line 216) | def forward(self, x): class ResNetV1 (line 237) | class ResNetV1(HybridBlock): method __init__ (line 255) | def __init__(self, block, layers, channels, classes=1000, thumbnail=Fa... method _make_layer (line 275) | def _make_layer(self, block, layers, channels, stride, in_channels=0): method forward (line 282) | def forward(self, x): class ResNetV2 (line 290) | class ResNetV2(HybridBlock): method __init__ (line 308) | def __init__(self, block, layers, channels, classes=1000, thumbnail=Fa... method _make_layer (line 334) | def _make_layer(self, block, layers, channels, stride, in_channels=0): method forward (line 341) | def forward(self, x): function get_resnet (line 361) | def get_resnet(version, num_layers, pretrained=False, device=cpu(), function resnet18_v1 (line 396) | def resnet18_v1(**kwargs): function resnet34_v1 (line 412) | def resnet34_v1(**kwargs): function resnet50_v1 (line 428) | def resnet50_v1(**kwargs): function resnet101_v1 (line 444) | def resnet101_v1(**kwargs): function resnet152_v1 (line 460) | def resnet152_v1(**kwargs): function resnet18_v2 (line 476) | def resnet18_v2(**kwargs): function resnet34_v2 (line 492) | def resnet34_v2(**kwargs): function resnet50_v2 (line 508) | def resnet50_v2(**kwargs): function resnet101_v2 (line 524) | def resnet101_v2(**kwargs): function resnet152_v2 (line 540) | def resnet152_v2(**kwargs): FILE: python/mxnet/gluon/model_zoo/vision/squeezenet.py function _make_fire (line 32) | def _make_fire(squeeze_channels, expand1x1_channels, expand3x3_channels): function _make_fire_conv (line 43) | def _make_fire_conv(channels, kernel_size, padding=0): class SqueezeNet (line 51) | class SqueezeNet(HybridBlock): method __init__ (line 66) | def __init__(self, version, classes=1000, **kwargs): method forward (line 107) | def forward(self, x): function get_squeezenet (line 114) | def get_squeezenet(version, pretrained=False, device=cpu(), function squeezenet1_0 (line 141) | def squeezenet1_0(**kwargs): function squeezenet1_1 (line 157) | def squeezenet1_1(**kwargs): FILE: python/mxnet/gluon/model_zoo/vision/vgg.py class VGG (line 37) | class VGG(HybridBlock): method __init__ (line 52) | def __init__(self, layers, filters, classes=1000, batch_norm=False, **... method _make_features (line 68) | def _make_features(self, layers, filters, batch_norm): method forward (line 83) | def forward(self, x): function get_vgg (line 98) | def get_vgg(num_layers, pretrained=False, device=cpu(), function vgg11 (line 124) | def vgg11(**kwargs): function vgg13 (line 140) | def vgg13(**kwargs): function vgg16 (line 156) | def vgg16(**kwargs): function vgg19 (line 172) | def vgg19(**kwargs): function vgg11_bn (line 188) | def vgg11_bn(**kwargs): function vgg13_bn (line 206) | def vgg13_bn(**kwargs): function vgg16_bn (line 224) | def vgg16_bn(**kwargs): function vgg19_bn (line 242) | def vgg19_bn(**kwargs): FILE: python/mxnet/gluon/nn/activations.py class Activation (line 30) | class Activation(HybridBlock): method __init__ (line 46) | def __init__(self, activation, **kwargs): method _alias (line 50) | def _alias(self): method forward (line 53) | def forward(self, x): method __repr__ (line 56) | def __repr__(self): class LeakyReLU (line 63) | class LeakyReLU(HybridBlock): method __init__ (line 89) | def __init__(self, alpha, **kwargs): method forward (line 94) | def forward(self, x): method __repr__ (line 97) | def __repr__(self): class PReLU (line 104) | class PReLU(HybridBlock): method __init__ (line 136) | def __init__(self, alpha_initializer=initializer.Constant(0.25), method forward (line 141) | def forward(self, x): class ELU (line 147) | class ELU(HybridBlock): method __init__ (line 167) | def __init__(self, alpha=1.0, **kwargs): method forward (line 171) | def forward(self, x): class SELU (line 176) | class SELU(HybridBlock): method __init__ (line 189) | def __init__(self, **kwargs): method forward (line 192) | def forward(self, x): class GELU (line 197) | class GELU(HybridBlock): method __init__ (line 214) | def __init__(self, approximation='erf', **kwargs): method forward (line 221) | def forward(self, x): class Swish (line 226) | class Swish(HybridBlock): method __init__ (line 244) | def __init__(self, beta=1.0, **kwargs): method forward (line 248) | def forward(self, x): class SiLU (line 253) | class SiLU(HybridBlock): method __init__ (line 272) | def __init__(self, **kwargs): method forward (line 275) | def forward(self, x): FILE: python/mxnet/gluon/nn/basic_layers.py class Sequential (line 36) | class Sequential(Block): method __init__ (line 45) | def __init__(self): method add (line 49) | def add(self, *blocks): method forward (line 55) | def forward(self, x, *args): method __repr__ (line 66) | def __repr__(self): method __getitem__ (line 73) | def __getitem__(self, key): method __len__ (line 82) | def __len__(self): method hybridize (line 85) | def hybridize(self, active=True, **kwargs): class HybridSequential (line 104) | class HybridSequential(HybridBlock): method __init__ (line 114) | def __init__(self): method add (line 118) | def add(self, *blocks): method forward (line 124) | def forward(self, x, *args): method __repr__ (line 135) | def __repr__(self): method __getitem__ (line 142) | def __getitem__(self, key): method __len__ (line 151) | def __len__(self): class Dense (line 156) | class Dense(HybridBlock): method __init__ (line 204) | def __init__(self, units, activation=None, use_bias=True, flatten=True, method forward (line 225) | def forward(self, x): method infer_shape (line 235) | def infer_shape(self, x, *args): method __repr__ (line 244) | def __repr__(self): class Dropout (line 253) | class Dropout(HybridBlock): method __init__ (line 278) | def __init__(self, rate, axes=(), **kwargs): method forward (line 283) | def forward(self, x): method __repr__ (line 289) | def __repr__(self): class _BatchNorm (line 296) | class _BatchNorm(HybridBlock): method __init__ (line 345) | def __init__(self, axis=1, momentum=0.9, epsilon=1e-5, center=True, sc... method cast (line 376) | def cast(self, dtype): method forward (line 381) | def forward(self, x): method infer_shape (line 388) | def infer_shape(self, x, *args): method __repr__ (line 396) | def __repr__(self): class BatchNorm (line 405) | class BatchNorm(_BatchNorm): method __init__ (line 453) | def __init__(self, axis=1, momentum=0.9, epsilon=1e-5, center=True, sc... class Embedding (line 470) | class Embedding(HybridBlock): method __init__ (line 501) | def __init__(self, input_dim, output_dim, dtype='float32', method forward (line 512) | def forward(self, x): method __repr__ (line 516) | def __repr__(self): class Flatten (line 523) | class Flatten(HybridBlock): method __init__ (line 532) | def __init__(self, **kwargs): method forward (line 535) | def forward(self, x): method __repr__ (line 538) | def __repr__(self): class InstanceNorm (line 543) | class InstanceNorm(HybridBlock): method __init__ (line 606) | def __init__(self, axis=1, epsilon=1e-5, center=True, scale=False, method forward (line 620) | def forward(self, x): method infer_shape (line 629) | def infer_shape(self, x, *args): method __repr__ (line 633) | def __repr__(self): class LayerNorm (line 644) | class LayerNorm(HybridBlock): method __init__ (line 697) | def __init__(self, axis=-1, epsilon=1e-5, center=True, scale=True, method forward (line 713) | def forward(self, data): method infer_shape (line 718) | def infer_shape(self, data, *args): method __repr__ (line 724) | def __repr__(self): class GroupNorm (line 735) | class GroupNorm(HybridBlock): method __init__ (line 795) | def __init__(self, num_groups=1, epsilon=1e-5, center=True, scale=True, method forward (line 811) | def forward(self, data): method infer_shape (line 817) | def infer_shape(self, data, *args): method __repr__ (line 821) | def __repr__(self): class Lambda (line 831) | class Lambda(Block): method __init__ (line 853) | def __init__(self, function): method forward (line 870) | def forward(self, *args): method __repr__ (line 873) | def __repr__(self): class HybridLambda (line 879) | class HybridLambda(HybridBlock): method __init__ (line 902) | def __init__(self, function): method forward (line 920) | def forward(self, x, *args): method __repr__ (line 923) | def __repr__(self): class Concatenate (line 929) | class Concatenate(Sequential): method __init__ (line 948) | def __init__(self, axis=-1): method forward (line 952) | def forward(self, x): class HybridConcatenate (line 961) | class HybridConcatenate(HybridSequential): method __init__ (line 980) | def __init__(self, axis=-1): method forward (line 984) | def forward(self, x): class Identity (line 993) | class Identity(HybridBlock): method __init__ (line 1006) | def __init__(self): method forward (line 1009) | def forward(self, x): class SyncBatchNorm (line 1014) | class SyncBatchNorm(BatchNorm): method __init__ (line 1068) | def __init__(self, in_channels=0, num_devices=None, momentum=0.9, epsi... method _get_num_devices (line 1086) | def _get_num_devices(self): method forward (line 1094) | def forward(self, x): FILE: python/mxnet/gluon/nn/conv_layers.py class _Conv (line 38) | class _Conv(HybridBlock): method __init__ (line 87) | def __init__(self, channels, kernel_size, strides, padding, dilation, method forward (line 126) | def forward(self, x): method pre_infer (line 137) | def pre_infer(self): method infer_shape (line 177) | def infer_shape(self, x): method _alias (line 190) | def _alias(self): method __repr__ (line 193) | def __repr__(self): class Conv1D (line 219) | class Conv1D(_Conv): method __init__ (line 284) | def __init__(self, channels, kernel_size, strides=1, padding=0, dilati... class Conv2D (line 299) | class Conv2D(_Conv): method __init__ (line 366) | def __init__(self, channels, kernel_size, strides=(1, 1), padding=(0, 0), class Conv3D (line 381) | class Conv3D(_Conv): method __init__ (line 449) | def __init__(self, channels, kernel_size, strides=(1, 1, 1), padding=(... class Conv1DTranspose (line 464) | class Conv1DTranspose(_Conv): method __init__ (line 532) | def __init__(self, channels, kernel_size, strides=1, padding=0, output... class Conv2DTranspose (line 551) | class Conv2DTranspose(_Conv): method __init__ (line 624) | def __init__(self, channels, kernel_size, strides=(1, 1), padding=(0, 0), class Conv3DTranspose (line 643) | class Conv3DTranspose(_Conv): method __init__ (line 717) | def __init__(self, channels, kernel_size, strides=(1, 1, 1), padding=(... class _Pooling (line 737) | class _Pooling(HybridBlock): method __init__ (line 739) | def __init__(self, pool_size, strides, padding, ceil_mode, global_pool, method _alias (line 756) | def _alias(self): method forward (line 759) | def forward(self, x): method __repr__ (line 762) | def __repr__(self): class MaxPool1D (line 770) | class MaxPool1D(_Pooling): method __init__ (line 805) | def __init__(self, pool_size=2, strides=None, padding=0, layout='NCW', class MaxPool2D (line 816) | class MaxPool2D(_Pooling): method __init__ (line 854) | def __init__(self, pool_size=(2, 2), strides=None, padding=0, layout='... class MaxPool3D (line 865) | class MaxPool3D(_Pooling): method __init__ (line 905) | def __init__(self, pool_size=(2, 2, 2), strides=None, padding=0, class AvgPool1D (line 916) | class AvgPool1D(_Pooling): method __init__ (line 952) | def __init__(self, pool_size=2, strides=None, padding=0, layout='NCW', class AvgPool2D (line 964) | class AvgPool2D(_Pooling): method __init__ (line 1003) | def __init__(self, pool_size=(2, 2), strides=None, padding=0, class AvgPool3D (line 1015) | class AvgPool3D(_Pooling): method __init__ (line 1056) | def __init__(self, pool_size=(2, 2, 2), strides=None, padding=0, class GlobalMaxPool1D (line 1068) | class GlobalMaxPool1D(_Pooling): method __init__ (line 1088) | def __init__(self, layout='NCW', **kwargs): class GlobalMaxPool2D (line 1095) | class GlobalMaxPool2D(_Pooling): method __init__ (line 1116) | def __init__(self, layout='NCHW', **kwargs): class GlobalMaxPool3D (line 1123) | class GlobalMaxPool3D(_Pooling): method __init__ (line 1145) | def __init__(self, layout='NCDHW', **kwargs): class GlobalAvgPool1D (line 1152) | class GlobalAvgPool1D(_Pooling): method __init__ (line 1170) | def __init__(self, layout='NCW', **kwargs): class GlobalAvgPool2D (line 1177) | class GlobalAvgPool2D(_Pooling): method __init__ (line 1197) | def __init__(self, layout='NCHW', **kwargs): class GlobalAvgPool3D (line 1204) | class GlobalAvgPool3D(_Pooling): method __init__ (line 1225) | def __init__(self, layout='NCDHW', **kwargs): class ReflectionPad2D (line 1233) | class ReflectionPad2D(HybridBlock): method __init__ (line 1261) | def __init__(self, padding=0, **kwargs): method forward (line 1268) | def forward(self, x): class DeformableConvolution (line 1277) | class DeformableConvolution(HybridBlock): method __init__ (line 1350) | def __init__(self, channels, kernel_size=(1, 1), strides=(1, 1), paddi... method forward (line 1418) | def forward(self, x): method pre_infer_offset_weight (line 1441) | def pre_infer_offset_weight(self): method pre_infer_weight (line 1453) | def pre_infer_weight(self): method infer_shape (line 1464) | def infer_shape(self, x): method _alias (line 1475) | def _alias(self): method __repr__ (line 1478) | def __repr__(self): class ModulatedDeformableConvolution (line 1501) | class ModulatedDeformableConvolution(HybridBlock): method __init__ (line 1572) | def __init__(self, channels, kernel_size=(1, 1), strides=(1, 1), paddi... method forward (line 1641) | def forward(self, x): method pre_infer_offset_weight (line 1668) | def pre_infer_offset_weight(self): method pre_infer_weight (line 1680) | def pre_infer_weight(self): method infer_shape (line 1691) | def infer_shape(self, x): method _alias (line 1702) | def _alias(self): class PixelShuffle1D (line 1707) | class PixelShuffle1D(HybridBlock): method __init__ (line 1738) | def __init__(self, factor): method forward (line 1742) | def forward(self, x): method __repr__ (line 1750) | def __repr__(self): class PixelShuffle2D (line 1755) | class PixelShuffle2D(HybridBlock): method __init__ (line 1795) | def __init__(self, factor): method forward (line 1803) | def forward(self, x): method __repr__ (line 1813) | def __repr__(self): class PixelShuffle3D (line 1818) | class PixelShuffle3D(HybridBlock): method __init__ (line 1858) | def __init__(self, factor): method forward (line 1866) | def forward(self, x): method __repr__ (line 1882) | def __repr__(self): FILE: python/mxnet/gluon/parameter.py class DeferredInitializationError (line 43) | class DeferredInitializationError(MXNetError): class Parameter (line 47) | class Parameter(object): method __init__ (line 106) | def __init__(self, name='weight', grad_req='write', shape=None, dtype=... method __repr__ (line 139) | def __repr__(self): method grad_req (line 144) | def grad_req(self): method name (line 148) | def name(self): method grad_req (line 152) | def grad_req(self, req): method dtype (line 167) | def dtype(self): method dtype (line 175) | def dtype(self, dtype): method shape (line 179) | def shape(self): method shape (line 196) | def shape(self, new_shape): method _set_trainer (line 208) | def _set_trainer(self, trainer): method _check_and_get (line 220) | def _check_and_get(self, arr_list, device): method _get_row_sparse (line 252) | def _get_row_sparse(self, arr_list, device, row_id): method _load_init (line 268) | def _load_init(self, data, device, cast_dtype=False, dtype_source='cur... method _finish_deferred_init (line 325) | def _finish_deferred_init(self): method _init_impl (line 355) | def _init_impl(self, data, device_list): method _init_grad (line 368) | def _init_grad(self): method _reduce (line 387) | def _reduce(self): method initialize (line 411) | def initialize(self, init=None, device=None, default_init=initializer.... method reset_device (line 480) | def reset_device(self, device): method reset_ctx (line 504) | def reset_ctx(self, ctx): method set_data (line 510) | def set_data(self, data): method row_sparse_data (line 529) | def row_sparse_data(self, row_id): method list_row_sparse_data (line 548) | def list_row_sparse_data(self, row_id): method data (line 569) | def data(self, device=None): method list_data (line 590) | def list_data(self): method grad (line 605) | def grad(self, device=None): method list_grad (line 619) | def list_grad(self): method list_ctx (line 628) | def list_ctx(self): method list_device (line 634) | def list_device(self): method zero_grad (line 642) | def zero_grad(self): method var (line 650) | def var(self): method cast (line 663) | def cast(self, dtype): method _check_and_setattr (line 682) | def _check_and_setattr(self, **kwargs): class Constant (line 714) | class Constant(Parameter): method __init__ (line 736) | def __init__(self, value): method __repr__ (line 752) | def __repr__(self): method grad_req (line 757) | def grad_req(self): method grad_req (line 761) | def grad_req(self, req): FILE: python/mxnet/gluon/probability/block/stochastic_block.py class StochasticBlock (line 28) | class StochasticBlock(HybridBlock): method __init__ (line 35) | def __init__(self, **kwargs): method add_loss (line 42) | def add_loss(self, loss): method collectLoss (line 46) | def collectLoss(func): method __call__ (line 72) | def __call__(self, *args, **kwargs): method losses (line 83) | def losses(self): class StochasticSequential (line 87) | class StochasticSequential(StochasticBlock): method __init__ (line 91) | def __init__(self, **kwargs): method add (line 95) | def add(self, *blocks): method forward (line 102) | def forward(self, x, *args): method __repr__ (line 117) | def __repr__(self): method __getitem__ (line 124) | def __getitem__(self, key): method __len__ (line 133) | def __len__(self): FILE: python/mxnet/gluon/probability/distributions/bernoulli.py class Bernoulli (line 29) | class Bernoulli(ExponentialFamily): method __init__ (line 45) | def __init__(self, prob=None, logit=None, validate_args=None): method prob (line 60) | def prob(self): method logit (line 72) | def logit(self): method mean (line 84) | def mean(self): method variance (line 88) | def variance(self): method broadcast_to (line 91) | def broadcast_to(self, batch_shape): method log_prob (line 104) | def log_prob(self, value): method sample (line 116) | def sample(self, size=None): method sample_n (line 119) | def sample_n(self, size=None): method _natural_params (line 123) | def _natural_params(self): method _log_normalizer (line 126) | def _log_normalizer(self, x): method entropy (line 130) | def entropy(self): FILE: python/mxnet/gluon/probability/distributions/beta.py class Beta (line 29) | class Beta(ExponentialFamily): method __init__ (line 46) | def __init__(self, alpha, beta, validate_args=None): method sample (line 52) | def sample(self, size=None): method sample_n (line 58) | def sample_n(self, size=None): method mean (line 62) | def mean(self): method variance (line 68) | def variance(self): method log_prob (line 74) | def log_prob(self, value): method entropy (line 85) | def entropy(self): FILE: python/mxnet/gluon/probability/distributions/binomial.py class Binomial (line 30) | class Binomial(Distribution): method __init__ (line 48) | def __init__(self, n=1, prob=None, logit=None, validate_args=None): method prob (line 66) | def prob(self): method logit (line 78) | def logit(self): method mean (line 90) | def mean(self): method variance (line 94) | def variance(self): method broadcast_to (line 98) | def broadcast_to(self, batch_shape): method log_prob (line 110) | def log_prob(self, value): method sample (line 121) | def sample(self, size=None): method sample_n (line 130) | def sample_n(self, size=None): FILE: python/mxnet/gluon/probability/distributions/categorical.py class Categorical (line 29) | class Categorical(Distribution): method __init__ (line 47) | def __init__(self, num_events, prob=None, logit=None, validate_args=No... method prob (line 68) | def prob(self): method logit (line 80) | def logit(self): method support (line 92) | def support(self): method log_prob (line 95) | def log_prob(self, value): method sample (line 115) | def sample(self, size=None): method sample_n (line 141) | def sample_n(self, size=None): method broadcast_to (line 146) | def broadcast_to(self, batch_shape): method enumerate_support (line 156) | def enumerate_support(self): FILE: python/mxnet/gluon/probability/distributions/cauchy.py class Cauchy (line 32) | class Cauchy(Distribution): method __init__ (line 48) | def __init__(self, loc=0.0, scale=1.0, validate_args=None): method mean (line 55) | def mean(self): method variance (line 59) | def variance(self): method sample (line 62) | def sample(self, size=None): method sample_n (line 72) | def sample_n(self, size=None): method log_prob (line 75) | def log_prob(self, value): method cdf (line 81) | def cdf(self, value): method icdf (line 86) | def icdf(self, value): method entropy (line 89) | def entropy(self): FILE: python/mxnet/gluon/probability/distributions/chi2.py class Chi2 (line 27) | class Chi2(Gamma): method __init__ (line 40) | def __init__(self, df, validate_args=None): method df (line 44) | def df(self): FILE: python/mxnet/gluon/probability/distributions/constraint.py class Constraint (line 34) | class Constraint(object): method check (line 41) | def check(self, value): class _Dependent (line 54) | class _Dependent(Constraint): method check (line 59) | def check(self, value): function is_dependent (line 63) | def is_dependent(constraint): class _DependentProperty (line 67) | class _DependentProperty(property, _Dependent): class Real (line 83) | class Real(Constraint): method check (line 88) | def check(self, value): class Boolean (line 97) | class Boolean(Constraint): method check (line 102) | def check(self, value): class Interval (line 110) | class Interval(Constraint): method __init__ (line 115) | def __init__(self, lower_bound, upper_bound): method check (line 120) | def check(self, value): class OpenInterval (line 128) | class OpenInterval(Constraint): method __init__ (line 133) | def __init__(self, lower_bound, upper_bound): method check (line 138) | def check(self, value): class HalfOpenInterval (line 146) | class HalfOpenInterval(Constraint): method __init__ (line 151) | def __init__(self, lower_bound, upper_bound): method check (line 156) | def check(self, value): class IntegerInterval (line 164) | class IntegerInterval(Constraint): method __init__ (line 169) | def __init__(self, lower_bound, upper_bound): method check (line 174) | def check(self, value): class IntegerOpenInterval (line 184) | class IntegerOpenInterval(Constraint): method __init__ (line 189) | def __init__(self, lower_bound, upper_bound): method check (line 194) | def check(self, value): class IntegerHalfOpenInterval (line 204) | class IntegerHalfOpenInterval(Constraint): method __init__ (line 209) | def __init__(self, lower_bound, upper_bound): method check (line 214) | def check(self, value): class GreaterThan (line 224) | class GreaterThan(Constraint): method __init__ (line 229) | def __init__(self, lower_bound): method check (line 233) | def check(self, value): class UnitInterval (line 241) | class UnitInterval(Interval): method __init__ (line 246) | def __init__(self): class GreaterThanEq (line 250) | class GreaterThanEq(Constraint): method __init__ (line 255) | def __init__(self, lower_bound): method check (line 259) | def check(self, value): class LessThan (line 267) | class LessThan(Constraint): method __init__ (line 272) | def __init__(self, upper_bound): method check (line 276) | def check(self, value): class LessThanEq (line 284) | class LessThanEq(Constraint): method __init__ (line 289) | def __init__(self, upper_bound): method check (line 293) | def check(self, value): class IntegerGreaterThan (line 301) | class IntegerGreaterThan(Constraint): method __init__ (line 306) | def __init__(self, lower_bound): method check (line 310) | def check(self, value): class IntegerGreaterThanEq (line 319) | class IntegerGreaterThanEq(Constraint): method __init__ (line 324) | def __init__(self, lower_bound): method check (line 328) | def check(self, value): class IntegerLessThan (line 338) | class IntegerLessThan(Constraint): method __init__ (line 343) | def __init__(self, upper_bound): method check (line 347) | def check(self, value): class IntegerLessThanEq (line 356) | class IntegerLessThanEq(Constraint): method __init__ (line 361) | def __init__(self, upper_bound): method check (line 365) | def check(self, value): class Positive (line 375) | class Positive(GreaterThan): method __init__ (line 380) | def __init__(self): class NonNegative (line 384) | class NonNegative(GreaterThanEq): method __init__ (line 389) | def __init__(self): class PositiveInteger (line 393) | class PositiveInteger(IntegerGreaterThan): method __init__ (line 398) | def __init__(self): class NonNegativeInteger (line 402) | class NonNegativeInteger(IntegerGreaterThanEq): method __init__ (line 407) | def __init__(self): class Simplex (line 411) | class Simplex(Constraint): method check (line 417) | def check(self, value): class LowerTriangular (line 426) | class LowerTriangular(Constraint): method check (line 431) | def check(self, value): class LowerCholesky (line 439) | class LowerCholesky(Constraint): method check (line 444) | def check(self, value): class PositiveDefinite (line 454) | class PositiveDefinite(Constraint): method check (line 459) | def check(self, value): class Cat (line 470) | class Cat(Constraint): method __init__ (line 477) | def __init__(self, constraint_seq, axis=0, lengths=None): method check (line 489) | def check(self, value): class Stack (line 501) | class Stack(Constraint): method __init__ (line 510) | def __init__(self, constraint_seq, axis=0): method check (line 515) | def check(self, value): FILE: python/mxnet/gluon/probability/distributions/dirichlet.py class Dirichlet (line 29) | class Dirichlet(ExponentialFamily): method __init__ (line 43) | def __init__(self, alpha, validate_args=None): method sample (line 48) | def sample(self, size=None): method sample_n (line 61) | def sample_n(self, size=None): method log_prob (line 70) | def log_prob(self, value): method mean (line 79) | def mean(self): method variance (line 84) | def variance(self): method entropy (line 89) | def entropy(self): FILE: python/mxnet/gluon/probability/distributions/distribution.py class Distribution (line 28) | class Distribution(object): method set_default_validate_args (line 48) | def set_default_validate_args(value): method __init__ (line 53) | def __init__(self, event_dim=None, validate_args=None): method log_prob (line 66) | def log_prob(self, value): method pdf (line 72) | def pdf(self, value): method cdf (line 78) | def cdf(self, value): method icdf (line 84) | def icdf(self, value): method sample (line 90) | def sample(self, size=None): method sample_n (line 96) | def sample_n(self, size): method broadcast_to (line 102) | def broadcast_to(self, batch_shape): method enumerate_support (line 116) | def enumerate_support(self): method arg_constraints (line 124) | def arg_constraints(self): method mean (line 135) | def mean(self): method variance (line 142) | def variance(self): method stddev (line 149) | def stddev(self): method support (line 156) | def support(self): method entropy (line 163) | def entropy(self): method perplexity (line 169) | def perplexity(self): method __repr__ (line 175) | def __repr__(self): method _validate_samples (line 198) | def _validate_samples(self, value): FILE: python/mxnet/gluon/probability/distributions/divergence.py function empirical_kl (line 48) | def empirical_kl(p, q, n_samples=1): function register_kl (line 65) | def register_kl(typeP, typeQ): function kl_divergence (line 89) | def kl_divergence(p, q): function _dispatch_kl (line 111) | def _dispatch_kl(type_p, type_q): class _KL_storage (line 135) | class _KL_storage(): method _kl_Normal_Normal (line 142) | def _kl_Normal_Normal(p, q): function _kl_bernoulli_bernoulli (line 149) | def _kl_bernoulli_bernoulli(p, q): function _kl_categorical_categorical (line 158) | def _kl_categorical_categorical(p, q): function _kl_onehotcategorical_onehotcategorical (line 163) | def _kl_onehotcategorical_onehotcategorical(p, q): function _kl_uniform_uniform (line 168) | def _kl_uniform_uniform(p, q): function _kl_cauchy_cauchy (line 175) | def _kl_cauchy_cauchy(p, q): function _kl_laplace_laplace (line 182) | def _kl_laplace_laplace(p, q): function _kl_poisson_poisson (line 192) | def _kl_poisson_poisson(p, q): function _kl_geometric_geometric (line 199) | def _kl_geometric_geometric(p, q): function _kl_exponential_exponential (line 204) | def _kl_exponential_exponential(p, q): function _kl_pareto_pareto (line 211) | def _kl_pareto_pareto(p, q): function _kl_gumbel_gumbel (line 223) | def _kl_gumbel_gumbel(p, q): function _kl_gamma_gamma (line 236) | def _kl_gamma_gamma(p, q): function _kl_beta_beta (line 248) | def _kl_beta_beta(p, q): function _kl_dirichlet_dirichlet (line 264) | def _kl_dirichlet_dirichlet(p, q): function _kl_halfNormal_halfNormal (line 277) | def _kl_halfNormal_halfNormal(p, q): function _kl_binomial_binomial (line 284) | def _kl_binomial_binomial(p, q): function _kl_mvn_mvn (line 292) | def _kl_mvn_mvn(p, q): function _kl_uniform_normal (line 317) | def _kl_uniform_normal(p, q): function _kl_uniform_gumbel (line 326) | def _kl_uniform_gumbel(p, q): function _kl_exponential_gumbel (line 336) | def _kl_exponential_gumbel(p, q): function _kl_exponential_normal (line 346) | def _kl_exponential_normal(p, q): function _kl_exponential_gamma (line 357) | def _kl_exponential_gamma(p, q): FILE: python/mxnet/gluon/probability/distributions/exp_family.py class ExponentialFamily (line 26) | class ExponentialFamily(Distribution): method _natural_params (line 42) | def _natural_params(self): method _log_normalizer (line 48) | def _log_normalizer(self, *natural_params): method _mean_carrier_measure (line 54) | def _mean_carrier_measure(self, x): method entropy (line 61) | def entropy(self): FILE: python/mxnet/gluon/probability/distributions/exponential.py class Exponential (line 29) | class Exponential(ExponentialFamily): method __init__ (line 43) | def __init__(self, scale=1.0, validate_args=None): method rate (line 49) | def rate(self): method mean (line 53) | def mean(self): method variance (line 57) | def variance(self): method stddev (line 61) | def stddev(self): method sample (line 64) | def sample(self, size=None): method sample_n (line 67) | def sample_n(self, size=None): method broadcast_to (line 71) | def broadcast_to(self, batch_shape): method log_prob (line 79) | def log_prob(self, value): method cdf (line 84) | def cdf(self, value): method icdf (line 89) | def icdf(self, value): method entropy (line 92) | def entropy(self): method _natural_params (line 96) | def _natural_params(self): method _log_normalizer (line 99) | def _log_normalizer(self, x): FILE: python/mxnet/gluon/probability/distributions/fishersnedecor.py class FisherSnedecor (line 32) | class FisherSnedecor(Distribution): method __init__ (line 47) | def __init__(self, df1, df2, validate_args=None): method broadcast_to (line 55) | def broadcast_to(self, batch_shape): method mean (line 66) | def mean(self): method variance (line 72) | def variance(self): method sample (line 80) | def sample(self, size=None): method sample_n (line 85) | def sample_n(self, size=None): method log_prob (line 90) | def log_prob(self, value): FILE: python/mxnet/gluon/probability/distributions/gamma.py class Gamma (line 30) | class Gamma(ExponentialFamily): method __init__ (line 48) | def __init__(self, shape, scale=1.0, validate_args=None): method log_prob (line 54) | def log_prob(self, value): method broadcast_to (line 65) | def broadcast_to(self, batch_shape): method sample (line 74) | def sample(self, size=None): method sample_n (line 77) | def sample_n(self, size=None): method mean (line 81) | def mean(self): method variance (line 85) | def variance(self): method entropy (line 88) | def entropy(self): method _natural_params (line 95) | def _natural_params(self): FILE: python/mxnet/gluon/probability/distributions/geometric.py class Geometric (line 30) | class Geometric(Distribution): method __init__ (line 46) | def __init__(self, prob=None, logit=None, validate_args=None): method prob (line 60) | def prob(self): method logit (line 72) | def logit(self): method mean (line 84) | def mean(self): method variance (line 88) | def variance(self): method broadcast_to (line 91) | def broadcast_to(self, batch_shape): method log_prob (line 102) | def log_prob(self, value): method sample (line 108) | def sample(self, size=None): method sample_n (line 119) | def sample_n(self, size=None): method entropy (line 122) | def entropy(self): FILE: python/mxnet/gluon/probability/distributions/gumbel.py class Gumbel (line 31) | class Gumbel(Distribution): method __init__ (line 48) | def __init__(self, loc, scale=1, validate_args=None): method log_prob (line 54) | def log_prob(self, value): method broadcast_to (line 61) | def broadcast_to(self, batch_shape): method cdf (line 72) | def cdf(self, value): method icdf (line 79) | def icdf(self, value): method sample (line 83) | def sample(self, size=None): method sample_n (line 86) | def sample_n(self, size=None): method mean (line 90) | def mean(self): method stddev (line 94) | def stddev(self): method variance (line 98) | def variance(self): method entropy (line 101) | def entropy(self): FILE: python/mxnet/gluon/probability/distributions/half_cauchy.py class HalfCauchy (line 32) | class HalfCauchy(TransformedDistribution): method __init__ (line 48) | def __init__(self, scale=1.0, validate_args=None): method log_prob (line 54) | def log_prob(self, value): method cdf (line 61) | def cdf(self, value): method icdf (line 66) | def icdf(self, value): method entropy (line 69) | def entropy(self): method mean (line 73) | def mean(self): method variance (line 77) | def variance(self): FILE: python/mxnet/gluon/probability/distributions/half_normal.py class HalfNormal (line 32) | class HalfNormal(TransformedDistribution): method __init__ (line 48) | def __init__(self, scale=1.0, validate_args=None): method log_prob (line 54) | def log_prob(self, value): method cdf (line 61) | def cdf(self, value): method icdf (line 66) | def icdf(self, value): method loc (line 70) | def loc(self): method mean (line 74) | def mean(self): method variance (line 78) | def variance(self): FILE: python/mxnet/gluon/probability/distributions/independent.py class Independent (line 28) | class Independent(Distribution): method __init__ (line 37) | def __init__(self, base_distribution, reinterpreted_batch_ndims, valid... method broadcast_to (line 44) | def broadcast_to(self, batch_shape): method has_enumerate_support (line 57) | def has_enumerate_support(self): method support (line 63) | def support(self): method mean (line 67) | def mean(self): method variance (line 71) | def variance(self): method sample (line 74) | def sample(self, size=None): method sample_n (line 77) | def sample_n(self, size): method log_prob (line 80) | def log_prob(self, value): method entropy (line 84) | def entropy(self): method enumerate_support (line 88) | def enumerate_support(self): FILE: python/mxnet/gluon/probability/distributions/laplace.py class Laplace (line 29) | class Laplace(Distribution): method __init__ (line 45) | def __init__(self, loc=0.0, scale=1.0, validate_args=None): method log_prob (line 51) | def log_prob(self, value): method sample (line 68) | def sample(self, size=None): method sample_n (line 85) | def sample_n(self, size=None): method broadcast_to (line 101) | def broadcast_to(self, batch_shape): method cdf (line 110) | def cdf(self, value): method icdf (line 116) | def icdf(self, value): method mean (line 121) | def mean(self): method stddev (line 125) | def stddev(self): method variance (line 129) | def variance(self): method entropy (line 132) | def entropy(self): FILE: python/mxnet/gluon/probability/distributions/multinomial.py class Multinomial (line 30) | class Multinomial(Distribution): method __init__ (line 48) | def __init__(self, num_events, method mean (line 67) | def mean(self): method variance (line 71) | def variance(self): method prob (line 75) | def prob(self): method logit (line 80) | def logit(self): method support (line 85) | def support(self): method sample (line 88) | def sample(self, size=None): method sample_n (line 95) | def sample_n(self, size=None): method log_prob (line 101) | def log_prob(self, value): method broadcast_to (line 110) | def broadcast_to(self, batch_shape): FILE: python/mxnet/gluon/probability/distributions/multivariate_normal.py class MultivariateNormal (line 30) | class MultivariateNormal(Distribution): method __init__ (line 53) | def __init__(self, loc, cov=None, precision=None, scale_tril=None, val... method _precision_to_scale_tril (line 67) | def _precision_to_scale_tril(self, P): method scale_tril (line 79) | def scale_tril(self): method cov (line 86) | def cov(self): method precision (line 93) | def precision(self): method mean (line 101) | def mean(self): method variance (line 105) | def variance(self): method sample (line 108) | def sample(self, size=None): method sample_n (line 121) | def sample_n(self, size=None): method log_prob (line 134) | def log_prob(self, value): method entropy (line 154) | def entropy(self): FILE: python/mxnet/gluon/probability/distributions/negative_binomial.py class NegativeBinomial (line 32) | class NegativeBinomial(Distribution): method __init__ (line 51) | def __init__(self, n, prob=None, logit=None, validate_args=None): method prob (line 66) | def prob(self): method logit (line 78) | def logit(self): method mean (line 90) | def mean(self): method variance (line 94) | def variance(self): method broadcast_to (line 98) | def broadcast_to(self, batch_shape): method log_prob (line 110) | def log_prob(self, value): method sample (line 121) | def sample(self, size=None): method sample_n (line 127) | def sample_n(self, size=None): FILE: python/mxnet/gluon/probability/distributions/normal.py class Normal (line 30) | class Normal(ExponentialFamily): method __init__ (line 46) | def __init__(self, loc=0.0, scale=1.0, validate_args=None): method log_prob (line 52) | def log_prob(self, value): method sample (line 73) | def sample(self, size=None): method sample_n (line 90) | def sample_n(self, size=None): method broadcast_to (line 106) | def broadcast_to(self, batch_shape): method cdf (line 115) | def cdf(self, value): method icdf (line 124) | def icdf(self, value): method mean (line 129) | def mean(self): method stddev (line 133) | def stddev(self): method variance (line 137) | def variance(self): method entropy (line 140) | def entropy(self): method _natural_params (line 144) | def _natural_params(self): method _log_normalizer (line 156) | def _log_normalizer(self, x, y): FILE: python/mxnet/gluon/probability/distributions/one_hot_categorical.py class OneHotCategorical (line 30) | class OneHotCategorical(Distribution): method __init__ (line 46) | def __init__(self, num_events, prob=None, logit=None, validate_args=No... method prob (line 59) | def prob(self): method logit (line 63) | def logit(self): method mean (line 67) | def mean(self): method variance (line 71) | def variance(self): method sample (line 75) | def sample(self, size=None): method sample_n (line 79) | def sample_n(self, size=None): method log_prob (line 83) | def log_prob(self, value): method broadcast_to (line 89) | def broadcast_to(self, batch_shape): method enumerate_support (line 98) | def enumerate_support(self): FILE: python/mxnet/gluon/probability/distributions/pareto.py class Pareto (line 31) | class Pareto(TransformedDistribution): method __init__ (line 47) | def __init__(self, alpha, scale=1.0, validate_args=None): method sample (line 54) | def sample(self, size=None): method sample_n (line 57) | def sample_n(self, size=None): method support (line 61) | def support(self): method mean (line 65) | def mean(self): method variance (line 70) | def variance(self): method entropy (line 74) | def entropy(self): FILE: python/mxnet/gluon/probability/distributions/poisson.py class Poisson (line 30) | class Poisson(ExponentialFamily): method __init__ (line 43) | def __init__(self, rate=1.0, validate_args=None): method mean (line 49) | def mean(self): method variance (line 53) | def variance(self): method broadcast_to (line 56) | def broadcast_to(self, batch_shape): method sample (line 64) | def sample(self, size=None): method sample_n (line 77) | def sample_n(self, size=None): method log_prob (line 87) | def log_prob(self, value): method _natural_params (line 95) | def _natural_params(self): method _log_normalizer (line 98) | def _log_normalizer(self, x): FILE: python/mxnet/gluon/probability/distributions/relaxed_bernoulli.py class _LogitRelaxedBernoulli (line 31) | class _LogitRelaxedBernoulli(Distribution): method __init__ (line 50) | def __init__(self, T, prob=None, logit=None, validate_args=None): method prob (line 65) | def prob(self): method logit (line 70) | def logit(self): method sample (line 74) | def sample(self, size=None): method log_prob (line 78) | def log_prob(self, value): class RelaxedBernoulli (line 84) | class RelaxedBernoulli(TransformedDistribution): method __init__ (line 103) | def __init__(self, T, prob=None, logit=None, validate_args=None): method T (line 108) | def T(self): method prob (line 112) | def prob(self): method logit (line 116) | def logit(self): method broadcast_to (line 119) | def broadcast_to(self, batch_shape): FILE: python/mxnet/gluon/probability/distributions/relaxed_one_hot_categorical.py class _LogRelaxedOneHotCategorical (line 32) | class _LogRelaxedOneHotCategorical(Distribution): method __init__ (line 53) | def __init__(self, T, num_events, prob=None, logit=None, validate_args... method prob (line 75) | def prob(self): method logit (line 87) | def logit(self): method log_prob (line 98) | def log_prob(self, value): method sample (line 118) | def sample(self, size=None): class RelaxedOneHotCategorical (line 131) | class RelaxedOneHotCategorical(TransformedDistribution): method __init__ (line 151) | def __init__(self, T, num_events, prob=None, logit=None, validate_args... method T (line 158) | def T(self): method prob (line 162) | def prob(self): method logit (line 166) | def logit(self): FILE: python/mxnet/gluon/probability/distributions/studentT.py class StudentT (line 31) | class StudentT(Distribution): method __init__ (line 48) | def __init__(self, df, loc=0.0, scale=1.0, validate_args=None): method broadcast_to (line 56) | def broadcast_to(self, batch_shape): method mean (line 68) | def mean(self): method variance (line 74) | def variance(self): method sample (line 81) | def sample(self, size=None): method sample_n (line 87) | def sample_n(self, size=None): method log_prob (line 90) | def log_prob(self, value): method entropy (line 102) | def entropy(self): FILE: python/mxnet/gluon/probability/distributions/transformed_distribution.py class TransformedDistribution (line 28) | class TransformedDistribution(Distribution): method __init__ (line 41) | def __init__(self, base_dist, transforms, validate_args=None): method sample (line 51) | def sample(self, size=None): method sample_n (line 57) | def sample_n(self, size=None): method log_prob (line 63) | def log_prob(self, value): method cdf (line 83) | def cdf(self, value): method icdf (line 94) | def icdf(self, value): FILE: python/mxnet/gluon/probability/distributions/uniform.py class Uniform (line 29) | class Uniform(Distribution): method __init__ (line 46) | def __init__(self, low=0.0, high=1.0, validate_args=None): method log_prob (line 52) | def log_prob(self, value): method sample (line 63) | def sample(self, size=None): method sample_n (line 66) | def sample_n(self, size=None): method support (line 71) | def support(self): method broadcast_to (line 74) | def broadcast_to(self, batch_shape): method cdf (line 83) | def cdf(self, value): method icdf (line 89) | def icdf(self, value): method entropy (line 92) | def entropy(self): FILE: python/mxnet/gluon/probability/distributions/utils.py function constraint_check (line 34) | def constraint_check(): function digamma (line 46) | def digamma(): function gammaln (line 61) | def gammaln(): function erf (line 76) | def erf(): function erfinv (line 89) | def erfinv(): function sample_n_shape_converter (line 102) | def sample_n_shape_converter(size): function sum_right_most (line 116) | def sum_right_most(x, ndim): function _clip_prob (line 136) | def _clip_prob(prob): function _clip_float_eps (line 141) | def _clip_float_eps(value): function prob2logit (line 146) | def prob2logit(prob, binary=True): function logit2prob (line 159) | def logit2prob(logit, binary=True): class _CachedProperty (line 170) | class _CachedProperty(object): method __init__ (line 173) | def __init__(self, func): method __get__ (line 177) | def __get__(self, instance, cls=None): FILE: python/mxnet/gluon/probability/distributions/weibull.py class Weibull (line 33) | class Weibull(TransformedDistribution): method __init__ (line 49) | def __init__(self, concentration, scale=1.0, validate_args=None): method sample (line 56) | def sample(self, size=None): method sample_n (line 59) | def sample_n(self, size=None): method mean (line 64) | def mean(self): method variance (line 68) | def variance(self): method entropy (line 75) | def entropy(self): FILE: python/mxnet/gluon/probability/transformation/domain_map.py class domain_map (line 33) | class domain_map(): method __init__ (line 38) | def __init__(self): method register (line 43) | def register(self, constraint, factory=None): method __call__ (line 69) | def __call__(self, constraint): function _transform_to_positive (line 84) | def _transform_to_positive(constraint): function _transform_to_greater_than (line 95) | def _transform_to_greater_than(constraint): function _transform_to_less_than (line 102) | def _transform_to_less_than(constraint): function _transform_to_interval (line 111) | def _transform_to_interval(constraint): FILE: python/mxnet/gluon/probability/transformation/transformation.py class Transformation (line 32) | class Transformation(object): method __init__ (line 44) | def __init__(self): method sign (line 49) | def sign(self): method inv (line 56) | def inv(self): method __call__ (line 65) | def __call__(self, x): method _inv_call (line 68) | def _inv_call(self, y): method _forward_compute (line 71) | def _forward_compute(self, x): method _inverse_compute (line 74) | def _inverse_compute(self, x): method log_det_jacobian (line 77) | def log_det_jacobian(self, x, y): class _InverseTransformation (line 84) | class _InverseTransformation(Transformation): method __init__ (line 90) | def __init__(self, forward_transformation): method inv (line 95) | def inv(self): method sign (line 99) | def sign(self): method event_dim (line 103) | def event_dim(self): method __call__ (line 106) | def __call__(self, x): method log_det_jacobian (line 109) | def log_det_jacobian(self, x, y): class TransformBlock (line 113) | class TransformBlock(Transformation, HybridBlock): method __init__ (line 119) | def __init__(self, *args, **kwargs): class ComposeTransform (line 123) | class ComposeTransform(Transformation): method __init__ (line 127) | def __init__(self, parts): method _forward_compute (line 131) | def _forward_compute(self, x): method sign (line 139) | def sign(self): method event_dim (line 146) | def event_dim(self): method inv (line 150) | def inv(self): method log_det_jacobian (line 160) | def log_det_jacobian(self, x, y): class ExpTransform (line 177) | class ExpTransform(Transformation): method _forward_compute (line 184) | def _forward_compute(self, x): method _inverse_compute (line 187) | def _inverse_compute(self, y): method log_det_jacobian (line 190) | def log_det_jacobian(self, x, y): class AffineTransform (line 194) | class AffineTransform(Transformation): method __init__ (line 200) | def __init__(self, loc, scale, event_dim=0): method _forward_compute (line 206) | def _forward_compute(self, x): method _inverse_compute (line 209) | def _inverse_compute(self, y): method log_det_jacobian (line 212) | def log_det_jacobian(self, x, y): method sign (line 218) | def sign(self): class PowerTransform (line 222) | class PowerTransform(Transformation): method __init__ (line 229) | def __init__(self, exponent): method _forward_compute (line 233) | def _forward_compute(self, x): method _inverse_compute (line 236) | def _inverse_compute(self, y): method log_det_jacobian (line 239) | def log_det_jacobian(self, x, y): class SigmoidTransform (line 245) | class SigmoidTransform(Transformation): method _forward_compute (line 252) | def _forward_compute(self, x): method _inverse_compute (line 255) | def _inverse_compute(self, y): method log_det_jacobian (line 259) | def log_det_jacobian(self, x, y): class SoftmaxTransform (line 264) | class SoftmaxTransform(Transformation): method _forward_compute (line 267) | def _forward_compute(self, x): method _inverse_compute (line 270) | def _inverse_compute(self, y): class AbsTransform (line 274) | class AbsTransform(Transformation): method _forward_compute (line 275) | def _forward_compute(self, x): method _inverse_compute (line 278) | def _inverse_compute(self, y): FILE: python/mxnet/gluon/rnn/conv_rnn_cell.py function _get_conv_out_size (line 35) | def _get_conv_out_size(dimensions, kernels, paddings, dilations): class _BaseConvRNNCell (line 41) | class _BaseConvRNNCell(HybridRecurrentCell): method __init__ (line 43) | def __init__(self, input_shape, hidden_channels, method _decide_shapes (line 98) | def _decide_shapes(self): method __repr__ (line 130) | def __repr__(self): method _num_gates (line 145) | def _num_gates(self): method _conv_forward (line 148) | def _conv_forward(self, inputs, states): method state_info (line 170) | def state_info(self, batch_size=0): method forward (line 173) | def forward(self, inputs, states): method infer_shape (line 177) | def infer_shape(self, i, x, is_bidirect): class _ConvRNNCell (line 187) | class _ConvRNNCell(_BaseConvRNNCell): method __init__ (line 188) | def __init__(self, input_shape, hidden_channels, method state_info (line 206) | def state_info(self, batch_size=0): method _alias (line 209) | def _alias(self): method _gate_names (line 213) | def _gate_names(self): method forward (line 216) | def forward(self, inputs, states): class Conv1DRNNCell (line 222) | class Conv1DRNNCell(_ConvRNNCell): method __init__ (line 263) | def __init__(self, input_shape, hidden_channels, class Conv2DRNNCell (line 283) | class Conv2DRNNCell(_ConvRNNCell): method __init__ (line 324) | def __init__(self, input_shape, hidden_channels, class Conv3DRNNCell (line 344) | class Conv3DRNNCell(_ConvRNNCell): method __init__ (line 385) | def __init__(self, input_shape, hidden_channels, class _ConvLSTMCell (line 407) | class _ConvLSTMCell(_BaseConvRNNCell): method __init__ (line 408) | def __init__(self, input_shape, hidden_channels, method state_info (line 427) | def state_info(self, batch_size=0): method _alias (line 431) | def _alias(self): method _gate_names (line 435) | def _gate_names(self): method forward (line 438) | def forward(self, inputs, states): class Conv1DLSTMCell (line 452) | class Conv1DLSTMCell(_ConvLSTMCell): method __init__ (line 502) | def __init__(self, input_shape, hidden_channels, class Conv2DLSTMCell (line 523) | class Conv2DLSTMCell(_ConvLSTMCell): method __init__ (line 573) | def __init__(self, input_shape, hidden_channels, class Conv3DLSTMCell (line 594) | class Conv3DLSTMCell(_ConvLSTMCell): method __init__ (line 644) | def __init__(self, input_shape, hidden_channels, class _ConvGRUCell (line 666) | class _ConvGRUCell(_BaseConvRNNCell): method __init__ (line 667) | def __init__(self, input_shape, hidden_channels, method state_info (line 685) | def state_info(self, batch_size=0): method _alias (line 688) | def _alias(self): method _gate_names (line 692) | def _gate_names(self): method forward (line 695) | def forward(self, inputs, states): class Conv1DGRUCell (line 714) | class Conv1DGRUCell(_ConvGRUCell): method __init__ (line 759) | def __init__(self, input_shape, hidden_channels, class Conv2DGRUCell (line 780) | class Conv2DGRUCell(_ConvGRUCell): method __init__ (line 825) | def __init__(self, input_shape, hidden_channels, class Conv3DGRUCell (line 846) | class Conv3DGRUCell(_ConvGRUCell): method __init__ (line 891) | def __init__(self, input_shape, hidden_channels, FILE: python/mxnet/gluon/rnn/rnn_cell.py function _cells_state_info (line 39) | def _cells_state_info(cells, batch_size): function _cells_begin_state (line 42) | def _cells_begin_state(cells, **kwargs): function _get_begin_state (line 45) | def _get_begin_state(cell, begin_state, inputs, batch_size): function _format_sequence (line 52) | def _format_sequence(length, inputs, layout, merge, in_layout=None): function _mask_sequence_variable_length (line 82) | def _mask_sequence_variable_length(data, length, valid_length, time_axis... function _reverse_sequences (line 93) | def _reverse_sequences(sequences, unroll_step, valid_length=None): class RecurrentCell (line 110) | class RecurrentCell(Block): method __init__ (line 114) | def __init__(self): method reset (line 119) | def reset(self): method state_info (line 126) | def state_info(self, batch_size=0): method begin_state (line 130) | def begin_state(self, batch_size=0, func=np.zeros, **kwargs): method unroll (line 171) | def unroll(self, length, inputs, begin_state=None, layout='NTC', merge... method _get_activation (line 249) | def _get_activation(self, inputs, activation, **kwargs): method forward (line 263) | def forward(self, inputs, states): class HybridRecurrentCell (line 294) | class HybridRecurrentCell(RecurrentCell, HybridBlock): method __init__ (line 296) | def __init__(self): method forward (line 299) | def forward(self, x, *args, **kwargs): class RNNCell (line 304) | class RNNCell(HybridRecurrentCell): method __init__ (line 348) | def __init__(self, hidden_size, activation='tanh', method state_info (line 369) | def state_info(self, batch_size=0): method _alias (line 372) | def _alias(self): method __repr__ (line 375) | def __repr__(self): method forward (line 386) | def forward(self, inputs, states): method infer_shape (line 402) | def infer_shape(self, i, x, is_bidirect): class LSTMCell (line 413) | class LSTMCell(HybridRecurrentCell): method __init__ (line 469) | def __init__(self, hidden_size, method state_info (line 493) | def state_info(self, batch_size=0): method _alias (line 497) | def _alias(self): method __repr__ (line 500) | def __repr__(self): method forward (line 508) | def forward(self, inputs, states): method infer_shape (line 530) | def infer_shape(self, i, x, is_bidirect): class GRUCell (line 540) | class GRUCell(HybridRecurrentCell): method __init__ (line 595) | def __init__(self, hidden_size, method state_info (line 617) | def state_info(self, batch_size=0): method _alias (line 620) | def _alias(self): method __repr__ (line 623) | def __repr__(self): method forward (line 631) | def forward(self, inputs, states): method infer_shape (line 660) | def infer_shape(self, i, x, is_bidirect): class SequentialRNNCell (line 670) | class SequentialRNNCell(RecurrentCell): method __init__ (line 672) | def __init__(self): method __repr__ (line 676) | def __repr__(self): method add (line 682) | def add(self, cell): method state_info (line 693) | def state_info(self, batch_size=0): method begin_state (line 696) | def begin_state(self, **kwargs): method __call__ (line 702) | def __call__(self, inputs, states): method unroll (line 716) | def unroll(self, length, inputs, begin_state=None, layout='NTC', merge... method __getitem__ (line 739) | def __getitem__(self, i): method __len__ (line 742) | def __len__(self): method forward (line 745) | def forward(self, *args, **kwargs): method infer_shape (line 749) | def infer_shape(self, _, x, is_bidirect): class HybridSequentialRNNCell (line 755) | class HybridSequentialRNNCell(HybridRecurrentCell): method __init__ (line 757) | def __init__(self): method __repr__ (line 761) | def __repr__(self): method add (line 767) | def add(self, cell): method state_info (line 778) | def state_info(self, batch_size=0): method begin_state (line 781) | def begin_state(self, **kwargs): method __call__ (line 787) | def __call__(self, inputs, states): method unroll (line 800) | def unroll(self, length, inputs, begin_state=None, layout='NTC', merge... method __getitem__ (line 822) | def __getitem__(self, i): method __len__ (line 825) | def __len__(self): method forward (line 828) | def forward(self, inputs, states): method infer_shape (line 832) | def infer_shape(self, _, x, is_bidirect): class DropoutCell (line 838) | class DropoutCell(HybridRecurrentCell): method __init__ (line 858) | def __init__(self, rate, axes=()): method __repr__ (line 864) | def __repr__(self): method state_info (line 869) | def state_info(self, batch_size=0): method _alias (line 872) | def _alias(self): method forward (line 875) | def forward(self, inputs, states): method unroll (line 880) | def unroll(self, length, inputs, begin_state=None, layout='NTC', merge... class ModifierCell (line 893) | class ModifierCell(HybridRecurrentCell): method __init__ (line 902) | def __init__(self, base_cell): method params (line 910) | def params(self): method state_info (line 913) | def state_info(self, batch_size=0): method begin_state (line 916) | def begin_state(self, func=np.zeros, **kwargs): method forward (line 925) | def forward(self, inputs, states): method __repr__ (line 928) | def __repr__(self): class ZoneoutCell (line 935) | class ZoneoutCell(ModifierCell): method __init__ (line 937) | def __init__(self, base_cell, zoneout_outputs=0., zoneout_states=0.): method __repr__ (line 949) | def __repr__(self): method _alias (line 954) | def _alias(self): method reset (line 957) | def reset(self): method forward (line 961) | def forward(self, inputs, states): method infer_shape (line 980) | def infer_shape(self, i, x, is_bidirect): class ResidualCell (line 984) | class ResidualCell(ModifierCell): method __init__ (line 991) | def __init__(self, base_cell): method forward (line 995) | def forward(self, inputs, states): method unroll (line 1000) | def unroll(self, length, inputs, begin_state=None, layout='NTC', merge... method infer_shape (line 1024) | def infer_shape(self, i, x, is_bidirect): class BidirectionalCell (line 1029) | class BidirectionalCell(HybridRecurrentCell): method __init__ (line 1039) | def __init__(self, l_cell, r_cell): method __call__ (line 1044) | def __call__(self, inputs, states): method __repr__ (line 1047) | def __repr__(self): method state_info (line 1053) | def state_info(self, batch_size=0): method begin_state (line 1056) | def begin_state(self, **kwargs): method unroll (line 1062) | def unroll(self, length, inputs, begin_state=None, layout='NTC', merge... method infer_shape (line 1104) | def infer_shape(self, i, x, is_bidirect): class VariationalDropoutCell (line 1110) | class VariationalDropoutCell(ModifierCell): method __init__ (line 1134) | def __init__(self, base_cell, drop_inputs=0., drop_states=0., drop_out... method _alias (line 1150) | def _alias(self): method reset (line 1153) | def reset(self): method _initialize_input_masks (line 1159) | def _initialize_input_masks(self, inputs, states): method _initialize_output_mask (line 1168) | def _initialize_output_mask(self, output): method forward (line 1174) | def forward(self, inputs, states): method __repr__ (line 1195) | def __repr__(self): method unroll (line 1200) | def unroll(self, length, inputs, begin_state=None, layout='NTC', merge... method infer_shape (line 1280) | def infer_shape(self, i, x, is_bidirect): class LSTMPCell (line 1284) | class LSTMPCell(HybridRecurrentCell): method __init__ (line 1338) | def __init__(self, hidden_size, projection_size, method state_info (line 1364) | def state_info(self, batch_size=0): method _alias (line 1368) | def _alias(self): method __repr__ (line 1371) | def __repr__(self): method forward (line 1382) | def forward(self, inputs, states): method infer_shape (line 1404) | def infer_shape(self, i, x, is_bidirect): function dynamic_unroll (line 1414) | def dynamic_unroll(cell, inputs, begin_state, drop_inputs=0, drop_output... FILE: python/mxnet/gluon/rnn/rnn_layer.py class _RNNLayer (line 33) | class _RNNLayer(HybridBlock): method __init__ (line 35) | def __init__(self, hidden_size, num_layers, layout, method __repr__ (line 74) | def __repr__(self): method state_info (line 88) | def state_info(self, batch_size=0): method cast (line 91) | def cast(self, dtype): method begin_state (line 95) | def begin_state(self, batch_size=0, func=np.zeros, **kwargs): method __call__ (line 133) | def __call__(self, inputs, states=None, sequence_length=None, **kwargs): method forward (line 146) | def forward(self, inputs, states, sequence_length=None): method infer_shape (line 158) | def infer_shape(self, inputs, *args): method _forward_kernel (line 176) | def _forward_kernel(self, inputs, states, sequence_length): class RNN (line 212) | class RNN(_RNNLayer): method __init__ (line 288) | def __init__(self, hidden_size, num_layers=1, activation='relu', method state_info (line 300) | def state_info(self, batch_size=0): class LSTM (line 305) | class LSTM(_RNNLayer): method __init__ (line 404) | def __init__(self, hidden_size, num_layers=1, layout='TNC', method state_info (line 419) | def state_info(self, batch_size=0): class GRU (line 432) | class GRU(_RNNLayer): method __init__ (line 513) | def __init__(self, hidden_size, num_layers=1, layout='TNC', method state_info (line 525) | def state_info(self, batch_size=0): FILE: python/mxnet/gluon/trainer.py class Trainer (line 32) | class Trainer(object): method __init__ (line 79) | def __init__(self, params, optimizer, optimizer_params=None, kvstore='... method _check_contexts (line 129) | def _check_contexts(self): method _check_devices (line 135) | def _check_devices(self): method _init_optimizer (line 146) | def _init_optimizer(self, optimizer, optimizer_params): method _init_params (line 162) | def _init_params(self): method _reset_kvstore (line 185) | def _reset_kvstore(self): method _init_kvstore (line 195) | def _init_kvstore(self): method learning_rate (line 287) | def learning_rate(self): method optimizer (line 295) | def optimizer(self): method set_learning_rate (line 301) | def set_learning_rate(self, lr): method _row_sparse_pull (line 315) | def _row_sparse_pull(self, parameter, out, row_id, full_idx=False): method _check_and_rescale_grad (line 331) | def _check_and_rescale_grad(self, scale): method step (line 341) | def step(self, batch_size, ignore_stale_grad=False): method allreduce_grads (line 370) | def allreduce_grads(self): method _allreduce_grads (line 392) | def _allreduce_grads(self): method update (line 418) | def update(self, batch_size, ignore_stale_grad=False): method _update (line 451) | def _update(self, ignore_stale_grad=False): method save_states (line 488) | def save_states(self, fname): method load_states (line 517) | def load_states(self, fname): FILE: python/mxnet/gluon/utils.py function split_data (line 41) | def split_data(data, num_slice, batch_axis=0, even_split=True): function split_and_load (line 86) | def split_and_load(data, ctx_list, batch_axis=0, even_split=True): function clip_global_norm (line 116) | def clip_global_norm(arrays, max_norm, check_isfinite=True): function _indent (line 169) | def _indent(s_, numSpaces): function check_sha1 (line 181) | def check_sha1(filename, sha1_hash): function replace_file (line 209) | def replace_file(src, dst): function _str_to_unicode (line 238) | def _str_to_unicode(x): function _handle_errors (line 244) | def _handle_errors(rv, src): function replace_file (line 256) | def replace_file(src, dst): function download (line 273) | def download(url, path=None, overwrite=False, sha1_hash=None, retries=5,... function _get_repo_url (line 366) | def _get_repo_url(): function _get_repo_file_url (line 374) | def _get_repo_file_url(namespace, filename): function _brief_print_list (line 388) | def _brief_print_list(lst, limit=7): class HookHandle (line 397) | class HookHandle(object): method __init__ (line 400) | def __init__(self): method attach (line 404) | def attach(self, hooks_dict, hook): method detach (line 410) | def detach(self): method __getstate__ (line 415) | def __getstate__(self): method __setstate__ (line 418) | def __setstate__(self, state): method __enter__ (line 425) | def __enter__(self): method __exit__ (line 428) | def __exit__(self, ptype, value, trace): function shape_is_known (line 432) | def shape_is_known(shape): function _check_same_symbol_type (line 450) | def _check_same_symbol_type(symbols): function _check_all_np_ndarrays (line 473) | def _check_all_np_ndarrays(out): function _check_block_input_np_ndarrays (line 491) | def _check_block_input_np_ndarrays(inputs): function split_rnn_params (line 509) | def split_rnn_params(param, mode, num_layers, input_size, hidden_size, b... FILE: python/mxnet/image/detection.py class DetAugmenter (line 40) | class DetAugmenter(object): method __init__ (line 42) | def __init__(self, **kwargs): method dumps (line 51) | def dumps(self): method __call__ (line 61) | def __call__(self, src, label): class DetBorrowAug (line 66) | class DetBorrowAug(DetAugmenter): method __init__ (line 75) | def __init__(self, augmenter): method dumps (line 81) | def dumps(self): method __call__ (line 85) | def __call__(self, src, label): class DetRandomSelectAug (line 91) | class DetRandomSelectAug(DetAugmenter): method __init__ (line 101) | def __init__(self, aug_list, skip_prob=0): method dumps (line 114) | def dumps(self): method __call__ (line 118) | def __call__(self, src, label): class DetHorizontalFlipAug (line 127) | class DetHorizontalFlipAug(DetAugmenter): method __init__ (line 135) | def __init__(self, p): method __call__ (line 139) | def __call__(self, src, label): method _flip_label (line 146) | def _flip_label(self, label): class DetRandomCropAug (line 153) | class DetRandomCropAug(DetAugmenter): method __init__ (line 176) | def __init__(self, min_object_covered=0.1, aspect_ratio_range=(0.75, 1... method __call__ (line 206) | def __call__(self, src, label): method _calculate_areas (line 214) | def _calculate_areas(self, label): method _intersect (line 221) | def _intersect(self, label, xmin, ymin, xmax, ymax): method _check_satisfy_constraints (line 236) | def _check_satisfy_constraints(self, label, xmin, ymin, xmax, ymax, wi... method _update_labels (line 253) | def _update_labels(self, label, crop_box, height, width): method _random_crop_proposal (line 275) | def _random_crop_proposal(self, label, height, width): class DetRandomPadAug (line 324) | class DetRandomPadAug(DetAugmenter): method __init__ (line 340) | def __init__(self, aspect_ratio_range=(0.75, 1.33), area_range=(1.0, 3... method __call__ (line 370) | def __call__(self, src, label): method _update_labels (line 379) | def _update_labels(self, label, pad_box, height, width): method _random_pad_proposal (line 386) | def _random_pad_proposal(self, label, height, width): function CreateMultiRandCropAugmenter (line 418) | def CreateMultiRandCropAugmenter(min_object_covered=0.1, aspect_ratio_ra... function CreateDetAugmenter (line 483) | def CreateDetAugmenter(data_shape, resize=0, rand_crop=0, rand_pad=0, ra... class ImageDetIter (line 625) | class ImageDetIter(ImageIter): method __init__ (line 671) | def __init__(self, batch_size, data_shape, method _check_valid_label (line 693) | def _check_valid_label(self, label): method _estimate_label_shape (line 703) | def _estimate_label_shape(self): method _parse_label (line 717) | def _parse_label(self, label): method reshape (line 742) | def reshape(self, data_shape=None, label_shape=None): method _batchify (line 761) | def _batchify(self, batch_data, batch_label, start=0): method next (line 792) | def next(self): method augmentation_transform (line 839) | def augmentation_transform(self, data, label): # pylint: disable=argu... method check_label_shape (line 845) | def check_label_shape(self, label_shape): method draw_next (line 856) | def draw_next(self, color=None, thickness=2, mean=None, std=None, clip... method sync_label_shape (line 964) | def sync_label_shape(self, it, verbose=False): FILE: python/mxnet/image/image.py function imread (line 51) | def imread(filename, *args, **kwargs): function imresize (line 96) | def imresize(src, w, h, *args, **kwargs): function imdecode (line 154) | def imdecode(buf, *args, **kwargs): function scale_down (line 214) | def scale_down(src_size, size): function copyMakeBorder (line 249) | def copyMakeBorder(src, top, bot, left, right, *args, **kwargs): function _get_interp_method (line 302) | def _get_interp_method(interp, sizes=()): function resize_short (line 357) | def resize_short(src, size, interp=2): function fixed_crop (line 419) | def fixed_crop(src, x0, y0, w, h, size=None, interp=2): function random_crop (line 451) | def random_crop(src, size, interp=2): function center_crop (line 490) | def center_crop(src, size, interp=2): function color_normalize (line 539) | def color_normalize(src, mean, std=None): function random_size_crop (line 563) | def random_size_crop(src, size, area, ratio, interp=2, **kwargs): function imrotate (line 618) | def imrotate(src, rotation_degrees, zoom_in=False, zoom_out=False): function random_rotate (line 727) | def random_rotate(src, angle_limits, zoom_in=False, zoom_out=False): class Augmenter (line 761) | class Augmenter(object): method __init__ (line 763) | def __init__(self, **kwargs): method dumps (line 772) | def dumps(self): method __call__ (line 782) | def __call__(self, src): class SequentialAug (line 787) | class SequentialAug(Augmenter): method __init__ (line 795) | def __init__(self, ts): method dumps (line 799) | def dumps(self): method __call__ (line 803) | def __call__(self, src): class ResizeAug (line 810) | class ResizeAug(Augmenter): method __init__ (line 820) | def __init__(self, size, interp=2): method __call__ (line 825) | def __call__(self, src): class ForceResizeAug (line 830) | class ForceResizeAug(Augmenter): method __init__ (line 840) | def __init__(self, size, interp=2): method __call__ (line 845) | def __call__(self, src): class RandomCropAug (line 851) | class RandomCropAug(Augmenter): method __init__ (line 861) | def __init__(self, size, interp=2): method __call__ (line 866) | def __call__(self, src): class RandomSizedCropAug (line 871) | class RandomSizedCropAug(Augmenter): method __init__ (line 886) | def __init__(self, size, area, ratio, interp=2, **kwargs): method __call__ (line 900) | def __call__(self, src): class CenterCropAug (line 905) | class CenterCropAug(Augmenter): method __init__ (line 915) | def __init__(self, size, interp=2): method __call__ (line 920) | def __call__(self, src): class RandomOrderAug (line 925) | class RandomOrderAug(Augmenter): method __init__ (line 933) | def __init__(self, ts): method dumps (line 937) | def dumps(self): method __call__ (line 941) | def __call__(self, src): class BrightnessJitterAug (line 949) | class BrightnessJitterAug(Augmenter): method __init__ (line 957) | def __init__(self, brightness): method __call__ (line 961) | def __call__(self, src): class ContrastJitterAug (line 968) | class ContrastJitterAug(Augmenter): method __init__ (line 976) | def __init__(self, contrast): method __call__ (line 981) | def __call__(self, src): class SaturationJitterAug (line 991) | class SaturationJitterAug(Augmenter): method __init__ (line 999) | def __init__(self, saturation): method __call__ (line 1004) | def __call__(self, src): class HueJitterAug (line 1015) | class HueJitterAug(Augmenter): method __init__ (line 1023) | def __init__(self, hue): method __call__ (line 1033) | def __call__(self, src): class ColorJitterAug (line 1049) | class ColorJitterAug(RandomOrderAug): method __init__ (line 1061) | def __init__(self, brightness, contrast, saturation): class LightingAug (line 1072) | class LightingAug(Augmenter): method __init__ (line 1084) | def __init__(self, alphastd, eigval, eigvec): method __call__ (line 1090) | def __call__(self, src): class ColorNormalizeAug (line 1098) | class ColorNormalizeAug(Augmenter): method __init__ (line 1108) | def __init__(self, mean, std): method __call__ (line 1113) | def __call__(self, src): class RandomGrayAug (line 1118) | class RandomGrayAug(Augmenter): method __init__ (line 1126) | def __init__(self, p): method __call__ (line 1133) | def __call__(self, src): class HorizontalFlipAug (line 1140) | class HorizontalFlipAug(Augmenter): method __init__ (line 1148) | def __init__(self, p): method __call__ (line 1152) | def __call__(self, src): class CastAug (line 1159) | class CastAug(Augmenter): method __init__ (line 1161) | def __init__(self, typ='float32'): method __call__ (line 1165) | def __call__(self, src): function CreateAugmenter (line 1171) | def CreateAugmenter(data_shape, resize=0, rand_crop=False, rand_resize=F... class ImageIter (line 1285) | class ImageIter(io.DataIter): method __init__ (line 1340) | def __init__(self, batch_size, data_shape, label_width=1, method reset (line 1435) | def reset(self): method hard_reset (line 1447) | def hard_reset(self): method next_sample (line 1459) | def next_sample(self): method _batchify (line 1490) | def _batchify(self, batch_data, batch_label, start=0): method next (line 1513) | def next(self): method check_data_shape (line 1560) | def check_data_shape(self, data_shape): method check_valid_image (line 1567) | def check_valid_image(self, data): method imdecode (line 1572) | def imdecode(self, s): method read_image (line 1593) | def read_image(self, fname): method augmentation_transform (line 1603) | def augmentation_transform(self, data): method postprocess_data (line 1609) | def postprocess_data(self, datum): FILE: python/mxnet/initializer.py class InitDesc (line 36) | class InitDesc(str): method __new__ (line 49) | def __new__(cls, name, attrs=None, global_init=None): class Initializer (line 56) | class Initializer(object): method __init__ (line 58) | def __init__(self, **kwargs): method set_verbosity (line 63) | def set_verbosity(self, verbose=False, print_func=None): method _verbose_print (line 84) | def _verbose_print(self, desc, init, arr): method dumps (line 99) | def dumps(self): method __call__ (line 120) | def __call__(self, desc, arr): method _legacy_init (line 173) | def _legacy_init(self, name, arr): method _init_bilinear (line 221) | def _init_bilinear(self, _, arr): method _init_loc_bias (line 232) | def _init_loc_bias(self, _, arr): method _init_zero (line 237) | def _init_zero(self, _, arr): method _init_one (line 240) | def _init_one(self, _, arr): method _init_bias (line 243) | def _init_bias(self, _, arr): method _init_quantized_bias (line 246) | def _init_quantized_bias(self, _, arr): method _init_gamma (line 249) | def _init_gamma(self, _, arr): method _init_beta (line 252) | def _init_beta(self, _, arr): method _init_weight (line 255) | def _init_weight(self, name, arr): method _init_quantized_weight (line 259) | def _init_quantized_weight(self, _, arr): method _init_default (line 263) | def _init_default(self, name, _): method __eq__ (line 270) | def __eq__(self, other): function register (line 282) | def register(klass): class Load (line 316) | class Load(object): method __init__ (line 332) | def __init__(self, param, default_init=None, verbose=False): method __call__ (line 345) | def __call__(self, name, arr): class Mixed (line 362) | class Mixed(object): method __init__ (line 391) | def __init__(self, patterns, initializers): method __call__ (line 395) | def __call__(self, name, arr): class Zero (line 405) | class Zero(Initializer): method __init__ (line 422) | def __init__(self): method _init_weight (line 425) | def _init_weight(self, _, arr): class One (line 430) | class One(Initializer): method __init__ (line 447) | def __init__(self): method _init_weight (line 450) | def _init_weight(self, _, arr): class Constant (line 454) | class Constant(Initializer): method __init__ (line 464) | def __init__(self, value): method _init_weight (line 468) | def _init_weight(self, _, arr): method dumps (line 471) | def dumps(self): class Uniform (line 478) | class Uniform(Initializer): method __init__ (line 503) | def __init__(self, scale=0.07): method _init_weight (line 507) | def _init_weight(self, _, arr): class Normal (line 512) | class Normal(Initializer): method __init__ (line 537) | def __init__(self, sigma=0.01): method _init_weight (line 541) | def _init_weight(self, _, arr): class Orthogonal (line 546) | class Orthogonal(Initializer): method __init__ (line 562) | def __init__(self, scale=1.414, rand_type="uniform"): method _init_weight (line 567) | def _init_weight(self, _, arr): class Xavier (line 583) | class Xavier(Initializer): method __init__ (line 614) | def __init__(self, rnd_type="uniform", factor_type="avg", magnitude=3): method _init_weight (line 622) | def _init_weight(self, name, arr): class MSRAPrelu (line 651) | class MSRAPrelu(Xavier): method __init__ (line 669) | def __init__(self, factor_type="avg", slope=0.25): class Bilinear (line 675) | class Bilinear(Initializer): method __init__ (line 677) | def __init__(self): method _init_weight (line 680) | def _init_weight(self, _, arr): class LSTMBias (line 693) | class LSTMBias(Initializer): method __init__ (line 703) | def __init__(self, forget_bias=1.0): method _init_weight (line 707) | def _init_weight(self, name, arr): class RNNFused (line 716) | class RNNFused(Initializer): method __init__ (line 737) | def __init__(self, mode, num_layers, state_size, bidirectional=False, method _init_weight (line 762) | def _init_weight(self, name, arr): method _init_util (line 816) | def _init_util(self, param, connect, arr): method set_initializer (line 821) | def set_initializer(self, init): FILE: python/mxnet/io/io.py class DataDesc (line 42) | class DataDesc(namedtuple('DataDesc', ['name', 'shape'])): method __new__ (line 68) | def __new__(cls, name, shape, dtype=mx_real_t, layout='NCHW'): # pylin... method __repr__ (line 74) | def __repr__(self): method get_batch_axis (line 78) | def get_batch_axis(layout): method get_list (line 100) | def get_list(shapes, types): class DataBatch (line 114) | class DataBatch(object): method __init__ (line 152) | def __init__(self, data, label=None, pad=None, index=None, method __str__ (line 167) | def __str__(self): class DataIter (line 178) | class DataIter(object): method __init__ (line 198) | def __init__(self, batch_size=0): method __iter__ (line 201) | def __iter__(self): method reset (line 204) | def reset(self): method next (line 208) | def next(self): method __next__ (line 227) | def __next__(self): method iter_next (line 230) | def iter_next(self): method getdata (line 240) | def getdata(self): method getlabel (line 250) | def getlabel(self): method getindex (line 260) | def getindex(self): method getpad (line 270) | def getpad(self): class ResizeIter (line 280) | class ResizeIter(DataIter): method __init__ (line 302) | def __init__(self, data_iter, size, reset_internal=True): method reset (line 316) | def reset(self): method iter_next (line 321) | def iter_next(self): method getdata (line 333) | def getdata(self): method getlabel (line 336) | def getlabel(self): method getindex (line 339) | def getindex(self): method getpad (line 342) | def getpad(self): class PrefetchingIter (line 345) | class PrefetchingIter(DataIter): method __init__ (line 373) | def __init__(self, iters, rename_data=None, rename_label=None): method __del__ (line 408) | def __del__(self): method provide_data (line 416) | def provide_data(self): method provide_label (line 427) | def provide_label(self): method reset (line 437) | def reset(self): method iter_next (line 447) | def iter_next(self): method next (line 470) | def next(self): method getdata (line 476) | def getdata(self): method getlabel (line 479) | def getlabel(self): method getindex (line 482) | def getindex(self): method getpad (line 485) | def getpad(self): class NDArrayIter (line 489) | class NDArrayIter(DataIter): method __init__ (line 605) | def __init__(self, data, label=None, batch_size=1, shuffle=False, method provide_data (line 635) | def provide_data(self): method provide_label (line 643) | def provide_label(self): method hard_reset (line 653) | def hard_reset(self): method reset (line 661) | def reset(self): method iter_next (line 673) | def iter_next(self): method next (line 679) | def next(self): method _getdata (line 694) | def _getdata(self, data_source, start=None, end=None): method _concat (line 711) | def _concat(self, first_data, second_data): method _tile (line 725) | def _tile(self, data, repeats): method _batchify (line 735) | def _batchify(self, data_source): method getdata (line 773) | def getdata(self): method getlabel (line 777) | def getlabel(self): method getpad (line 781) | def getpad(self): method _shuffle_data (line 793) | def _shuffle_data(self): class MXDataIter (line 801) | class MXDataIter(DataIter): method __init__ (line 827) | def __init__(self, handle, data_name='data', label_name='softmax_label... method __del__ (line 848) | def __del__(self): method debug_skip_load (line 851) | def debug_skip_load(self): method reset (line 858) | def reset(self): method next (line 863) | def next(self): method iter_next (line 880) | def iter_next(self): method getdata (line 887) | def getdata(self): method getlabel (line 892) | def getlabel(self): method getindex (line 897) | def getindex(self): method getpad (line 911) | def getpad(self): method getitems (line 916) | def getitems(self): method __len__ (line 926) | def __len__(self): function _make_io_iterator (line 934) | def _make_io_iterator(handle): function _init_io_module (line 1011) | def _init_io_module(): FILE: python/mxnet/io/utils.py function _init_data (line 32) | def _init_data(data, allow_empty, default_name): function _has_instance (line 63) | def _has_instance(data, dtype): function _getdata_by_idx (line 74) | def _getdata_by_idx(data, idx): FILE: python/mxnet/kvstore/base.py function _ctype_key_value (line 32) | def _ctype_key_value(keys, vals): function _ctype_dict (line 66) | def _ctype_dict(param_dict): class KVStoreBase (line 74) | class KVStoreBase(object): method broadcast (line 77) | def broadcast(self, key, value, out, priority=0): method pushpull (line 98) | def pushpull(self, key, value, out=None, priority=0): method set_optimizer (line 127) | def set_optimizer(self, optimizer): method is_capable (line 144) | def is_capable(self, capability): method save_optimizer_states (line 160) | def save_optimizer_states(self, fname, dump_optimizer=False): method load_optimizer_states (line 174) | def load_optimizer_states(self, fname): method type (line 185) | def type(self): method rank (line 196) | def rank(self): method num_workers (line 207) | def num_workers(self): method register (line 220) | def register(klass): class TestStore (line 244) | class TestStore(KVStoreBase): method broadcast (line 247) | def broadcast(self, key, value, out, priority=0): method pushpull (line 270) | def pushpull(self, key, value, out=None, priority=0): method is_capable (line 311) | def is_capable(capability): method type (line 333) | def type(self): method rank (line 344) | def rank(self): method num_workers (line 355) | def num_workers(self): method set_optimizer (line 365) | def set_optimizer(self, optimizer): method save_optimizer_states (line 380) | def save_optimizer_states(self, fname, dump_optimizer=False): method load_optimizer_states (line 394) | def load_optimizer_states(self, fname): function create (line 404) | def create(name='local'): FILE: python/mxnet/kvstore/byteps.py class BytePS (line 29) | class BytePS(KVStoreBase): method __init__ (line 32) | def __init__(self): method broadcast (line 45) | def broadcast(self, key, value, out, priority=0): method pushpull (line 105) | def pushpull(self, key, value, out=None, priority=0): method is_capable (line 165) | def is_capable(capability): method type (line 183) | def type(self): method local_rank (line 194) | def local_rank(self): method rank (line 205) | def rank(self): method num_workers (line 216) | def num_workers(self): method set_optimizer (line 226) | def set_optimizer(self, optimizer): method save_optimizer_states (line 237) | def save_optimizer_states(self, fname, dump_optimizer=False): method load_optimizer_states (line 251) | def load_optimizer_states(self, fname): FILE: python/mxnet/kvstore/horovod.py class Horovod (line 27) | class Horovod(KVStoreBase): method __init__ (line 30) | def __init__(self): method type (line 35) | def type(self): method broadcast (line 38) | def broadcast(self, key, value, out, priority=0): method pushpull (line 75) | def pushpull(self, key, value, out=None, priority=0): method set_optimizer (line 135) | def set_optimizer(self, optimizer): method is_capable (line 139) | def is_capable(capability): method save_optimizer_states (line 142) | def save_optimizer_states(self, fname, dump_optimizer=False): method load_optimizer_states (line 145) | def load_optimizer_states(self, fname): method rank (line 149) | def rank(self): method local_rank (line 154) | def local_rank(self): method num_workers (line 159) | def num_workers(self): FILE: python/mxnet/kvstore/kvstore.py function _updater_wrapper (line 34) | def _updater_wrapper(updater): function _get_kvstore_server_command_type (line 43) | def _get_kvstore_server_command_type(command): class KVStore (line 54) | class KVStore(KVStoreBase): method __init__ (line 57) | def __init__(self, handle): method __del__ (line 72) | def __del__(self): method broadcast (line 75) | def broadcast(self, key, value, out, priority=0): method is_capable (line 121) | def is_capable(self, capability): method init (line 140) | def init(self, key, value): method push (line 184) | def push(self, key, value, priority=0): method pull (line 265) | def pull(self, key, out=None, priority=0, ignore_sparse=True): method pushpull (line 340) | def pushpull(self, key, value, out=None, priority=0): method row_sparse_pull (line 420) | def row_sparse_pull(self, key, out=None, priority=0, row_ids=None): method set_gradient_compression (line 500) | def set_gradient_compression(self, compression_params): method set_optimizer (line 559) | def set_optimizer(self, optimizer): method type (line 609) | def type(self): method rank (line 622) | def rank(self): method num_workers (line 635) | def num_workers(self): method save_optimizer_states (line 647) | def save_optimizer_states(self, fname, dump_optimizer=False): method load_optimizer_states (line 663) | def load_optimizer_states(self, fname): method _set_updater (line 674) | def _set_updater(self, updater): method _barrier (line 715) | def _barrier(self): method _send_command_to_servers (line 725) | def _send_command_to_servers(self, head, body): FILE: python/mxnet/kvstore/kvstore_server.py class KVStoreServer (line 29) | class KVStoreServer(object): method __init__ (line 31) | def __init__(self, kvstore): method _controller (line 42) | def _controller(self): method run (line 64) | def run(self): function _init_kvstore_server_module (line 75) | def _init_kvstore_server_module(): FILE: python/mxnet/libinfo.py function find_lib_path (line 25) | def find_lib_path(prefix='libmxnet'): function find_include_path (line 84) | def find_include_path(): function find_conf_path (line 118) | def find_conf_path(prefix='tvmop'): FILE: python/mxnet/library.py class MXlib (line 27) | class MXlib: method __init__ (line 29) | def __init__(self, handle): method __del__ (line 31) | def __del__(self): function load (line 38) | def load(path, verbose=True): function compiled_with_gcc_cxx11_abi (line 92) | def compiled_with_gcc_cxx11_abi(): FILE: python/mxnet/log.py class _Formatter (line 34) | class _Formatter(logging.Formatter): method __init__ (line 38) | def __init__(self): method _get_color (line 42) | def _get_color(self, level): method _get_label (line 50) | def _get_label(self, level): method format (line 64) | def format(self, record): function getLogger (line 74) | def getLogger(name=None, filename=None, filemode=None, level=WARNING): function get_logger (line 84) | def get_logger(name=None, filename=None, filemode=None, level=WARNING): FILE: python/mxnet/lr_scheduler.py class LRScheduler (line 22) | class LRScheduler(object): method __init__ (line 41) | def __init__(self, base_lr=0.01, method get_warmup_lr (line 57) | def get_warmup_lr(self, num_update): method __call__ (line 68) | def __call__(self, num_update): class FactorScheduler (line 86) | class FactorScheduler(LRScheduler): method __init__ (line 102) | def __init__(self, step, factor=1, stop_factor_lr=1e-8, base_lr=0.01, method __call__ (line 114) | def __call__(self, num_update): class MultiFactorScheduler (line 131) | class MultiFactorScheduler(LRScheduler): method __init__ (line 157) | def __init__(self, step, factor=1, base_lr=0.01, warmup_steps=0, warmu... method __call__ (line 174) | def __call__(self, num_update): class PolyScheduler (line 190) | class PolyScheduler(LRScheduler): method __init__ (line 218) | def __init__(self, max_update, base_lr=0.01, pwr=2, final_lr=0, method __call__ (line 230) | def __call__(self, num_update): class CosineScheduler (line 238) | class CosineScheduler(LRScheduler): method __init__ (line 264) | def __init__(self, max_update, base_lr=0.01, final_lr=0, method __call__ (line 275) | def __call__(self, num_update): FILE: python/mxnet/misc.py class LearningRateScheduler (line 24) | class LearningRateScheduler(object): method __init__ (line 26) | def __init__(self): method __call__ (line 29) | def __call__(self, iteration): class FactorScheduler (line 41) | class FactorScheduler(LearningRateScheduler): method __init__ (line 51) | def __init__(self, step, factor=0.1): method __call__ (line 62) | def __call__(self, iteration): FILE: python/mxnet/model.py function _create_sparse_kvstore (line 47) | def _create_sparse_kvstore(kvstore): function _create_kvstore (line 74) | def _create_kvstore(kvstore, num_device, arg_params): function _initialize_kvstore (line 115) | def _initialize_kvstore(kvstore, param_arrays, arg_params, param_names, ... function _update_params_on_kvstore_nccl (line 124) | def _update_params_on_kvstore_nccl(param_arrays, grad_arrays, kvstore, p... function _update_params_on_kvstore (line 144) | def _update_params_on_kvstore(param_arrays, grad_arrays, kvstore, param_... function _update_params (line 159) | def _update_params(param_arrays, grad_arrays, updater, num_device, function save_checkpoint (line 189) | def save_checkpoint(prefix, epoch, symbol, arg_params, aux_params, remov... function load_params (line 221) | def load_params(prefix, epoch): function load_checkpoint (line 238) | def load_checkpoint(prefix, epoch): FILE: python/mxnet/name.py class NameManager (line 21) | class NameManager: method __init__ (line 26) | def __init__(self): method get (line 30) | def get(self, name, hint): method __enter__ (line 61) | def __enter__(self): method __exit__ (line 67) | def __exit__(self, ptype, value, trace): class Prefix (line 71) | class Prefix(NameManager): method __init__ (line 83) | def __init__(self, prefix): method get (line 87) | def get(self, name, hint): function current (line 95) | def current(): FILE: python/mxnet/ndarray/contrib.py function _flatten_list (line 35) | def _flatten_list(nested_list): function rand_zipfian (line 39) | def rand_zipfian(true_classes, num_sampled, range_max, ctx=None): function _flatten (line 107) | def _flatten(args, inout_str): function _regroup (line 123) | def _regroup(args, fmt): function foreach (line 139) | def foreach(body, data, init_states): function while_loop (line 233) | def while_loop(cond, func, loop_vars, max_iterations=None): function cond (line 401) | def cond(pred, then_func, else_func): function isinf (line 467) | def isinf(data): function isfinite (line 493) | def isfinite(data): function isnan (line 522) | def isnan(data): function _get_rescale_grad (line 548) | def _get_rescale_grad(rescale_grad, ctx=mx.cpu()): function adamw_update (line 554) | def adamw_update(weight, grad, mean, var, rescale_grad, lr, eta, beta1=0... function mp_adamw_update (line 563) | def mp_adamw_update(weight, grad, mean, var, weight32, rescale_grad, lr,... function multi_adamw_update (line 574) | def multi_adamw_update(weights, grads, mean, var, rescale_grad, lrs, wds... function multi_mp_adamw_update (line 590) | def multi_mp_adamw_update(weights, grads, mean, var, weights32, rescale_... function multi_lamb_update (line 606) | def multi_lamb_update(weights, grads, mean, var, step_count, function multi_mp_lamb_update (line 643) | def multi_mp_lamb_update(weights, grads, mean, var, weights32, step_count, function adabelief_update (line 682) | def adabelief_update(weight, grad, mean, var, rescale_grad, lr, eta, bet... function mp_adabelief_update (line 691) | def mp_adabelief_update(weight, grad, mean, var, weight32, rescale_grad,... function multi_adabelief_update (line 702) | def multi_adabelief_update(weights, grads, mean, var, rescale_grad, lrs,... function multi_mp_adabelief_update (line 718) | def multi_mp_adabelief_update(weights, grads, mean, var, weights32, resc... function multi_lans_update (line 734) | def multi_lans_update(weights, grads, mean, var, step_count, function multi_mp_lans_update (line 772) | def multi_mp_lans_update(weights, grads, mean, var, weights32, step_count, FILE: python/mxnet/ndarray/ndarray.py function _register_platform_dependent_mx_dtype (line 85) | def _register_platform_dependent_mx_dtype(): function get_dtype_type (line 117) | def get_dtype_type(dtype): function is_mx_dtype (line 122) | def is_mx_dtype(dtype): function get_dtype_name (line 125) | def get_dtype_name(dtype): function dtype_np_to_mx (line 129) | def dtype_np_to_mx(dtype): function dtype_mx_to_np (line 135) | def dtype_mx_to_np(dtype_idx): function _int64_enabled (line 174) | def _int64_enabled(): function _new_empty_handle (line 180) | def _new_empty_handle(): function _new_alloc_handle (line 195) | def _new_alloc_handle(shape, ctx, delay_alloc, dtype=mx_real_t): function _new_from_shared_mem (line 236) | def _new_from_shared_mem(shared_pid, shared_id, shape, dtype): function waitall (line 248) | def waitall(): function _storage_type (line 260) | def _storage_type(handle): class NDArray (line 266) | class NDArray(NDArrayBase): method as_np_ndarray (line 279) | def as_np_ndarray(self): method as_nd_ndarray (line 290) | def as_nd_ndarray(self): method _tvm_handle (line 297) | def _tvm_handle(self): method __repr__ (line 300) | def __repr__(self): method __reduce__ (line 308) | def __reduce__(self): method _to_shared_mem (line 311) | def _to_shared_mem(self): method __abs__ (line 318) | def __abs__(self): method __add__ (line 322) | def __add__(self, other): method __iadd__ (line 326) | def __iadd__(self, other): method __radd__ (line 337) | def __radd__(self, other): method __sub__ (line 340) | def __sub__(self, other): method __isub__ (line 344) | def __isub__(self, other): method __rsub__ (line 355) | def __rsub__(self, other): method __mul__ (line 359) | def __mul__(self, other): method __neg__ (line 363) | def __neg__(self): method __imul__ (line 367) | def __imul__(self, other): method __rmul__ (line 378) | def __rmul__(self, other): method __div__ (line 381) | def __div__(self, other): method __rdiv__ (line 385) | def __rdiv__(self, other): method __idiv__ (line 389) | def __idiv__(self, other): method __truediv__ (line 400) | def __truediv__(self, other): method __rtruediv__ (line 403) | def __rtruediv__(self, other): method __itruediv__ (line 406) | def __itruediv__(self, other): method __mod__ (line 409) | def __mod__(self, other): method __rmod__ (line 413) | def __rmod__(self, other): method __imod__ (line 417) | def __imod__(self, other): method __pow__ (line 428) | def __pow__(self, other): method __rpow__ (line 432) | def __rpow__(self, other): method __eq__ (line 436) | def __eq__(self, other): method __hash__ (line 440) | def __hash__(self): method __ne__ (line 444) | def __ne__(self, other): method __gt__ (line 448) | def __gt__(self, other): method __ge__ (line 452) | def __ge__(self, other): method __lt__ (line 456) | def __lt__(self, other): method __le__ (line 460) | def __le__(self, other): method __bool__ (line 464) | def __bool__(self): method __str__ (line 476) | def __str__(self): method __len__ (line 483) | def __len__(self): method __getstate__ (line 487) | def __getstate__(self): method __setstate__ (line 499) | def __setstate__(self, state): method __setitem__ (line 512) | def __setitem__(self, key, value): method __getitem__ (line 609) | def __getitem__(self, key): # pylint: disable=too-many-return-statements method _prepare_value_nd (line 788) | def _prepare_value_nd(self, value, bcast_shape, squeeze_axes=None): method _basic_indexing_key_to_begin_end_step (line 837) | def _basic_indexing_key_to_begin_end_step(idcs, shape, keep_none=True): method _basic_indexing_key_int_to_slice (line 852) | def _basic_indexing_key_int_to_slice(idcs): method _new_axes_after_basic_indexing (line 867) | def _new_axes_after_basic_indexing(axes, key): method _new_axes_after_advanced_indexing (line 883) | def _new_axes_after_advanced_indexing(key, adv_axs, bcast_adv_ndim, ad... method _basic_indexing_slice_is_contiguous (line 911) | def _basic_indexing_slice_is_contiguous(slc_key, shape): method _basic_indexing_sliced_shape (line 945) | def _basic_indexing_sliced_shape(slc_key, shape): method _basic_indexing_contiguous_flat_begin_end (line 956) | def _basic_indexing_contiguous_flat_begin_end(slc_key, shape): method _drop_int_axes (line 974) | def _drop_int_axes(indexed_shape, int_axes): method _set_nd_basic_indexing (line 984) | def _set_nd_basic_indexing(self, key, value): method _get_nd_basic_indexing (line 1063) | def _get_nd_basic_indexing(self, key): method _advanced_index_to_array (line 1142) | def _advanced_index_to_array(idx, ax_len, ctx): method _broadcast_advanced_indices (line 1169) | def _broadcast_advanced_indices(arrays, block_axes): method _drop_slice_none_at_end (line 1215) | def _drop_slice_none_at_end(key): method _get_index_nd (line 1227) | def _get_index_nd(self, key): method _set_nd_advanced_indexing (line 1326) | def _set_nd_advanced_indexing(self, key, value): method _get_nd_advanced_indexing (line 1333) | def _get_nd_advanced_indexing(self, key): method _sync_copyfrom (line 1348) | def _sync_copyfrom(self, source_array): method _slice (line 1384) | def _slice(self, start, stop): method _at (line 1414) | def _at(self, idx): method reshape (line 1451) | def reshape(self, *shape, **kwargs): method reshape_like (line 1579) | def reshape_like(self, *args, **kwargs): method zeros_like (line 1587) | def zeros_like(self, *args, **kwargs): method ones_like (line 1595) | def ones_like(self, *args, **kwargs): method broadcast_axes (line 1603) | def broadcast_axes(self, *args, **kwargs): method repeat (line 1611) | def repeat(self, *args, **kwargs): method pad (line 1619) | def pad(self, *args, **kwargs): method swapaxes (line 1627) | def swapaxes(self, *args, **kwargs): method split (line 1635) | def split(self, *args, **kwargs): method split_v2 (line 1643) | def split_v2(self, *args, **kwargs): method slice (line 1651) | def slice(self, *args, **kwargs): method slice_axis (line 1659) | def slice_axis(self, *args, **kwargs): method slice_like (line 1667) | def slice_like(self, *args, **kwargs): method take (line 1675) | def take(self, *args, **kwargs): method one_hot (line 1683) | def one_hot(self, *args, **kwargs): method pick (line 1691) | def pick(self, *args, **kwargs): method sort (line 1699) | def sort(self, *args, **kwargs): method topk (line 1707) | def topk(self, *args, **kwargs): method argsort (line 1715) | def argsort(self, *args, **kwargs): method argmax (line 1723) | def argmax(self, *args, **kwargs): method argmax_channel (line 1731) | def argmax_channel(self, *args, **kwargs): method argmin (line 1739) | def argmin(self, *args, **kwargs): method clip (line 1747) | def clip(self, *args, **kwargs): method abs (line 1755) | def abs(self, *args, **kwargs): method sign (line 1763) | def sign(self, *args, **kwargs): method flatten (line 1771) | def flatten(self, inplace=False): method shape_array (line 1804) | def shape_array(self, *args, **kwargs): method size_array (line 1812) | def size_array(self, *args, **kwargs): method expand_dims (line 1820) | def expand_dims(self, axis, inplace=False): method tile (line 1867) | def tile(self, *args, **kwargs): method transpose (line 1875) | def transpose(self, *args, **kwargs): method flip (line 1883) | def flip(self, *args, **kwargs): method depth_to_space (line 1891) | def depth_to_space(self, *args, **kwargs): method space_to_depth (line 1899) | def space_to_depth(self, *args, **kwargs): method diag (line 1907) | def diag(self, k=0, **kwargs): method sum (line 1915) | def sum(self, *args, **kwargs): method nansum (line 1923) | def nansum(self, *args, **kwargs): method prod (line 1931) | def prod(self, *args, **kwargs): method nanprod (line 1939) | def nanprod(self, *args, **kwargs): method mean (line 1947) | def mean(self, *args, **kwargs): method max (line 1955) | def max(self, *args, **kwargs): method min (line 1963) | def min(self, *args, **kwargs): method norm (line 1971) | def norm(self, *args, **kwargs): method round (line 1979) | def round(self, *args, **kwargs): method rint (line 1987) | def rint(self, *args, **kwargs): method fix (line 1995) | def fix(self, *args, **kwargs): method floor (line 2003) | def floor(self, *args, **kwargs): method ceil (line 2011) | def ceil(self, *args, **kwargs): method trunc (line 2019) | def trunc(self, *args, **kwargs): method sin (line 2027) | def sin(self, *args, **kwargs): method cos (line 2035) | def cos(self, *args, **kwargs): method tan (line 2043) | def tan(self, *args, **kwargs): method arcsin (line 2051) | def arcsin(self, *args, **kwargs): method arccos (line 2059) | def arccos(self, *args, **kwargs): method arctan (line 2067) | def arctan(self, *args, **kwargs): method degrees (line 2075) | def degrees(self, *args, **kwargs): method radians (line 2083) | def radians(self, *args, **kwargs): method sinh (line 2091) | def sinh(self, *args, **kwargs): method cosh (line 2099) | def cosh(self, *args, **kwargs): method tanh (line 2107) | def tanh(self, *args, **kwargs): method arcsinh (line 2115) | def arcsinh(self, *args, **kwargs): method arccosh (line 2123) | def arccosh(self, *args, **kwargs): method arctanh (line 2131) | def arctanh(self, *args, **kwargs): method exp (line 2139) | def exp(self, *args, **kwargs): method expm1 (line 2147) | def expm1(self, *args, **kwargs): method log (line 2155) | def log(self, *args, **kwargs): method log10 (line 2163) | def log10(self, *args, **kwargs): method log2 (line 2171) | def log2(self, *args, **kwargs): method log1p (line 2179) | def log1p(self, *args, **kwargs): method log_sigmoid (line 2187) | def log_sigmoid(self, *args, **kwargs): method sqrt (line 2195) | def sqrt(self, *args, **kwargs): method rsqrt (line 2203) | def rsqrt(self, *args, **kwargs): method cbrt (line 2211) | def cbrt(self, *args, **kwargs): method rcbrt (line 2219) | def rcbrt(self, *args, **kwargs): method square (line 2227) | def square(self, *args, **kwargs): method reciprocal (line 2235) | def reciprocal(self, *args, **kwargs): method relu (line 2243) | def relu(self, *args, **kwargs): method sigmoid (line 2251) | def sigmoid(self, *args, **kwargs): method softmax (line 2259) | def softmax(self, *args, **kwargs): method log_softmax (line 2267) | def log_softmax(self, *args, **kwargs): method softmin (line 2275) | def softmin(self, *args, **kwargs): method mish (line 2283) | def mish(self, *args, **kwargs): method squeeze (line 2291) | def squeeze(self, axis=None, inplace=False): method broadcast_to (line 2332) | def broadcast_to(self, shape): method broadcast_like (line 2384) | def broadcast_like(self, other): method wait_to_read (line 2422) | def wait_to_read(self): method ndim (line 2443) | def ndim(self): method shape (line 2458) | def shape(self): method size (line 2486) | def size(self): method context (line 2506) | def context(self): method ctx (line 2527) | def ctx(self): method device (line 2544) | def device(self): method dtype (line 2561) | def dtype(self): method stype (line 2584) | def stype(self): method T (line 2591) | def T(self): method _fresh_grad (line 2618) | def _fresh_grad(self): method _fresh_grad (line 2632) | def _fresh_grad(self, state): method asnumpy (line 2635) | def asnumpy(self): method asscalar (line 2661) | def asscalar(self): method astype (line 2681) | def astype(self, dtype, copy=True): method copyto (line 2716) | def copyto(self, other): method copy (line 2762) | def copy(self): method slice_assign_scalar (line 2780) | def slice_assign_scalar(self, value, begin, end, step): method slice_assign (line 2821) | def slice_assign(self, rhs, begin, end, step): method as_in_context (line 2862) | def as_in_context(self, context): method attach_grad (line 2893) | def attach_grad(self, grad_req='write', stype=None): method drop_grad (line 2920) | def drop_grad(self): method grad (line 2926) | def grad(self): method detach (line 2935) | def detach(self): method backward (line 2942) | def backward(self, out_grad=None, retain_graph=False, train_mode=True): method tostype (line 2972) | def tostype(self, stype): method to_dlpack_for_read (line 2990) | def to_dlpack_for_read(self): method to_dlpack_for_write (line 3013) | def to_dlpack_for_write(self): method _full (line 3037) | def _full(self, value): method _scatter_set_nd (line 3043) | def _scatter_set_nd(self, value_nd, indices): function check_boolean_array_dimension (line 3051) | def check_boolean_array_dimension(array_shape, axis, bool_shape): function indexing_key_expand_implicit_axes (line 3063) | def indexing_key_expand_implicit_axes(key, shape): function _int_to_slice (line 3160) | def _int_to_slice(idx): function _shape_for_bcast (line 3169) | def _shape_for_bcast(shape, target_ndim, new_axes): function _is_advanced_index (line 3195) | def _is_advanced_index(idx): function get_indexing_dispatch_code (line 3212) | def get_indexing_dispatch_code(key): function _get_index_range (line 3229) | def _get_index_range(start, stop, length, step=1): function get_oshape_of_gather_nd_op (line 3272) | def get_oshape_of_gather_nd_op(dshape, ishape): function _get_dim_size (line 3282) | def _get_dim_size(start, stop, step): function _get_slice_len (line 3298) | def _get_slice_len(slc, seq_length): function _get_broadcast_shape (line 3318) | def _get_broadcast_shape(shape1, shape2): function _broadcast_shapes (line 3339) | def _broadcast_shapes(seq): function onehot_encode (line 3347) | def onehot_encode(indices, out): function ones (line 3358) | def ones(shape, ctx=None, dtype=None, **kwargs): function full (line 3396) | def full(shape, val, ctx=None, dtype=mx_real_t, out=None): function array (line 3431) | def array(source_array, ctx=None, dtype=None): function moveaxis (line 3473) | def moveaxis(tensor, source, destination): function arange (line 3525) | def arange(start, stop=None, step=1.0, repeat=1, infer_range=None, ctx=N... function linspace (line 3580) | def linspace(start, stop, num, endpoint=True, ctx=None, dtype=mx_real_t): function _ufunc_helper (line 3626) | def _ufunc_helper(lhs, rhs, fn_array, fn_scalar, lfn_scalar, rfn_scalar=... function add (line 3674) | def add(lhs, rhs): function subtract (line 3736) | def subtract(lhs, rhs): function multiply (line 3798) | def multiply(lhs, rhs): function divide (line 3859) | def divide(lhs, rhs): function modulo (line 3916) | def modulo(lhs, rhs): function power (line 3973) | def power(base, exp): function maximum (line 4035) | def maximum(lhs, rhs): function minimum (line 4092) | def minimum(lhs, rhs): function equal (line 4149) | def equal(lhs, rhs): function not_equal (line 4213) | def not_equal(lhs, rhs): function greater (line 4280) | def greater(lhs, rhs): function greater_equal (line 4344) | def greater_equal(lhs, rhs): function lesser (line 4408) | def lesser(lhs, rhs): function lesser_equal (line 4472) | def lesser_equal(lhs, rhs): function logical_and (line 4535) | def logical_and(lhs, rhs): function logical_or (line 4595) | def logical_or(lhs, rhs): function logical_xor (line 4655) | def logical_xor(lhs, rhs): function true_divide (line 4709) | def true_divide(lhs, rhs): function concatenate (line 4716) | def concatenate(arrays, axis=0, always_copy=True): function imdecode (line 4779) | def imdecode(str_img, clip_rect=(0, 0, 0, 0), out=None, index=0, channel... function zeros (line 4821) | def zeros(shape, ctx=None, dtype=None, **kwargs): function eye (line 4857) | def eye(N, M=0, k=0, ctx=None, dtype=None, **kwargs): function empty (line 4900) | def empty(shape, ctx=None, dtype=None): function histogram (line 4928) | def histogram(a, bins=10, range=None): function split_v2 (line 4965) | def split_v2(ary, indices_or_sections, axis=0, squeeze_axis=False): FILE: python/mxnet/ndarray/numpy/_op.py function shape (line 58) | def shape(a): function zeros (line 92) | def zeros(shape, dtype=None, order='C', device=None): # pylint: disable... function ones (line 134) | def ones(shape, dtype=None, order='C', device=None): # pylint: disable=... function zeros_like (line 174) | def zeros_like(a, dtype=None, order='C', device=None, out=None): function ones_like (line 234) | def ones_like(a, dtype=None, order='C', device=None, out=None): function broadcast_to (line 292) | def broadcast_to(array, shape): function full (line 322) | def full(shape, fill_value, dtype=None, order='C', device=None, out=None... function full_like (line 405) | def full_like(a, fill_value, dtype=None, order='C', device=None, out=Non... function empty_like (line 471) | def empty_like(prototype, dtype=None, order='C', subok=False, shape=None... function arange (line 545) | def arange(start, stop=None, step=1, dtype=None, device=None): function identity (line 601) | def identity(n, dtype=None, device=None): function take (line 649) | def take(a, indices, axis=None, mode='raise', out=None): function insert (line 735) | def insert(arr, obj, values, axis=None): function _ufunc_helper (line 843) | def _ufunc_helper(lhs, rhs, fn_array, fn_scalar, lfn_scalar, rfn_scalar=... function unique (line 894) | def unique(ar, return_index=False, return_inverse=False, return_counts=F... function add (line 1000) | def add(x1, x2, out=None, **kwargs): function subtract (line 1035) | def subtract(x1, x2, out=None, **kwargs): function multiply (line 1071) | def multiply(x1, x2, out=None, **kwargs): function divide (line 1107) | def divide(x1, x2, out=None, **kwargs): function true_divide (line 1145) | def true_divide(x1, x2, out=None): function floor_divide (line 1187) | def floor_divide(x1, x2, out=None): function mod (line 1226) | def mod(x1, x2, out=None, **kwargs): function fmod (line 1255) | def fmod(x1, x2, out=None, **kwargs): function delete (line 1283) | def delete(arr, obj, axis=None): function matmul (line 1345) | def matmul(a, b, out=None): function remainder (line 1445) | def remainder(x1, x2, out=None): function power (line 1474) | def power(x1, x2, out=None, **kwargs): function all (line 1503) | def all(a, axis=None, out=None, keepdims=False): function any (line 1552) | def any(a, axis=None, out=None, keepdims=False): function argsort (line 1607) | def argsort(a, axis=-1, descending=False, stable=True): function sort (line 1685) | def sort(a, axis=-1, descending=False, stable=True): function dot (line 1734) | def dot(a, b, out=None): function tensordot (line 1796) | def tensordot(a, b, axes=2): function histogram (line 1853) | def histogram(a, bins=10, range=None, normed=None, weights=None, density... function eye (line 1900) | def eye(N, M=None, k=0, dtype=float, **kwargs): function linspace (line 1944) | def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=No... function logspace (line 2047) | def logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None, ... function expand_dims (line 2135) | def expand_dims(a, axis): function gcd (line 2158) | def gcd(x1, x2, out=None, **kwargs): function lcm (line 2198) | def lcm(x1, x2, out=None, **kwargs): function tril (line 2237) | def tril(m, k=0): function triu (line 2273) | def triu(m, k=0): function trace (line 2298) | def trace(a, offset=0, axis1=0, axis2=1, out=None): function tri (line 2345) | def tri(N, M=None, k=0, dtype=None, device=None): function triu_indices (line 2387) | def triu_indices(n, k=0, m=None, device=None): function triu_indices_from (line 2466) | def triu_indices_from(arr, k=0): function _unary_func_helper (line 2489) | def _unary_func_helper(x, fn_array, fn_scalar, out=None, **kwargs): function _pure_unary_func_helper (line 2516) | def _pure_unary_func_helper(x, fn_array, fn_scalar, out=None, **kwargs): function sin (line 2545) | def sin(x, out=None, **kwargs): function cos (line 2580) | def cos(x, out=None, **kwargs): function sinh (line 2618) | def sinh(x, out=None, **kwargs): function cosh (line 2657) | def cosh(x, out=None, **kwargs): function tanh (line 2691) | def tanh(x, out=None, **kwargs): function log10 (line 2737) | def log10(x, out=None, **kwargs): function sqrt (line 2771) | def sqrt(x, out=None, **kwargs): function cbrt (line 2806) | def cbrt(x, out=None, **kwargs): function abs (line 2835) | def abs(x, out=None, **kwargs): function fabs (line 2865) | def fabs(x, out=None, **kwargs): function absolute (line 2900) | def absolute(x, out=None, **kwargs): function sign (line 2930) | def sign(x, out=None, **kwargs): function exp (line 2980) | def exp(x, out=None, **kwargs): function expm1 (line 3012) | def expm1(x, out=None, **kwargs): function arcsin (line 3044) | def arcsin(x, out=None, **kwargs): function arccos (line 3101) | def arccos(x, out=None, **kwargs): function arctan (line 3144) | def arctan(x, out=None, **kwargs): function log (line 3189) | def log(x, out=None, **kwargs): function degrees (line 3241) | def degrees(x, out=None, **kwargs): function rad2deg (line 3288) | def rad2deg(x, out=None, **kwargs): function rint (line 3324) | def rint(x, out=None, **kwargs): function log2 (line 3362) | def log2(x, out=None, **kwargs): function log1p (line 3401) | def log1p(x, out=None, **kwargs): function radians (line 3447) | def radians(x, out=None, **kwargs): function deg2rad (line 3487) | def deg2rad(x, out=None, **kwargs): function reciprocal (line 3523) | def reciprocal(x, out=None, **kwargs): function square (line 3569) | def square(x, out=None, **kwargs): function negative (line 3610) | def negative(x, out=None, **kwargs): function positive (line 3636) | def positive(x, out=None, **kwargs): function fix (line 3670) | def fix(x, out=None, **kwargs): function tan (line 3696) | def tan(x, out=None, **kwargs): function ceil (line 3730) | def ceil(x, out=None, **kwargs): function floor (line 3771) | def floor(x, out=None, **kwargs): function bitwise_not (line 3812) | def bitwise_not(x, out=None, **kwargs): function invert (line 3865) | def invert(x, out=None, **kwargs): function trunc (line 3918) | def trunc(x, out=None, **kwargs): function logical_not (line 3959) | def logical_not(x, out=None, **kwargs): function arcsinh (line 4000) | def arcsinh(x, out=None, **kwargs): function arccosh (line 4046) | def arccosh(x, out=None, **kwargs): function arctanh (line 4092) | def arctanh(x, out=None, **kwargs): function tile (line 4137) | def tile(A, reps): function transpose (line 4210) | def transpose(a, axes=None): function repeat (line 4253) | def repeat(a, repeats, axis=None): function split (line 4299) | def split(ary, indices_or_sections, axis=0): function array_split (line 4341) | def array_split(ary, indices_or_sections, axis=0): function hsplit (line 4397) | def hsplit(ary, indices_or_sections): function vsplit (line 4495) | def vsplit(ary, indices_or_sections): function dsplit (line 4575) | def dsplit(ary, indices_or_sections): function concatenate (line 4634) | def concatenate(seq, axis=0, out=None): function append (line 4676) | def append(arr, values, axis=None): # pylint: disable=redefined-outer-name function stack (line 4717) | def stack(arrays, axis=0, out=None): function vstack (line 4746) | def vstack(arrays, out=None): function row_stack (line 4797) | def row_stack(arrays): function column_stack (line 4842) | def column_stack(tup): function hstack (line 4872) | def hstack(arrays): function dstack (line 4911) | def dstack(arrays): function maximum (line 4954) | def maximum(x1, x2, out=None, **kwargs): function fmax (line 4975) | def fmax(x1, x2, out=None, **kwargs): function minimum (line 4996) | def minimum(x1, x2, out=None, **kwargs): function fmin (line 5017) | def fmin(x1, x2, out=None, **kwargs): function max (line 5037) | def max(a, axis=None, out=None, keepdims=False): function min (line 5102) | def min(a, axis=None, out=None, keepdims=False): function amax (line 5164) | def amax(a, axis=None, out=None, keepdims=False): function amin (line 5229) | def amin(a, axis=None, out=None, keepdims=False): function swapaxes (line 5291) | def swapaxes(a, axis1, axis2): function clip (line 5312) | def clip(a, a_min, a_max, out=None): function tril_indices (line 5365) | def tril_indices(n, k=0, m=None): function argmax (line 5447) | def argmax(a, axis=None, out=None, keepdims=False): function argmin (line 5525) | def argmin(a, axis=None, out=None, keepdims=False): function average (line 5602) | def average(a, axis=None, weights=None, returned=False, out=None): function mean (line 5698) | def mean(a, axis=None, dtype=None, out=None, keepdims=False): # pylint:... function std (line 5760) | def std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False): # ... function var (line 5827) | def var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False): # ... function indices (line 5900) | def indices(dimensions, dtype=None, device=None): function copysign (line 5972) | def copysign(x1, x2, out=None, **kwargs): function ravel (line 6024) | def ravel(x, order='C'): function unravel_index (line 6077) | def unravel_index(indices, shape, order='C'): # pylint: disable=redefine... function flatnonzero (line 6112) | def flatnonzero(a): function diag_indices_from (line 6152) | def diag_indices_from(arr): function hanning (line 6192) | def hanning(M, dtype=None, device=None): function hamming (line 6279) | def hamming(M, dtype=None, device=None): function blackman (line 6364) | def blackman(M, dtype=None, device=None): function flip (line 6447) | def flip(m, axis=None, out=None): function flipud (line 6515) | def flipud(m): function fliplr (line 6568) | def fliplr(m): function around (line 6617) | def around(x, decimals=0, out=None, **kwargs): function round (line 6674) | def round(x, decimals=0, out=None, **kwargs): function round_ (line 6693) | def round_(x, decimals=0, out=None, **kwargs): function arctan2 (line 6713) | def arctan2(x1, x2, out=None, **kwargs): function hypot (line 6799) | def hypot(x1, x2, out=None, **kwargs): function bitwise_and (line 6849) | def bitwise_and(x1, x2, out=None, **kwargs): function bitwise_xor (line 6891) | def bitwise_xor(x1, x2, out=None, **kwargs): function bitwise_or (line 6931) | def bitwise_or(x1, x2, out=None, **kwargs): function ldexp (line 6971) | def ldexp(x1, x2, out=None, **kwargs): function logaddexp (line 7012) | def logaddexp(x1, x2, out=None, **kwargs): function vdot (line 7053) | def vdot(a, b): function inner (line 7093) | def inner(a, b): function outer (line 7150) | def outer(a, b): function cross (line 7200) | def cross(a, b, axisa=-1, axisb=-1, axisc=-1, axis=None): # pylint: disa... function kron (line 7314) | def kron(a, b): function equal (line 7354) | def equal(x1, x2, out=None): function not_equal (line 7388) | def not_equal(x1, x2, out=None): function greater (line 7423) | def greater(x1, x2, out=None): function less (line 7457) | def less(x1, x2, out=None): function greater_equal (line 7491) | def greater_equal(x1, x2, out=None): function less_equal (line 7526) | def less_equal(x1, x2, out=None): function roll (line 7560) | def roll(a, shift, axis=None): function logical_and (line 7626) | def logical_and(x1, x2, out=None): function logical_or (line 7663) | def logical_or(x1, x2, out=None): function logical_xor (line 7700) | def logical_xor(x1, x2, out=None): function rot90 (line 7736) | def rot90(m, k=1, axes=(0, 1)): function einsum (line 7782) | def einsum(*operands, **kwargs): function nonzero (line 8021) | def nonzero(a): function percentile (line 8102) | def percentile(a, q, axis=None, out=None, overwrite_input=None, interpol... function median (line 8172) | def median(a, axis=None, out=None, overwrite_input=None, keepdims=False): function quantile (line 8221) | def quantile(a, q, axis=None, out=None, overwrite_input=None, interpolat... function shares_memory (line 8302) | def shares_memory(a, b, max_work=None): function may_share_memory (line 8335) | def may_share_memory(a, b, max_work=None): function interp (line 8376) | def interp(x, xp, fp, left=None, right=None, period=None): # pylint: di... function diff (line 8456) | def diff(a, n=1, axis=-1, prepend=None, append=None): # pylint: disable... function ediff1d (line 8503) | def ediff1d(ary, to_end=None, to_begin=None): function resize (line 8543) | def resize(a, new_shape): function fill_diagonal (line 8595) | def fill_diagonal(a, val, wrap=False): function squeeze (line 8688) | def squeeze(x, axis=None): function nan_to_num (line 8739) | def nan_to_num(x, copy=True, nan=0.0, posinf=None, neginf=None, **kwargs): function isnan (line 8839) | def isnan(x, out=None, **kwargs): function isinf (line 8885) | def isinf(x, out=None, **kwargs): function isposinf (line 8937) | def isposinf(x, out=None, **kwargs): function isneginf (line 8983) | def isneginf(x, out=None, **kwargs): function isfinite (line 9029) | def isfinite(x, out=None, **kwargs): function atleast_1d (line 9083) | def atleast_1d(*arys): function atleast_2d (line 9121) | def atleast_2d(*arys): function atleast_3d (line 9155) | def atleast_3d(*arys): function where (line 9200) | def where(condition, x=None, y=None): # pylint: disable=too-many-return... function polyval (line 9286) | def polyval(p, x): function bincount (line 9338) | def bincount(x, weights=None, minlength=0): function pad (line 9391) | def pad(x, pad_width, mode='constant', **kwargs): # pylint: disable=too-... function prod (line 9525) | def prod(a, axis=None, dtype=None, out=None, keepdims=False, initial=Non... function cumsum (line 9604) | def cumsum(a, axis=None, dtype=None, out=None): function reshape (line 9655) | def reshape(a, newshape, order='C'): function moveaxis (line 9719) | def moveaxis(a, source, destination): function copy (line 9764) | def copy(a): function rollaxis (line 9793) | def rollaxis(a, axis, start=0): function diag (line 9824) | def diag(v, k=0): function diagflat (line 9865) | def diagflat(v, k=0): function diagonal (line 9906) | def diagonal(a, offset=0, axis1=0, axis2=1): function sum (line 9960) | def sum(a, axis=None, dtype=None, out=None, keepdims=None, initial=None,... function bitwise_left_shift (line 10057) | def bitwise_left_shift(x1, x2, out=None): function bitwise_right_shift (line 10096) | def bitwise_right_shift(x1, x2, out=None): FILE: python/mxnet/ndarray/numpy/linalg.py function matrix_rank (line 28) | def matrix_rank(M, tol=None, hermitian=False): function lstsq (line 73) | def lstsq(a, b, rcond='warn'): function pinv (line 147) | def pinv(a, rcond=1e-15, hermitian=False): function norm (line 218) | def norm(x, ord=None, axis=None, keepdims=False): function svd (line 379) | def svd(a): function cholesky (line 453) | def cholesky(a, upper=False): function qr (line 522) | def qr(a, mode='reduced'): function inv (line 581) | def inv(a): function det (line 623) | def det(a): function slogdet (line 667) | def slogdet(a): function solve (line 733) | def solve(a, b): function tensorinv (line 787) | def tensorinv(a, ind=2): function tensorsolve (line 842) | def tensorsolve(a, b, axes=None): function eigvals (line 890) | def eigvals(a): function eigvalsh (line 958) | def eigvalsh(a, UPLO='L'): function eig (line 1017) | def eig(a): function eigh (line 1086) | def eigh(a, UPLO='L'): FILE: python/mxnet/ndarray/numpy/random.py function randint (line 35) | def randint(low, high=None, size=None, dtype=None, device=None, out=None): function uniform (line 101) | def uniform(low=0.0, high=1.0, size=None, dtype=None, device=None, out=N... function normal (line 148) | def normal(loc=0.0, scale=1.0, size=None, dtype=None, device=None, out=N... function lognormal (line 191) | def lognormal(mean=0.0, sigma=1.0, size=None, dtype=None, device=None, o... function logistic (line 228) | def logistic(loc=0.0, scale=1.0, size=None, device=None, out=None): function gumbel (line 266) | def gumbel(loc=0.0, scale=1.0, size=None, device=None, out=None): function multinomial (line 303) | def multinomial(n, pvals, size=None): function rayleigh (line 353) | def rayleigh(scale=1.0, size=None, device=None, out=None): function multivariate_normal (line 387) | def multivariate_normal(mean, cov, size=None, check_valid=None, tol=None): function choice (line 469) | def choice(a, size=None, replace=True, p=None, device=None, out=None): function exponential (line 536) | def exponential(scale=1.0, size=None, device=None, out=None): function weibull (line 569) | def weibull(a, size=None, device=None, out=None): function pareto (line 621) | def pareto(a, size=None, device=None, out=None): function power (line 663) | def power(a, size=None, device=None, out=None): function gamma (line 705) | def gamma(shape, scale=1.0, size=None, dtype=None, device=None, out=None): function beta (line 754) | def beta(a, b, size=None, dtype=None, device=None): function f (line 812) | def f(dfnum, dfden, size=None, device=None): function chisquare (line 877) | def chisquare(df, size=None, dtype=None, device=None): function rand (line 957) | def rand(*size, **kwargs): function shuffle (line 984) | def shuffle(x): function laplace (line 1021) | def laplace(loc=0.0, scale=1.0, size=None, dtype=None, device=None, out=... FILE: python/mxnet/ndarray/numpy_extension/_op.py function softmax (line 37) | def softmax(data, axis=-1, length=None, temperature=None, use_length=Fal... function log_softmax (line 92) | def log_softmax(data, axis=-1, length=None, temperature=None, use_length... function masked_softmax (line 139) | def masked_softmax(data, mask, axis=-1, temperature=1.0, normalize=True): function masked_log_softmax (line 177) | def masked_log_softmax(data, mask, axis=-1, temperature=1.0, normalize=T... function activation (line 216) | def activation(data, act_type='relu', **kwargs): function batch_norm (line 246) | def batch_norm(x, gamma, beta, running_mean, running_var, eps=1e-3, mome... function fully_connected (line 350) | def fully_connected(x, weight, bias=None, num_hidden=None, function pick (line 413) | def pick(data, index, axis=-1, mode='clip', keepdims=False): function convolution (line 485) | def convolution(data=None, weight=None, bias=None, kernel=None, stride=N... function deconvolution (line 619) | def deconvolution(data=None, weight=None, bias=None, kernel=None, stride... function pooling (line 702) | def pooling(data=None, kernel=None, stride=None, pad=None, pool_type="max", function dropout (line 799) | def dropout(data, p=0.5, mode="training", axes=None, cudnn_off=False, **... function one_hot (line 832) | def one_hot(data, depth=None, on_value=1.0, off_value=0.0, dtype="float3... function rnn (line 893) | def rnn(data=None, parameters=None, state=None, state_cell=None, sequenc... function embedding (line 1048) | def embedding(data, weight, input_dim=None, output_dim=None, dtype="floa... function topk (line 1138) | def topk(data, axis=-1, k=1, ret_typ="indices", is_ascend=False, dtype="... function layer_norm (line 1216) | def layer_norm(data=None, gamma=None, beta=None, axis=None, eps=None, ou... function leaky_relu (line 1272) | def leaky_relu(data=None, gamma=None, act_type="leaky", slope=0.25, lowe... function batch_dot (line 1323) | def batch_dot(a, b, transpose_a=False, transpose_b=False, forward_stype=... function broadcast_like (line 1361) | def broadcast_like(lhs, rhs, lhs_axes=None, rhs_axes=None): function arange_like (line 1405) | def arange_like(data, start=0.0, step=1.0, repeat=1, ctx=None, axis=None): function group_norm (line 1452) | def group_norm(data, gamma, beta, num_groups=1, eps=1e-3, output_mean_va... FILE: python/mxnet/ndarray/numpy_extension/control_flow.py function _flatten (line 33) | def _flatten(args, inout_str): function _regroup (line 74) | def _regroup(args, fmt): function _get_unique_subgraph_name (line 117) | def _get_unique_subgraph_name(subgraph_name): function _construct_subgraph (line 128) | def _construct_subgraph(sym_out, sym_states): function foreach (line 153) | def foreach(body, data, init_states, name="foreach"): function while_loop (line 317) | def while_loop(cond, func, loop_vars, max_iterations=None, name="while_l... function cond (line 570) | def cond(pred, then_func, else_func, inputs, name="cond"): FILE: python/mxnet/ndarray/numpy_extension/random.py function bernoulli (line 28) | def bernoulli(prob=None, logit=None, size=None, dtype=None, device=None,... function uniform_n (line 109) | def uniform_n(low=0.0, high=1.0, batch_shape=None, dtype=None, device=No... function normal_n (line 190) | def normal_n(loc=0.0, scale=1.0, batch_shape=None, dtype=None, device=No... FILE: python/mxnet/ndarray/random.py function _random_helper (line 31) | def _random_helper(random, sampler, params, shape, dtype, ctx, out, kwar... function uniform (line 54) | def uniform(low=0, high=1, shape=_Null, dtype=_Null, ctx=None, out=None,... function normal (line 113) | def normal(loc=0, scale=1, shape=_Null, dtype=_Null, ctx=None, out=None,... function randn (line 170) | def randn(*shape, **kwargs): function poisson (line 229) | def poisson(lam=1, shape=_Null, dtype=_Null, ctx=None, out=None, **kwargs): function exponential (line 279) | def exponential(scale=1, shape=_Null, dtype=_Null, ctx=None, out=None, *... function gamma (line 332) | def gamma(alpha=1, beta=1, shape=_Null, dtype=_Null, ctx=None, out=None,... function binomial (line 386) | def binomial(n=1, p=0.5, shape=_Null, dtype=_Null, ctx=None, out=None, *... function negative_binomial (line 439) | def negative_binomial(k=1, p=1, shape=_Null, dtype=_Null, ctx=None, function generalized_negative_binomial (line 495) | def generalized_negative_binomial(mu=1, alpha=1, shape=_Null, dtype=_Nul... function categorical (line 552) | def categorical(data, shape=_Null, get_prob=False, out=None, dtype='int3... function multinomial (line 617) | def multinomial(n=[1], p=[[1.0]], shape=_Null, dtype='float32', ctx=None... function shuffle (line 673) | def shuffle(data, **kwargs): function randint (line 712) | def randint(low, high, shape=_Null, dtype=_Null, ctx=None, out=None, **k... FILE: python/mxnet/ndarray/register.py function _verify_all_np_ndarrays (line 31) | def _verify_all_np_ndarrays(op_name, func_name, args, out): function _verify_all_legacy_ndarrays (line 75) | def _verify_all_legacy_ndarrays(op_name, func_name, args, out): function _generate_ndarray_function_code (line 116) | def _generate_ndarray_function_code(handle, op_name, func_name, signatur... function _make_ndarray_function (line 258) | def _make_ndarray_function(handle, name, func_name): FILE: python/mxnet/ndarray/sparse.py function _new_alloc_handle (line 70) | def _new_alloc_handle(stype, shape, ctx, delay_alloc, dtype, aux_types, ... class BaseSparseNDArray (line 120) | class BaseSparseNDArray(NDArray): method __repr__ (line 126) | def __repr__(self): method __add__ (line 132) | def __add__(self, other): method __sub__ (line 135) | def __sub__(self, other): method __mul__ (line 138) | def __mul__(self, other): method __div__ (line 141) | def __div__(self, other): method __iadd__ (line 144) | def __iadd__(self, other): method __isub__ (line 147) | def __isub__(self, other): method __imul__ (line 150) | def __imul__(self, other): method __idiv__ (line 153) | def __idiv__(self, other): method __itruediv__ (line 156) | def __itruediv__(self, other): method _sync_copyfrom (line 159) | def _sync_copyfrom(self, source_array): method _at (line 162) | def _at(self, idx): method _slice (line 165) | def _slice(self, start, stop): method reshape (line 168) | def reshape(self, *shape, **kwargs): method size (line 172) | def size(self): method _aux_type (line 176) | def _aux_type(self, i): method _num_aux (line 189) | def _num_aux(self): method _aux_types (line 195) | def _aux_types(self): method asnumpy (line 204) | def asnumpy(self): method astype (line 209) | def astype(self, dtype, copy=True): method copyto (line 238) | def copyto(self, other): method check_format (line 265) | def check_format(self, full_check=True): method _data (line 276) | def _data(self): method _aux_data (line 287) | def _aux_data(self, i): class CSRNDArray (line 300) | class CSRNDArray(BaseSparseNDArray): method __reduce__ (line 327) | def __reduce__(self): method __iadd__ (line 330) | def __iadd__(self, other): method __isub__ (line 334) | def __isub__(self, other): method __imul__ (line 338) | def __imul__(self, other): method __idiv__ (line 342) | def __idiv__(self, other): method __itruediv__ (line 346) | def __itruediv__(self, other): method __getitem__ (line 350) | def __getitem__(self, key): method __setitem__ (line 398) | def __setitem__(self, key, value): method indices (line 458) | def indices(self): method indptr (line 470) | def indptr(self): method data (line 482) | def data(self): method indices (line 494) | def indices(self, indices): method indptr (line 498) | def indptr(self, indptr): method data (line 502) | def data(self, data): method tostype (line 506) | def tostype(self, stype): method copyto (line 520) | def copyto(self, other): method asscipy (line 552) | def asscipy(self): class RowSparseNDArray (line 574) | class RowSparseNDArray(BaseSparseNDArray): method __reduce__ (line 612) | def __reduce__(self): method __iadd__ (line 615) | def __iadd__(self, other): method __isub__ (line 619) | def __isub__(self, other): method __imul__ (line 623) | def __imul__(self, other): method __idiv__ (line 627) | def __idiv__(self, other): method __itruediv__ (line 631) | def __itruediv__(self, other): method __getitem__ (line 635) | def __getitem__(self, key): method __setitem__ (line 663) | def __setitem__(self, key, value): method indices (line 722) | def indices(self): method data (line 734) | def data(self): method indices (line 746) | def indices(self, indices): method data (line 750) | def data(self, data): method tostype (line 753) | def tostype(self, stype): method copyto (line 767) | def copyto(self, other): method retain (line 799) | def retain(self, *args, **kwargs): function _prepare_src_array (line 809) | def _prepare_src_array(source_array, dtype): function _prepare_default_dtype (line 821) | def _prepare_default_dtype(src_array, dtype): function _check_shape (line 833) | def _check_shape(s1, s2): function csr_matrix (line 838) | def csr_matrix(arg1, shape=None, ctx=None, dtype=None): function _csr_matrix_from_definition (line 994) | def _csr_matrix_from_definition(data, indices, indptr, shape=None, ctx=N... function row_sparse_array (line 1036) | def row_sparse_array(arg1, shape=None, ctx=None, dtype=None): function _row_sparse_ndarray_from_definition (line 1158) | def _row_sparse_ndarray_from_definition(data, indices, shape=None, ctx=N... function _ndarray_cls (line 1193) | def _ndarray_cls(handle, writable=True, stype=_STORAGE_TYPE_UNDEFINED): function add (line 1209) | def add(lhs, rhs): function subtract (line 1281) | def subtract(lhs, rhs): function multiply (line 1353) | def multiply(lhs, rhs): function divide (line 1437) | def divide(lhs, rhs): function zeros (line 1523) | def zeros(stype, shape, ctx=None, dtype=None, **kwargs): function empty (line 1563) | def empty(stype, shape, ctx=None, dtype=None): function array (line 1595) | def array(source_array, ctx=None, dtype=None): FILE: python/mxnet/ndarray/utils.py function zeros (line 40) | def zeros(shape, ctx=None, dtype=None, stype=None, **kwargs): function empty (line 72) | def empty(shape, ctx=None, dtype=None, stype=None): function array (line 108) | def array(source_array, ctx=None, dtype=None): function load (line 149) | def load(fname): function load_frombuffer (line 185) | def load_frombuffer(buf): function save (line 222) | def save(fname, data): FILE: python/mxnet/ndarray_doc.py class NDArrayDoc (line 26) | class NDArrayDoc(object): function _build_doc (line 30) | def _build_doc(func_name, FILE: python/mxnet/notebook/__init__.py class Bokeh_Failed_To_Import (line 25) | class Bokeh_Failed_To_Import: pass FILE: python/mxnet/notebook/callback.py class Datetime_Failed_To_Import (line 25) | class Datetime_Failed_To_Import: pass class Defaultdict_Failed_To_Import (line 36) | class Defaultdict_Failed_To_Import: pass class Pandas_Failed_To_Import (line 42) | class Pandas_Failed_To_Import: pass function _add_new_columns (line 49) | def _add_new_columns(dataframe, metrics): function _extend (line 65) | def _extend(baseData, newData): class PandasLogger (line 71) | class PandasLogger(object): method __init__ (line 85) | def __init__(self, batch_size, frequent=50): method train_df (line 98) | def train_df(self): method eval_df (line 106) | def eval_df(self): method epoch_df (line 113) | def epoch_df(self): method all_dataframes (line 120) | def all_dataframes(self): method elapsed (line 125) | def elapsed(self): method append_metrics (line 130) | def append_metrics(self, metrics, df_name): method train_cb (line 144) | def train_cb(self, param): method eval_cb (line 150) | def eval_cb(self, param): method _process_batch (line 155) | def _process_batch(self, param, dataframe): method epoch_cb (line 181) | def epoch_cb(self): method callback_args (line 192) | def callback_args(self): class LiveBokehChart (line 204) | class LiveBokehChart(object): method __init__ (line 212) | def __init__(self, pandas_logger, metric_name, display_freq=10, method setup_chart (line 225) | def setup_chart(self): method update_chart_data (line 230) | def update_chart_data(self): method interval_elapsed (line 235) | def interval_elapsed(self): method _push_render (line 243) | def _push_render(self): method _do_update (line 249) | def _do_update(self): method batch_cb (line 255) | def batch_cb(self, param): method eval_cb (line 261) | def eval_cb(self, param): method callback_args (line 267) | def callback_args(self): class LiveTimeSeries (line 278) | class LiveTimeSeries(LiveBokehChart): method __init__ (line 281) | def __init__(self, **fig_params): method setup_chart (line 286) | def setup_chart(self): method elapsed (line 293) | def elapsed(self): method update_chart_data (line 298) | def update_chart_data(self, value): class LiveLearningCurve (line 304) | class LiveLearningCurve(LiveBokehChart): method __init__ (line 308) | def __init__(self, metric_name, display_freq=10, frequent=50): method setup_chart (line 317) | def setup_chart(self): method _do_update (line 345) | def _do_update(self): method batch_cb (line 349) | def batch_cb(self, param): method eval_cb (line 355) | def eval_cb(self, param): method _process_batch (line 360) | def _process_batch(self, param, df_name): method update_chart_data (line 378) | def update_chart_data(self): function args_wrapper (line 392) | def args_wrapper(*args): FILE: python/mxnet/numpy/arrayprint.py function set_printoptions (line 28) | def set_printoptions(precision=None, threshold=None, **kwarg): FILE: python/mxnet/numpy/fallback.py function get_func (line 117) | def get_func(obj, doc): FILE: python/mxnet/numpy/function_base.py function meshgrid (line 25) | def meshgrid(*xi, **kwargs): FILE: python/mxnet/numpy/io.py function genfromtxt (line 28) | def genfromtxt(*args, **kwargs): FILE: python/mxnet/numpy/linalg.py function matrix_rank (line 35) | def matrix_rank(M, rtol=None, hermitian=False): function matrix_transpose (line 83) | def matrix_transpose(a): function trace (line 124) | def trace(a, offset=0): function tensordot (line 176) | def tensordot(a, b, axes=2): function diagonal (line 227) | def diagonal(a, offset=0): function cross (line 275) | def cross(a, b, axis=-1): function outer (line 347) | def outer(a, b): function vecdot (line 385) | def vecdot(a, b, axis=None): function lstsq (line 438) | def lstsq(a, b, rcond='warn'): function pinv (line 510) | def pinv(a, rtol=None, hermitian=False): function norm (line 584) | def norm(x, ord=None, axis=None, keepdims=False): function vector_norm (line 649) | def vector_norm(x, ord=None, axis=None, keepdims=False): function matrix_norm (line 694) | def matrix_norm(x, ord='fro', axis=(-2, -1), keepdims=False): function svd (line 729) | def svd(a): function svdvals (line 801) | def svdvals(a): function cholesky (line 826) | def cholesky(a, upper=False): function qr (line 895) | def qr(a, mode='reduced'): function inv (line 957) | def inv(a): function det (line 999) | def det(a): function slogdet (line 1043) | def slogdet(a): function solve (line 1109) | def solve(a, b): function tensorinv (line 1163) | def tensorinv(a, ind=2): function tensorsolve (line 1218) | def tensorsolve(a, b, axes=None): function eigvals (line 1266) | def eigvals(a): function eigvalsh (line 1336) | def eigvalsh(a, upper=False): function eig (line 1398) | def eig(a): function eigh (line 1466) | def eigh(a, upper=False): FILE: python/mxnet/numpy/multiarray.py function _int64_enabled (line 109) | def _int64_enabled(): function _new_alloc_handle (line 117) | def _new_alloc_handle(shape, device, delay_alloc, dtype=mx_real_t): # p... function _reshape_view (line 158) | def _reshape_view(a, *shape): # pylint: disable=redefined-outer-name function _as_mx_np_array (line 186) | def _as_mx_np_array(object, device=None, zero_copy=False): function _as_onp_array (line 204) | def _as_onp_array(object, cur_device=None): function _np_ndarray_cls (line 237) | def _np_ndarray_cls(handle, writable=True, stype=0): function wrap_mxnp_np_ufunc (line 253) | def wrap_mxnp_np_ufunc(func): class ndarray (line 275) | class ndarray(NDArray): # pylint: disable=invalid-name method __array_ufunc__ (line 321) | def __array_ufunc__(self, ufunc, method, *inputs, **kwargs): # pylint... method __array_function__ (line 378) | def __array_function__(self, func, types, args, kwargs): # pylint: di... method __array_namespace__ (line 418) | def __array_namespace__(self, api_version=None): method __dlpack__ (line 446) | def __dlpack__(self, stream=None): method __dlpack_device__ (line 475) | def __dlpack_device__(self): method _get_np_basic_indexing (line 485) | def _get_np_basic_indexing(self, key): method _get_np_empty_tuple_indexing (line 561) | def _get_np_empty_tuple_indexing(self, key): method _get_np_advanced_indexing (line 574) | def _get_np_advanced_indexing(self, key): method _set_np_advanced_indexing (line 590) | def _set_np_advanced_indexing(self, key, value): method _get_np_boolean_indexing (line 602) | def _get_np_boolean_indexing(self, key, ndim, shape): method _set_np_boolean_indexing (line 627) | def _set_np_boolean_indexing(self, key, value): method __getitem__ (line 644) | def __getitem__(self, key): method __setitem__ (line 916) | def __setitem__(self, key, value): method _prepare_value_nd (line 1032) | def _prepare_value_nd(self, value, bcast_shape, squeeze_axes=None): method __add__ (line 1081) | def __add__(self, other): method __iadd__ (line 1086) | def __iadd__(self, other): method __radd__ (line 1093) | def __radd__(self, other): method __invert__ (line 1097) | def __invert__(self): method __and__ (line 1102) | def __and__(self, other): method __rand__ (line 1107) | def __rand__(self, other): method __or__ (line 1112) | def __or__(self, other): method __ror__ (line 1117) | def __ror__(self, other): method __xor__ (line 1122) | def __xor__(self, other): method __rxor__ (line 1127) | def __rxor__(self, other): method __lshift__ (line 1132) | def __lshift__(self, other): method __rshift__ (line 1137) | def __rshift__(self, other): method __iand__ (line 1142) | def __iand__(self, other): method __ior__ (line 1147) | def __ior__(self, other): method __ixor__ (line 1152) | def __ixor__(self, other): method __ilshift__ (line 1157) | def __ilshift__(self, other): method __irshift__ (line 1162) | def __irshift__(self, other): method __rlshift__ (line 1167) | def __rlshift__(self, other): method __rrshift__ (line 1172) | def __rrshift__(self, other): method __round__ (line 1176) | def __round__(self, n=0): method __abs__ (line 1180) | def __abs__(self): method __ceil__ (line 1184) | def __ceil__(self): method __floor__ (line 1188) | def __floor__(self): method __trunc__ (line 1192) | def __trunc__(self): method __sub__ (line 1197) | def __sub__(self, other): method __isub__ (line 1202) | def __isub__(self, other): method __rsub__ (line 1209) | def __rsub__(self, other): method __mul__ (line 1214) | def __mul__(self, other): method __floordiv__ (line 1219) | def __floordiv__(self, other): method __ifloordiv__ (line 1224) | def __ifloordiv__(self, other): method __rfloordiv__ (line 1231) | def __rfloordiv__(self, other): method __neg__ (line 1235) | def __neg__(self): method __pos__ (line 1239) | def __pos__(self): method __imul__ (line 1244) | def __imul__(self, other): method __rmul__ (line 1251) | def __rmul__(self, other): method __div__ (line 1256) | def __div__(self, other): method __rdiv__ (line 1261) | def __rdiv__(self, other): method __idiv__ (line 1266) | def __idiv__(self, other): method __truediv__ (line 1271) | def __truediv__(self, other): method __rtruediv__ (line 1276) | def __rtruediv__(self, other): method __itruediv__ (line 1281) | def __itruediv__(self, other): method __mod__ (line 1286) | def __mod__(self, other): method __rmod__ (line 1291) | def __rmod__(self, other): method __imod__ (line 1296) | def __imod__(self, other): method __pow__ (line 1301) | def __pow__(self, other): method __rpow__ (line 1306) | def __rpow__(self, other): method __ipow__ (line 1311) | def __ipow__(self, other): method __eq__ (line 1316) | def __eq__(self, other): method __hash__ (line 1320) | def __hash__(self): method __ne__ (line 1324) | def __ne__(self, other): method __gt__ (line 1329) | def __gt__(self, other): method __ge__ (line 1334) | def __ge__(self, other): method __lt__ (line 1339) | def __lt__(self, other): method __le__ (line 1344) | def __le__(self, other): method __matmul__ (line 1349) | def __matmul__(self, other): method __rmatmul__ (line 1354) | def __rmatmul__(self, other): method __imatmul__ (line 1359) | def __imatmul__(self, other): method __bool__ (line 1363) | def __bool__(self): method __index__ (line 1377) | def __index__(self): method __float__ (line 1382) | def __float__(self): method __int__ (line 1388) | def __int__(self): method __len__ (line 1394) | def __len__(self): method __reduce__ (line 1401) | def __reduce__(self): method item (line 1404) | def item(self, *args): method nonzero (line 1427) | def nonzero(self): method T (line 1440) | def T(self): method mT (line 1451) | def mT(self): method all (line 1458) | def all(self, axis=None, out=None, keepdims=False): method any (line 1461) | def any(self, axis=None, out=None, keepdims=False): method as_nd_ndarray (line 1464) | def as_nd_ndarray(self): method as_np_ndarray (line 1470) | def as_np_ndarray(self): method __repr__ (line 1476) | def __repr__(self): method __str__ (line 1544) | def __str__(self): method __format__ (line 1552) | def __format__(self, fmt): method attach_grad (line 1561) | def attach_grad(self, grad_req='write'): # pylint: disable=arguments-... method drop_grad (line 1580) | def drop_grad(self): method grad (line 1586) | def grad(self): method detach (line 1594) | def detach(self): method astype (line 1600) | def astype(self, dtype, order='K', casting='unsafe', subok=True, copy=... method copyto (line 1662) | def copyto(self, other): method asscalar (line 1705) | def asscalar(self): method argmax (line 1708) | def argmax(self, axis=None, out=None, keepdims=False): # pylint: disa... method as_in_context (line 1713) | def as_in_context(self, context): method as_in_ctx (line 1719) | def as_in_ctx(self, ctx): method ctx (line 1726) | def ctx(self): method to_device (line 1732) | def to_device(self, device): method device (line 1753) | def device(self): method context (line 1775) | def context(self): method copy (line 1780) | def copy(self, order='C'): # pylint: disable=arguments-differ method dot (line 1802) | def dot(self, b, out=None): method reshape (line 1807) | def reshape(self, *args, **kwargs): # pylint: disable=arguments-differ method reshape_like (line 1835) | def reshape_like(self, *args, **kwargs): method reshape_view (line 1843) | def reshape_view(self, *shape, **kwargs): # pylint: disable=redefined... method zeros_like (line 1849) | def zeros_like(self, *args, **kwargs): method ones_like (line 1857) | def ones_like(self, *args, **kwargs): method broadcast_axes (line 1865) | def broadcast_axes(self, *args, **kwargs): method repeat (line 1873) | def repeat(self, repeats, axis=None): # pylint: disable=arguments-differ method pad (line 1877) | def pad(self, *args, **kwargs): method swapaxes (line 1885) | def swapaxes(self, axis1, axis2): # pylint: disable=arguments-differ method split (line 1891) | def split(self, *args, **kwargs): method split_v2 (line 1899) | def split_v2(self, *args, **kwargs): method slice (line 1907) | def slice(self, *args, **kwargs): method slice_axis (line 1915) | def slice_axis(self, *args, **kwargs): method slice_like (line 1923) | def slice_like(self, *args, **kwargs): method slice_assign_scalar (line 1931) | def slice_assign_scalar(self, value, begin, end, step): method slice_assign (line 1968) | def slice_assign(self, rhs, begin, end, step): method take (line 2007) | def take(self, indices, axis=None, mode='raise'): # pylint: disable=a... method one_hot (line 2015) | def one_hot(self, *args, **kwargs): method pick (line 2023) | def pick(self, *args, **kwargs): method sort (line 2031) | def sort(self, axis=-1, descending=False, stable=True): # pylint: dis... method topk (line 2039) | def topk(self, *args, **kwargs): method argsort (line 2047) | def argsort(self, axis=-1, descending=False, stable=True): # pylint: ... method argmax_channel (line 2055) | def argmax_channel(self, *args, **kwargs): method argmin (line 2063) | def argmin(self, axis=None, out=None, keepdims=False): # pylint: disa... method clip (line 2068) | def clip(self, min=None, max=None, out=None): # pylint: disable=argum... method abs (line 2074) | def abs(self, *args, **kwargs): method sign (line 2082) | def sign(self, *args, **kwargs): method flatten (line 2090) | def flatten(self, order='C'): # pylint: disable=arguments-differ method shape_array (line 2094) | def shape_array(self, *args, **kwargs): method size_array (line 2102) | def size_array(self, *args, **kwargs): method expand_dims (line 2110) | def expand_dims(self, *args, **kwargs): # pylint: disable=arguments-d... method tile (line 2118) | def tile(self, reps): # pylint: disable=arguments-differ method transpose (line 2123) | def transpose(self, *axes): # pylint: disable=arguments-differ method flip (line 2134) | def flip(self, *args, **kwargs): method depth_to_space (line 2142) | def depth_to_space(self, *args, **kwargs): method space_to_depth (line 2150) | def space_to_depth(self, *args, **kwargs): method diag (line 2158) | def diag(self, k=0, **kwargs): method diagonal (line 2166) | def diagonal(self, offset=0, axis1=0, axis2=1): # pylint: disable=arg... method sum (line 2176) | def sum(self, axis=None, dtype=None, out=None, keepdims=False): # pyl... method nansum (line 2180) | def nansum(self, *args, **kwargs): method prod (line 2188) | def prod(self, axis=None, dtype=None, out=None, keepdims=False): # py... method nanprod (line 2192) | def nanprod(self, *args, **kwargs): method mean (line 2200) | def mean(self, axis=None, dtype=None, out=None, keepdims=False): # py... method std (line 2207) | def std(self, axis=None, dtype=None, out=None, correction=0, keepdims=... method var (line 2212) | def var(self, axis=None, dtype=None, out=None, correction=0, keepdims=... method cumsum (line 2217) | def cumsum(self, axis=None, dtype=None, out=None): method tolist (line 2221) | def tolist(self): method max (line 2224) | def max(self, axis=None, out=None, keepdims=False): # pylint: disable... method min (line 2228) | def min(self, axis=None, out=None, keepdims=False): # pylint: disable... method norm (line 2236) | def norm(self, *args, **kwargs): method round (line 2244) | def round(self, decimals=0, out=None, **kwargs): # pylint: disable=arg... method rint (line 2252) | def rint(self, *args, **kwargs): method fix (line 2260) | def fix(self, *args, **kwargs): method floor (line 2268) | def floor(self, *args, **kwargs): method ceil (line 2276) | def ceil(self, *args, **kwargs): method trunc (line 2284) | def trunc(self, *args, **kwargs): method sin (line 2292) | def sin(self, *args, **kwargs): method cos (line 2300) | def cos(self, *args, **kwargs): method tan (line 2308) | def tan(self, *args, **kwargs): method arcsin (line 2316) | def arcsin(self, *args, **kwargs): method arccos (line 2324) | def arccos(self, *args, **kwargs): method arctan (line 2332) | def arctan(self, *args, **kwargs): method degrees (line 2340) | def degrees(self, *args, **kwargs): method radians (line 2348) | def radians(self, *args, **kwargs): method sinh (line 2356) | def sinh(self, *args, **kwargs): method cosh (line 2364) | def cosh(self, *args, **kwargs): method tanh (line 2372) | def tanh(self, *args, **kwargs): method arcsinh (line 2380) | def arcsinh(self, *args, **kwargs): method arccosh (line 2388) | def arccosh(self, *args, **kwargs): method arctanh (line 2396) | def arctanh(self, *args, **kwargs): method exp (line 2404) | def exp(self, *args, **kwargs): method expm1 (line 2412) | def expm1(self, *args, **kwargs): method log (line 2420) | def log(self, *args, **kwargs): method log10 (line 2428) | def log10(self, *args, **kwargs): method log2 (line 2436) | def log2(self, *args, **kwargs): method log1p (line 2444) | def log1p(self, *args, **kwargs): method log_sigmoid (line 2452) | def log_sigmoid(self, *args, **kwargs): method sqrt (line 2460) | def sqrt(self, *args, **kwargs): method rsqrt (line 2468) | def rsqrt(self, *args, **kwargs): method cbrt (line 2476) | def cbrt(self, *args, **kwargs): method rcbrt (line 2484) | def rcbrt(self, *args, **kwargs): method square (line 2492) | def square(self, *args, **kwargs): method reciprocal (line 2500) | def reciprocal(self, *args, **kwargs): method relu (line 2508) | def relu(self, *args, **kwargs): method sigmoid (line 2516) | def sigmoid(self, *args, **kwargs): method softmax (line 2524) | def softmax(self, *args, **kwargs): method log_softmax (line 2532) | def log_softmax(self, *args, **kwargs): method softmin (line 2540) | def softmin(self, *args, **kwargs): method mish (line 2548) | def mish(self, *args, **kwargs): method squeeze (line 2556) | def squeeze(self, axis=None): # pylint: disable=arguments-differ method broadcast_to (line 2560) | def broadcast_to(self, shape): # pylint: disable=redefined-outer-name method broadcast_like (line 2563) | def broadcast_like(self, other): method _full (line 2566) | def _full(self, value): method _scatter_set_nd (line 2574) | def _scatter_set_nd(self, value_nd, indices): method shape (line 2584) | def shape(self): method ndim (line 2614) | def ndim(self): method size (line 2619) | def size(self): method dtype (line 2624) | def dtype(self): method tostype (line 2643) | def tostype(self, stype): function empty (line 2649) | def empty(shape, dtype=None, order='C', device=None): # pylint: disable... function array (line 2699) | def array(object, dtype=None, device=None): function shape (line 2777) | def shape(a): function zeros (line 2812) | def zeros(shape, dtype=None, order='C', device=None): # pylint: disable... function ones (line 2857) | def ones(shape, dtype=None, order='C', device=None): # pylint: disable=... function broadcast_to (line 2905) | def broadcast_to(array, shape): # pylint: disable=redefined-outer-name function full (line 2935) | def full(shape, fill_value, dtype=None, order='C', device=None, out=None): function empty_like (line 2996) | def empty_like(prototype, dtype=None, device=None, order='C', subok=Fals... function all (line 3063) | def all(a, axis=None, out=None, keepdims=False): function any (line 3112) | def any(a, axis=None, out=None, keepdims=False): function identity (line 3168) | def identity(n, dtype=None, device=None): function take (line 3207) | def take(a, indices, axis=None, mode='raise', out=None): function unique (line 3286) | def unique(ar, return_index=False, return_inverse=False, return_counts=F... function add (line 3391) | def add(x1, x2, out=None, **kwargs): function subtract (line 3435) | def subtract(x1, x2, out=None, **kwargs): function multiply (line 3477) | def multiply(x1, x2, out=None, **kwargs): function divide (line 3521) | def divide(x1, x2, out=None, **kwargs): function true_divide (line 3561) | def true_divide(x1, x2, out=None): function floor_divide (line 3607) | def floor_divide(x1, x2, out=None): function mod (line 3651) | def mod(x1, x2, out=None, **kwargs): function fmod (line 3683) | def fmod(x1, x2, out=None, **kwargs): function matmul (line 3715) | def matmul(a, b, out=None, **kwargs): function remainder (line 3817) | def remainder(x1, x2, out=None, **kwargs): function power (line 3850) | def power(x1, x2, out=None, **kwargs): function gcd (line 3956) | def gcd(x1, x2, out=None, **kwargs): function lcm (line 3994) | def lcm(x1, x2, out=None, **kwargs): function sin (line 4032) | def sin(x, out=None, **kwargs): function cos (line 4067) | def cos(x, out=None, **kwargs): function sinh (line 4105) | def sinh(x, out=None, **kwargs): function cosh (line 4144) | def cosh(x, out=None, **kwargs): function tanh (line 4178) | def tanh(x, out=None, **kwargs): function log10 (line 4225) | def log10(x, out=None, **kwargs): function sqrt (line 4259) | def sqrt(x, out=None, **kwargs): function cbrt (line 4294) | def cbrt(x, out=None, **kwargs): function abs (line 4323) | def abs(x, out=None, **kwargs): function fabs (line 4353) | def fabs(x, out=None, **kwargs): function absolute (line 4388) | def absolute(x, out=None, **kwargs): function exp (line 4418) | def exp(x, out=None, **kwargs): function expm1 (line 4450) | def expm1(x, out=None, **kwargs): function arcsin (line 4482) | def arcsin(x, out=None, **kwargs): function arccos (line 4599) | def arccos(x, out=None, **kwargs): function arctan (line 4679) | def arctan(x, out=None, **kwargs): function sign (line 4772) | def sign(x, out=None, **kwargs): function log (line 4823) | def log(x, out=None, **kwargs): function rint (line 4877) | def rint(x, out=None, **kwargs): function log2 (line 4915) | def log2(x, out=None, **kwargs): function log1p (line 4954) | def log1p(x, out=None, **kwargs): function degrees (line 5000) | def degrees(x, out=None, **kwargs): function rad2deg (line 5050) | def rad2deg(x, out=None, **kwargs): function radians (line 5086) | def radians(x, out=None, **kwargs): function deg2rad (line 5126) | def deg2rad(x, out=None, **kwargs): function reciprocal (line 5162) | def reciprocal(x, out=None, **kwargs): function square (line 5208) | def square(x, out=None, **kwargs): function negative (line 5250) | def negative(x, out=None, **kwargs): function positive (line 5280) | def positive(x, out=None, **kwargs): function fix (line 5312) | def fix(x, out=None, **kwargs): function tan (line 5339) | def tan(x, out=None, **kwargs): function ceil (line 5370) | def ceil(x, out=None, **kwargs): function floor (line 5409) | def floor(x, out=None, **kwargs): function bitwise_invert (line 5447) | def bitwise_invert(x, out=None, **kwargs): function invert (line 5500) | def invert(x, out=None, **kwargs): function bitwise_not (line 5552) | def bitwise_not(x, out=None, **kwargs): function trunc (line 5605) | def trunc(x, out=None, **kwargs): function logical_not (line 5644) | def logical_not(x, out=None, **kwargs): function arcsinh (line 5684) | def arcsinh(x, out=None, **kwargs): function arccosh (line 5781) | def arccosh(x, out=None, **kwargs): function arctanh (line 5877) | def arctanh(x, out=None, **kwargs): function argsort (line 5974) | def argsort(a, axis=-1, descending=False, stable=True): function sort (line 6055) | def sort(a, axis=-1, descending=False, stable=True): function tensordot (line 6105) | def tensordot(a, b, axes=2): function histogram (line 6166) | def histogram(a, bins=10, range=None, normed=None, weights=None, density... function eye (line 6204) | def eye(N, M=None, k=0, dtype=None, device=None, **kwargs): function linspace (line 6249) | def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=No... function logspace (line 6341) | def logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None, ... function expand_dims (line 6419) | def expand_dims(a, axis): function tile (line 6472) | def tile(A, reps): function trace (line 6540) | def trace(a, offset=0, axis1=0, axis2=1, out=None): function transpose (line 6587) | def transpose(a, axes=None): function permute_dims (line 6630) | def permute_dims(a, axes=None): function repeat (line 6670) | def repeat(a, repeats, axis=None): function tril (line 6713) | def tril(m, k=0): function tri (line 6750) | def tri(N, M=None, k=0, dtype=None, device=None): # pylint: disable=r... function triu_indices (line 6786) | def triu_indices(n, k=0, m=None, device=None): # pylint: disable=rede... function triu_indices_from (line 6849) | def triu_indices_from(arr, k=0): function tril_indices (line 6871) | def tril_indices(n, k=0, m=None): function triu (line 6950) | def triu(m, k=0): function arange (line 6976) | def arange(start, stop=None, step=1, dtype=None, device=None): function split (line 7042) | def split(ary, indices_or_sections, axis=0): function array_split (line 7101) | def array_split(ary, indices_or_sections, axis=0): function vsplit (line 7154) | def vsplit(ary, indices_or_sections): function dsplit (line 7227) | def dsplit(ary, indices_or_sections): function concat (line 7300) | def concat(seq, axis=0, out=None): function concatenate (line 7357) | def concatenate(seq, axis=0, out=None): function append (line 7409) | def append(arr, values, axis=None): # pylint: disable=redefined-outer-name function stack (line 7449) | def stack(arrays, axis=0, out=None): function vstack (line 7501) | def vstack(arrays, out=None): function row_stack (line 7546) | def row_stack(arrays): function column_stack (line 7585) | def column_stack(tup): function hstack (line 7621) | def hstack(arrays): function dstack (line 7660) | def dstack(arrays): function maximum (line 7705) | def maximum(x1, x2, out=None, **kwargs): function fmax (line 7734) | def fmax(x1, x2, out=None, **kwargs): function minimum (line 7763) | def minimum(x1, x2, out=None, **kwargs): function fmin (line 7792) | def fmin(x1, x2, out=None, **kwargs): function max (line 7820) | def max(a, axis=None, out=None, keepdims=False): function min (line 7885) | def min(a, axis=None, out=None, keepdims=False): function swapaxes (line 7947) | def swapaxes(a, axis1, axis2): function clip (line 7991) | def clip(a, a_min, a_max, out=None): function argmax (line 8047) | def argmax(a, axis=None, out=None, keepdims=False): function argmin (line 8125) | def argmin(a, axis=None, out=None, keepdims=False): function amax (line 8203) | def amax(a, axis=None, out=None, keepdims=False): function amin (line 8268) | def amin(a, axis=None, out=None, keepdims=False): function average (line 8330) | def average(a, axis=None, weights=None, returned=False, out=None): function mean (line 8424) | def mean(a, axis=None, dtype=None, out=None, keepdims=False): # pylint:... function std (line 8490) | def std(a, axis=None, dtype=None, out=None, correction=0, keepdims=False... function delete (line 8558) | def delete(arr, obj, axis=None): function var (line 8609) | def var(a, axis=None, dtype=None, out=None, correction=0, keepdims=False... function indices (line 8683) | def indices(dimensions, dtype=None, device=None): function copysign (line 8746) | def copysign(x1, x2, out=None, **kwargs): function ravel (line 8795) | def ravel(x, order='C'): function unravel_index (line 8841) | def unravel_index(indices, shape, order='C'): # pylint: disable=redefine... function flatnonzero (line 8872) | def flatnonzero(a): function diag_indices_from (line 8912) | def diag_indices_from(arr): function hanning (line 8954) | def hanning(M, dtype=None, device=None): function hamming (line 9037) | def hamming(M, dtype=None, device=None): function blackman (line 9118) | def blackman(M, dtype=None, device=None): function flip (line 9195) | def flip(m, axis=None, out=None): function flipud (line 9257) | def flipud(m): function fliplr (line 9310) | def fliplr(m): function around (line 9359) | def around(x, decimals=0, out=None, **kwargs): function round (line 9410) | def round(x, decimals=0, out=None, **kwargs): function round_ (line 9423) | def round_(x, decimals=0, out=None, **kwargs): function arctan2 (line 9437) | def arctan2(x1, x2, out=None, **kwargs): function hypot (line 9617) | def hypot(x1, x2, out=None, **kwargs): function bitwise_and (line 9665) | def bitwise_and(x1, x2, out=None, **kwargs): function bitwise_xor (line 9705) | def bitwise_xor(x1, x2, out=None, **kwargs): function bitwise_or (line 9743) | def bitwise_or(x1, x2, out=None, **kwargs): function ldexp (line 9781) | def ldexp(x1, x2, out=None, **kwargs): function logaddexp (line 9820) | def logaddexp(x1, x2, out=None, **kwargs): function vdot (line 9859) | def vdot(a, b): function inner (line 9900) | def inner(a, b): function outer (line 9966) | def outer(a, b): function cross (line 10019) | def cross(a, b, axisa=-1, axisb=-1, axisc=-1, axis=None): # pylint: disa... function kron (line 10127) | def kron(a, b): function equal (line 10177) | def equal(x1, x2, out=None): function not_equal (line 10209) | def not_equal(x1, x2, out=None): function greater (line 10241) | def greater(x1, x2, out=None): function less (line 10273) | def less(x1, x2, out=None): function logical_and (line 10306) | def logical_and(x1, x2, out=None): function logical_or (line 10341) | def logical_or(x1, x2, out=None): function logical_xor (line 10376) | def logical_xor(x1, x2, out=None): function greater_equal (line 10410) | def greater_equal(x1, x2, out=None): function less_equal (line 10442) | def less_equal(x1, x2, out=None): function roll (line 10474) | def roll(a, shift, axis=None): function rot90 (line 10540) | def rot90(m, k=1, axes=(0, 1)): function hsplit (line 10589) | def hsplit(ary, indices_or_sections): function einsum (line 10675) | def einsum(*operands, **kwargs): function insert (line 10909) | def insert(arr, obj, values, axis=None): function nonzero (line 10990) | def nonzero(a): function percentile (line 11070) | def percentile(a, q, axis=None, out=None, overwrite_input=None, interpol... function median (line 11139) | def median(a, axis=None, out=None, overwrite_input=None, keepdims=False): function quantile (line 11191) | def quantile(a, q, axis=None, out=None, overwrite_input=None, interpolat... function shares_memory (line 11277) | def shares_memory(a, b, max_work=None): function may_share_memory (line 11311) | def may_share_memory(a, b, max_work=None): function diff (line 11353) | def diff(a, n=1, axis=-1, prepend=None, append=None): # pylint: disable... function ediff1d (line 11401) | def ediff1d(ary, to_end=None, to_begin=None): function resize (line 11441) | def resize(a, new_shape): function interp (line 11493) | def interp(x, xp, fp, left=None, right=None, period=None): # pylint: di... function full_like (line 11573) | def full_like(a, fill_value, dtype=None, order='C', device=None, out=Non... function zeros_like (line 11632) | def zeros_like(a, dtype=None, order='C', device=None, out=None): function ones_like (line 11693) | def ones_like(a, dtype=None, order='C', device=None, out=None): function fill_diagonal (line 11752) | def fill_diagonal(a, val, wrap=False): function nan_to_num (line 11840) | def nan_to_num(x, copy=True, nan=0.0, posinf=None, neginf=None, **kwargs): function squeeze (line 11932) | def squeeze(x, axis=None): function isnan (line 11982) | def isnan(x, out=None, **kwargs): function isinf (line 12033) | def isinf(x, out=None, **kwargs): function isposinf (line 12091) | def isposinf(x, out=None, **kwargs): function isneginf (line 12137) | def isneginf(x, out=None, **kwargs): function isfinite (line 12183) | def isfinite(x, out=None, **kwargs): function where (line 12237) | def where(condition, x=None, y=None): function polyval (line 12306) | def polyval(p, x): function bincount (line 12352) | def bincount(x, weights=None, minlength=0): function atleast_1d (line 12403) | def atleast_1d(*arys): function atleast_2d (line 12444) | def atleast_2d(*arys): function atleast_3d (line 12481) | def atleast_3d(*arys): function pad (line 12529) | def pad(x, pad_width=None, mode="constant", **kwargs): # pylint: disable... function prod (line 12630) | def prod(a, axis=None, dtype=None, out=None, keepdims=False, initial=Non... function dot (line 12708) | def dot(a, b, out=None): function cumsum (line 12771) | def cumsum(a, axis=None, dtype=None, out=None): function reshape (line 12822) | def reshape(a, newshape, order='C'): function moveaxis (line 12886) | def moveaxis(a, source, destination): function copy (line 12930) | def copy(a): # pylint: disable=redefined-outer-name function rollaxis (line 12960) | def rollaxis(a, axis, start=0): function diag (line 12995) | def diag(v, k=0): function diagflat (line 13036) | def diagflat(v, k=0): function diagonal (line 13077) | def diagonal(a, offset=0, axis1=0, axis2=1): function sum (line 13131) | def sum(a, axis=None, dtype=None, out=None, keepdims=None, initial=None,... function bitwise_left_shift (line 13225) | def bitwise_left_shift(x1, x2, out=None): function bitwise_right_shift (line 13260) | def bitwise_right_shift(x1, x2, out=None): function asarray (line 13299) | def asarray(obj, dtype=None, device=None, copy=None): function from_dlpack (line 13373) | def from_dlpack(x): FILE: python/mxnet/numpy/random.py function randint (line 34) | def randint(low, high=None, size=None, dtype=None, device=None, out=None): function uniform (line 87) | def uniform(low=0.0, high=1.0, size=None, dtype=None, device=None, out=N... function normal (line 146) | def normal(loc=0.0, scale=1.0, size=None, dtype=None, device=None, out=N... function lognormal (line 216) | def lognormal(mean=0.0, sigma=1.0, size=None, dtype=None, device=None, o... function logistic (line 284) | def logistic(loc=0.0, scale=1.0, size=None, device=None, out=None): function gumbel (line 330) | def gumbel(loc=0.0, scale=1.0, size=None, device=None, out=None): function multinomial (line 393) | def multinomial(n, pvals, size=None, **kwargs): function multivariate_normal (line 436) | def multivariate_normal(mean, cov, size=None, check_valid=None, tol=None): function choice (line 514) | def choice(a, size=None, replace=True, p=None, device=None, out=None): function rayleigh (line 570) | def rayleigh(scale=1.0, size=None, device=None, out=None): function rand (line 598) | def rand(*size, **kwargs): function exponential (line 629) | def exponential(scale=1.0, size=None, device=None, out=None): function weibull (line 656) | def weibull(a, size=None, device=None, out=None): function pareto (line 699) | def pareto(a, size=None, device=None, out=None): function power (line 734) | def power(a, size=None, device=None, out=None): function shuffle (line 768) | def shuffle(x): function gamma (line 801) | def gamma(shape, scale=1.0, size=None, dtype=None, device=None, out=None): function beta (line 838) | def beta(a, b, size=None, dtype=None, device=None): function f (line 887) | def f(dfnum, dfden, size=None, device=None): function chisquare (line 950) | def chisquare(df, size=None, dtype=None, device=None): function randn (line 1016) | def randn(*size, **kwargs): function laplace (line 1058) | def laplace(loc=0.0, scale=1.0, size=None, dtype=None, device=None, out=... FILE: python/mxnet/numpy/set_functions.py function unique_all (line 28) | def unique_all(x): function unique_inverse (line 63) | def unique_inverse(x): function unique_values (line 93) | def unique_values(x): FILE: python/mxnet/numpy/stride_tricks.py function _broadcast_shape (line 27) | def _broadcast_shape(*args): function broadcast_arrays (line 34) | def broadcast_arrays(*args): FILE: python/mxnet/numpy/type_functions.py class finfo_obj (line 29) | class finfo_obj(NamedTuple): class iinfo_obj (line 37) | class iinfo_obj(NamedTuple): function can_cast (line 43) | def can_cast(from_, to): function finfo (line 65) | def finfo(dtype): function iinfo (line 98) | def iinfo(dtype): function _get_dtype (line 125) | def _get_dtype(array_or_dtype): function result_type (line 135) | def result_type(*arrays_and_dtypes): FILE: python/mxnet/numpy/utils.py function _get_np_op (line 73) | def _get_np_op(name): FILE: python/mxnet/numpy_dispatch_protocol.py function _find_duplicate (line 26) | def _find_duplicate(strs): function _implements (line 36) | def _implements(numpy_function): function with_array_function_protocol (line 44) | def with_array_function_protocol(func): function with_array_ufunc_protocol (line 64) | def with_array_ufunc_protocol(func): function _register_array_function (line 203) | def _register_array_function(): function _register_array_ufunc (line 315) | def _register_array_ufunc(): FILE: python/mxnet/numpy_extension/_op.py function softmax (line 33) | def softmax(data, length=None, axis=-1, temperature=None, use_length=Fal... function log_softmax (line 82) | def log_softmax(data, axis=-1, length=None, temperature=None, use_length... function masked_softmax (line 123) | def masked_softmax(data, mask, axis=-1, temperature=1.0, normalize=True): function masked_log_softmax (line 161) | def masked_log_softmax(data, mask, axis=-1, temperature=1.0, normalize=T... function activation (line 200) | def activation(data, act_type='relu', **kwargs): function batch_norm (line 230) | def batch_norm(x, gamma, beta, running_mean, running_var, eps=1e-3, mome... function fully_connected (line 333) | def fully_connected(x, weight, bias=None, num_hidden=None, function pick (line 391) | def pick(data, index, axis=-1, mode='clip', keepdims=False): function convolution (line 463) | def convolution(data=None, weight=None, bias=None, kernel=None, stride=N... function deconvolution (line 587) | def deconvolution(data=None, weight=None, bias=None, kernel=None, stride... function pooling (line 661) | def pooling(data=None, kernel=None, stride=None, pad=None, pool_type="max", function dropout (line 755) | def dropout(data, p=0.5, mode="training", axes=None, cudnn_off=False, **... function one_hot (line 788) | def one_hot(data, depth=None, on_value=1.0, off_value=0.0, dtype="float3... function rnn (line 847) | def rnn(data=None, parameters=None, state=None, state_cell=None, sequenc... function embedding (line 976) | def embedding(data, weight, input_dim=None, output_dim=None, dtype="floa... function topk (line 1064) | def topk(data, axis=-1, k=1, ret_typ="indices", is_ascend=False, dtype="... function layer_norm (line 1139) | def layer_norm(data=None, gamma=None, beta=None, axis=None, eps=None, ou... function leaky_relu (line 1193) | def leaky_relu(data=None, gamma=None, act_type="leaky", slope=0.25, lowe... function batch_dot (line 1238) | def batch_dot(a, b, transpose_a=False, transpose_b=False, forward_stype=... function broadcast_like (line 1277) | def broadcast_like(lhs, rhs, lhs_axes=None, rhs_axes=None): function arange_like (line 1321) | def arange_like(data, start=0.0, step=1.0, repeat=1, ctx=None, axis=None): function group_norm (line 1369) | def group_norm(data, gamma, beta, num_groups=1, eps=1e-3, output_mean_va... FILE: python/mxnet/numpy_extension/control_flow.py function foreach (line 28) | def foreach(body, data, init_states): function while_loop (line 87) | def while_loop(cond, func, loop_vars, max_iterations=None): function cond (line 173) | def cond(pred, then_func, else_func, inputs, name="cond"): FILE: python/mxnet/numpy_extension/random.py function seed (line 29) | def seed(seed, device='all'): # pylint: disable=redefined-outer-name function bernoulli (line 80) | def bernoulli(prob=None, logit=None, size=None, dtype=None, device=None,... function uniform_n (line 134) | def uniform_n(low=0.0, high=1.0, batch_shape=None, dtype=None, device=No... function normal_n (line 192) | def normal_n(loc=0.0, scale=1.0, batch_shape=None, dtype=None, device=No... FILE: python/mxnet/numpy_extension/utils.py function save (line 34) | def save(file, arr): function savez (line 62) | def savez(file, *args, **kwds): function load (line 124) | def load(file): FILE: python/mxnet/numpy_op_fallback.py function register (line 32) | def register(op_name, imperative=True, symbolic=True): class EmptyLike (line 54) | class EmptyLike(operator.CustomOp): method __init__ (line 56) | def __init__(self, dtype, order, subok, shape): method forward (line 63) | def forward(self, is_train, req, in_data, out_data, aux): method backward (line 72) | def backward(self, req, out_grad, in_data, out_data, in_grad, aux): class EmptyLikeProp (line 77) | class EmptyLikeProp(operator.CustomOpProp): method __init__ (line 79) | def __init__(self, dtype, order, subok, shape): method list_arguments (line 86) | def list_arguments(self): method infer_shape (line 89) | def infer_shape(self, in_shape): method infer_type (line 92) | def infer_type(self, in_type): method create_operator (line 98) | def create_operator(self, ctx, in_shapes, in_dtypes): class Resize (line 103) | class Resize(operator.CustomOp): method __init__ (line 105) | def __init__(self, new_shape): method forward (line 109) | def forward(self, is_train, req, in_data, out_data, aux): method backward (line 113) | def backward(self, req, out_grad, in_data, out_data, in_grad, aux): class ResizeProp (line 118) | class ResizeProp(operator.CustomOpProp): method __init__ (line 120) | def __init__(self, new_shape): method list_arguments (line 124) | def list_arguments(self): method infer_shape (line 127) | def infer_shape(self, in_shape): method create_operator (line 131) | def create_operator(self, ctx, in_shapes, in_dtypes): class Unravel_index (line 136) | class Unravel_index(operator.CustomOp): method __init__ (line 138) | def __init__(self, shape): method forward (line 142) | def forward(self, is_train, req, in_data, out_data, aux): method backward (line 146) | def backward(self, req, out_grad, in_data, out_data, in_grad, aux): class Unravel_indexProp (line 151) | class Unravel_indexProp(operator.CustomOpProp): method __init__ (line 153) | def __init__(self, shape): method list_arguments (line 157) | def list_arguments(self): method infer_shape (line 160) | def infer_shape(self, in_shape): method create_operator (line 165) | def create_operator(self, ctx, in_shapes, in_dtypes): class MultivariateNormal (line 170) | class MultivariateNormal(operator.CustomOp): method __init__ (line 172) | def __init__(self, size=None): method forward (line 176) | def forward(self, is_train, req, in_data, out_data, aux): method backward (line 188) | def backward(self, req, out_grad, in_data, out_data, in_grad, aux): class MultivariateNormalProp (line 194) | class MultivariateNormalProp(operator.CustomOpProp): method __init__ (line 197) | def __init__(self, size=None): method list_arguments (line 202) | def list_arguments(self): method infer_shape (line 205) | def infer_shape(self, in_shape): method create_operator (line 228) | def create_operator(self, ctx, in_shapes, in_dtypes): FILE: python/mxnet/numpy_op_signature.py function _get_builtin_op (line 27) | def _get_builtin_op(op_name): function _register_op_signatures (line 54) | def _register_op_signatures(): FILE: python/mxnet/onnx/mx2onnx/_export_helper.py function load_module (line 24) | def load_module(sym_filepath, params_filepath): FILE: python/mxnet/onnx/mx2onnx/_export_model.py function get_operator_support (line 31) | def get_operator_support(opset_version=None): function export_model (line 51) | def export_model(sym, params, in_shapes=None, in_types=np.float32, FILE: python/mxnet/onnx/mx2onnx/_export_onnx.py class MXNetGraph (line 42) | class MXNetGraph(object): method __init__ (line 47) | def __init__(self): method register (line 54) | def register(op_name, opset_version=12): method convert_layer (line 69) | def convert_layer(node, **kwargs): method split_params (line 105) | def split_params(sym, params): method get_outputs (line 133) | def get_outputs(sym, params, in_shapes, output_label, in_types, dynami... method convert_weights_to_numpy (line 231) | def convert_weights_to_numpy(weights_dict): method create_onnx_graph_proto (line 236) | def create_onnx_graph_proto(self, sym, params, in_shapes, in_types, ve... FILE: python/mxnet/onnx/mx2onnx/_op_translations/_op_translations_opset12.py function parse_helper (line 50) | def parse_helper(attrs, attrs_name, alt_value=None): function transform_padding (line 67) | def transform_padding(pad_width): function convert_string_to_list (line 87) | def convert_string_to_list(string_val): function get_boolean_attribute_value (line 108) | def get_boolean_attribute_value(attrs, attr_name): function get_inputs (line 116) | def get_inputs(node, kwargs): function get_input_dtypes (line 130) | def get_input_dtypes(node, kwargs): function create_basic_op_node (line 139) | def create_basic_op_node(op_name, node, kwargs): function create_const_scalar_node (line 151) | def create_const_scalar_node(input_name, value, kwargs): function create_const_node (line 164) | def create_const_node(input_name, value, kwargs): function create_tensor (line 178) | def create_tensor(tensor_list, tensor_name, initializer, dtype='int64'): function convert_weights_and_inputs (line 197) | def convert_weights_and_inputs(node, **kwargs): function convert_convolution (line 223) | def convert_convolution(node, **kwargs): function convert_deconvolution (line 265) | def convert_deconvolution(node, **kwargs): function convert_crop (line 319) | def convert_crop(node, **kwargs): function convert_fully_connected (line 355) | def convert_fully_connected(node, **kwargs): function convert_batchnorm (line 410) | def convert_batchnorm(node, **kwargs): function convert_tanh (line 440) | def convert_tanh(node, **kwargs): function convert_cos (line 448) | def convert_cos(node, **kwargs): function convert_sin (line 456) | def convert_sin(node, **kwargs): function convert_tan (line 464) | def convert_tan(node, **kwargs): function convert_acos (line 472) | def convert_acos(node, **kwargs): function convert_asin (line 480) | def convert_asin(node, **kwargs): function convert_atan (line 488) | def convert_atan(node, **kwargs): function convert_sigmoid (line 497) | def convert_sigmoid(node, **kwargs): function convert_relu (line 505) | def convert_relu(node, **kwargs): function convert_activation (line 512) | def convert_activation(node, **kwargs): function convert_pad (line 547) | def convert_pad(node, **kwargs): function create_helper_trans_node (line 602) | def create_helper_trans_node(node_name, input_node): function convert_dot (line 616) | def convert_dot(node, **kwargs): function transpose_last_two_dim (line 645) | def transpose_last_two_dim(name, kwargs): function convert_linalg_gemm2 (line 672) | def convert_linalg_gemm2(node, **kwargs): function convert_pooling (line 721) | def convert_pooling(node, **kwargs): function convert_exp (line 800) | def convert_exp(node, **kwargs): function convert_copy (line 807) | def convert_copy(node, **kwargs): function convert_identity (line 814) | def convert_identity(node, **kwargs): function convert_instancenorm (line 821) | def convert_instancenorm(node, **kwargs): function convert_leakyrelu (line 839) | def convert_leakyrelu(node, **kwargs): function convert_softmax (line 883) | def convert_softmax(node, **kwargs): function convert_softmax_output (line 1007) | def convert_softmax_output(node, **kwargs): function convert_logistic_regression_output (line 1026) | def convert_logistic_regression_output(node, **kwargs): function convert_blockgrad (line 1042) | def convert_blockgrad(node, **kwargs): function convert_makeloss (line 1047) | def convert_makeloss(node, **kwargs): function convert_concat (line 1053) | def convert_concat(node, **kwargs): function convert_transpose (line 1075) | def convert_transpose(node, **kwargs): function convert_lrn (line 1106) | def convert_lrn(node, **kwargs): function convert_l2normalization (line 1132) | def convert_l2normalization(node, **kwargs): function convert_dropout (line 1154) | def convert_dropout(node, **kwargs): function convert_flatten (line 1176) | def convert_flatten(node, **kwargs): function convert_clip (line 1183) | def convert_clip(node, **kwargs): function scalar_op_helper (line 1209) | def scalar_op_helper(node, op_name, reverse=False, **kwargs): function convert_mul_scalar (line 1314) | def convert_mul_scalar(node, **kwargs): function convert_minus_scalar (line 1325) | def convert_minus_scalar(node, **kwargs): function convert_rminus_scalar (line 1334) | def convert_rminus_scalar(node, **kwargs): function convert_add_scalar (line 1344) | def convert_add_scalar(node, **kwargs): function convert_div_scalar (line 1354) | def convert_div_scalar(node, **kwargs): function convert_rdiv_scalar (line 1363) | def convert_rdiv_scalar(node, **kwargs): function convert_pow_scalar (line 1372) | def convert_pow_scalar(node, **kwargs): function convert_argmax (line 1381) | def convert_argmax(node, **kwargs): function convert_argmin (line 1423) | def convert_argmin(node, **kwargs): function convert_maximum (line 1464) | def convert_maximum(node, **kwargs): function convert_minimum (line 1472) | def convert_minimum(node, **kwargs): function convert_min (line 1480) | def convert_min(node, **kwargs): function convert_max (line 1522) | def convert_max(node, **kwargs): function convert_mean (line 1563) | def convert_mean(node, **kwargs): function convert_prod (line 1605) | def convert_prod(node, **kwargs): function convert_elementwise_add (line 1647) | def convert_elementwise_add(node, **kwargs): function covert_broadcast_add (line 1656) | def covert_broadcast_add(node, **kwargs): function convert_elementwise_sub (line 1665) | def convert_elementwise_sub(node, **kwargs): function covert_broadcast_sub (line 1672) | def covert_broadcast_sub(node, **kwargs): function convert_elemwise_mul (line 1680) | def convert_elemwise_mul(node, **kwargs): function convert_broadcast_mul (line 1687) | def convert_broadcast_mul(node, **kwargs): function convert_broadcast_min (line 1694) | def convert_broadcast_min(node, **kwargs): function convert_broadcast_max (line 1702) | def convert_broadcast_max(node, **kwargs): function convert_elemwise_div (line 1710) | def convert_elemwise_div(node, **kwargs): function convert_broadcast_div (line 1717) | def convert_broadcast_div(node, **kwargs): function convert_negative (line 1725) | def convert_negative(node, **kwargs): function convert_abs (line 1733) | def convert_abs(node, **kwargs): function convert_addn (line 1740) | def convert_addn(node, **kwargs): function convert_ceil (line 1749) | def convert_ceil(node, **kwargs): function convert_floor (line 1757) | def convert_floor(node, **kwargs): function convert_npx_reshape (line 1765) | def convert_npx_reshape(node, **kwargs): function convert_reshape (line 1795) | def convert_reshape(node, **kwargs): function convert_cast (line 1980) | def convert_cast(node, **kwargs): function convert_slice_axis (line 1995) | def convert_slice_axis(node, **kwargs): function convert_slice_channel (line 2041) | def convert_slice_channel(node, **kwargs): function convert_expand_dims (line 2072) | def convert_expand_dims(node, **kwargs): function convert_squeeze (line 2091) | def convert_squeeze(node, **kwargs): function convert_log (line 2120) | def convert_log(node, **kwargs): function convert_reciprocal (line 2128) | def convert_reciprocal(node, **kwargs): function convert_power (line 2136) | def convert_power(node, **kwargs): function convert_broadcast_power (line 2143) | def convert_broadcast_power(node, **kwargs): function convert_sqrt (line 2151) | def convert_sqrt(node, **kwargs): function convert_depthtospace (line 2158) | def convert_depthtospace(node, **kwargs): function convert_spacetodepth (line 2176) | def convert_spacetodepth(node, **kwargs): function convert_square (line 2195) | def convert_square(node, **kwargs): function convert_sum (line 2230) | def convert_sum(node, **kwargs): function convert_shape (line 2262) | def convert_shape(node, **kwargs): function convert_hardsigmoid (line 2270) | def convert_hardsigmoid(node, **kwargs): function convert_broadcast_lesser (line 2291) | def convert_broadcast_lesser(node, **kwargs): function convert_broadcast_lesser_equal (line 2311) | def convert_broadcast_lesser_equal(node, **kwargs): function convert_broadcast_greater_equal (line 2330) | def convert_broadcast_greater_equal(node, **kwargs): function convert_broadcast_greater (line 2349) | def convert_broadcast_greater(node, **kwargs): function convert_broadcast_equal (line 2369) | def convert_broadcast_equal(node, **kwargs): function convert_broadcast_not_equal (line 2388) | def convert_broadcast_not_equal(node, **kwargs): function convert_broadcast_logical_and (line 2408) | def convert_broadcast_logical_and(node, **kwargs): function convert_broadcast_logical_or (line 2428) | def convert_broadcast_logical_or(node, **kwargs): function convert_broadcast_logical_xor (line 2448) | def convert_broadcast_logical_xor(node, **kwargs): function convert_logical_not (line 2468) | def convert_logical_not(node, **kwargs): function convert_size (line 2487) | def convert_size(node, **kwargs): function convert_logsoftmax (line 2503) | def convert_logsoftmax(node, **kwargs): function convert_norm (line 2531) | def convert_norm(node, **kwargs): function convert_multinomial (line 2578) | def convert_multinomial(node, **kwargs): function convert_random_uniform (line 2601) | def convert_random_uniform(node, **kwargs): function convert_random_normal (line 2628) | def convert_random_normal(node, **kwargs): function convert_roipooling (line 2655) | def convert_roipooling(node, **kwargs): function convert_tile (line 2676) | def convert_tile(node, **kwargs): function convert_broadcast_to (line 2710) | def convert_broadcast_to(node, **kwargs): function convert_topk (line 2748) | def convert_topk(node, **kwargs): function convert_take (line 2809) | def convert_take(node, **kwargs): function convert_layer_norm (line 2876) | def convert_layer_norm(node, **kwargs): function convert_matmul_selfatt_qk (line 2940) | def convert_matmul_selfatt_qk(node, **kwargs): function convert_contrib_interleaved_matmul_selfatt_valatt (line 3006) | def convert_contrib_interleaved_matmul_selfatt_valatt(node, **kwargs): function convert_broadcast_axis (line 3054) | def convert_broadcast_axis(node, **kwargs): function convert_sequencemask (line 3100) | def convert_sequencemask(node, **kwargs): function convert_embedding (line 3159) | def convert_embedding(node, **kwargs): function convert_stack (line 3178) | def convert_stack(node, **kwargs): function convert_slice (line 3205) | def convert_slice(node, **kwargs): function convert_zeros (line 3246) | def convert_zeros(node, **kwargs): function convert_ones (line 3266) | def convert_ones(node, **kwargs): function convert_zeros_like (line 3285) | def convert_zeros_like(node, **kwargs): function convert_ones_like (line 3304) | def convert_ones_like(node, **kwargs): function convert_arange_like (line 3323) | def convert_arange_like(node, **kwargs): function convert_contrib_BilinearResize2D (line 3382) | def convert_contrib_BilinearResize2D(node, **kwargs): function convert_arange (line 3440) | def convert_arange(node, **kwargs): function convert_reverse (line 3475) | def convert_reverse(node, **kwargs): function convert_repeat (line 3516) | def convert_repeat(node, **kwargs): function convert_contrib_box_nms (line 3596) | def convert_contrib_box_nms(node, **kwargs): function convert_greater_scalar (line 3697) | def convert_greater_scalar(node, **kwargs): function convert_lesser_scalar (line 3725) | def convert_lesser_scalar(node, **kwargs): function convert_equal_scalar (line 3754) | def convert_equal_scalar(node, **kwargs): function convert_where (line 3783) | def convert_where(node, **kwargs): function convert_maximum_scalar (line 3810) | def convert_maximum_scalar(node, **kwargs): function convert_minimum_scalar (line 3833) | def convert_minimum_scalar(node, **kwargs): function convert_contrib_box_decode (line 3856) | def convert_contrib_box_decode(node, **kwargs): function convert_contrib_AdaptiveAvgPooling2D (line 3937) | def convert_contrib_AdaptiveAvgPooling2D(node, **kwargs): function convert_broadcast_mod (line 3959) | def convert_broadcast_mod(node, **kwargs): function convert_reshape_like (line 3987) | def convert_reshape_like(node, **kwargs): function convert_gather_nd (line 4080) | def convert_gather_nd(node, **kwargs): function convert_upsampling (line 4121) | def convert_upsampling(node, **kwargs): function convert_swapaxis (line 4150) | def convert_swapaxis(node, **kwargs): function convert_slice_like (line 4196) | def convert_slice_like(node, **kwargs): function convert_broadcast_like (line 4237) | def convert_broadcast_like(node, **kwargs): function convert_contrib_roialign (line 4280) | def convert_contrib_roialign(node, **kwargs): function convert_batch_dot (line 4323) | def convert_batch_dot(node, **kwargs): function convert_log2 (line 4424) | def convert_log2(node, **kwargs): function convert_argsort (line 4449) | def convert_argsort(node, **kwargs): function convert_one_hot (line 4486) | def convert_one_hot(node, **kwargs): function convert_random_uniform_like (line 4509) | def convert_random_uniform_like(node, **kwargs): function convert_sequence_reverse (line 4531) | def convert_sequence_reverse(node, **kwargs): function convert_RNN (line 4562) | def convert_RNN(node, **kwargs): function convert_rnn_param_concat (line 5006) | def convert_rnn_param_concat(node, **kwargs): function convert_contrib_div_sqrt_dim (line 5022) | def convert_contrib_div_sqrt_dim(node, **kwargs): function convert_contrib_split_v2 (line 5050) | def convert_contrib_split_v2(node, **kwargs): function convert_full_like (line 5083) | def convert_full_like(node, **kwargs): function covert_np_equal (line 5107) | def covert_np_equal(node, **kwargs): function convert_not_equal (line 5114) | def convert_not_equal(node, **kwargs): function convert_broadcast_npi_greater (line 5128) | def convert_broadcast_npi_greater(node, **kwargs): function convert_broadcast_npi_less (line 5135) | def convert_broadcast_npi_less(node, **kwargs): function convert_broadcast_npi_greater_equal (line 5142) | def convert_broadcast_npi_greater_equal(node, **kwargs): function convert_broadcast_npi_less_equal (line 5149) | def convert_broadcast_npi_less_equal(node, **kwargs): function convert_np_argmin (line 5156) | def convert_np_argmin(node, **kwargs): function convert_np_argmax (line 5181) | def convert_np_argmax(node, **kwargs): function convert_npi_mean (line 5206) | def convert_npi_mean(node, **kwargs): function convert_np_logical_and (line 5254) | def convert_np_logical_and(node, **kwargs): function convert_np_logical_xor (line 5270) | def convert_np_logical_xor(node, **kwargs): function convert_np_logical_or (line 5286) | def convert_np_logical_or(node, **kwargs): function convert_np_logical_not (line 5302) | def convert_np_logical_not(node, **kwargs): function convert_np_divide (line 5317) | def convert_np_divide(node, **kwargs): FILE: python/mxnet/onnx/mx2onnx/_op_translations/_op_translations_opset13.py function parse_helper (line 51) | def parse_helper(attrs, attrs_name, alt_value=None): function transform_padding (line 68) | def transform_padding(pad_width): function convert_string_to_list (line 88) | def convert_string_to_list(string_val): function get_boolean_attribute_value (line 109) | def get_boolean_attribute_value(attrs, attr_name): function get_inputs (line 117) | def get_inputs(node, kwargs): function get_input_dtypes (line 130) | def get_input_dtypes(node, kwargs): function create_basic_op_node (line 139) | def create_basic_op_node(op_name, node, kwargs): function create_const_scalar_node (line 152) | def create_const_scalar_node(input_name, value, kwargs): function create_const_node (line 165) | def create_const_node(input_name, value, kwargs): function create_tensor (line 179) | def create_tensor(tensor_list, tensor_name, initializer, dtype='int64'): function create_helper_trans_node (line 197) | def create_helper_trans_node(node_name, input_node): function scalar_op_helper (line 208) | def scalar_op_helper(node, op_name, **kwargs): function convert_arange_like (line 291) | def convert_arange_like(node, **kwargs): function convert_layer_norm (line 349) | def convert_layer_norm(node, **kwargs): function convert_broadcast_axis (line 414) | def convert_broadcast_axis(node, **kwargs): function convert_sequencemask (line 460) | def convert_sequencemask(node, **kwargs): function convert_expand_dims (line 519) | def convert_expand_dims(node, **kwargs): function convert_stack (line 538) | def convert_stack(node, **kwargs): function convert_softmax (line 565) | def convert_softmax(node, **kwargs): function convert_reverse (line 685) | def convert_reverse(node, **kwargs): function convert_repeat (line 726) | def convert_repeat(node, **kwargs): function convert_contrib_box_nms (line 808) | def convert_contrib_box_nms(node, **kwargs): function convert_contrib_roialign (line 909) | def convert_contrib_roialign(node, **kwargs): function convert_sum (line 954) | def convert_sum(node, **kwargs): function convert_RNN (line 992) | def convert_RNN(node, **kwargs): function convert_slice_channel (line 1436) | def convert_slice_channel(node, **kwargs): function convert_max (line 1470) | def convert_max(node, **kwargs): function convert_min (line 1519) | def convert_min(node, **kwargs): function convert_mean (line 1569) | def convert_mean(node, **kwargs): function convert_prod (line 1619) | def convert_prod(node, **kwargs): function convert_squeeze (line 1670) | def convert_squeeze(node, **kwargs): function convert_softmax_output (line 1698) | def convert_softmax_output(node, **kwargs): function convert_norm (line 1716) | def convert_norm(node, **kwargs): function convert_logsoftmax (line 1769) | def convert_logsoftmax(node, **kwargs): function convert_contrib_split_v2 (line 1798) | def convert_contrib_split_v2(node, **kwargs): function convert_npi_mean (line 1864) | def convert_npi_mean(node, **kwargs): function convert_npi_prod (line 1915) | def convert_npi_prod(node, **kwargs): function convert_npi_min (line 1959) | def convert_npi_min(node, **kwargs): function convert_npi_max (line 2003) | def convert_npi_max(node, **kwargs): FILE: python/mxnet/operator.py class PythonOp (line 46) | class PythonOp(object): method __init__ (line 56) | def __init__(self, need_top_grad=True): method __call__ (line 61) | def __call__(self, *args, **kwargs): method get_symbol (line 64) | def get_symbol(self, *args, **kwargs): method forward (line 80) | def forward(self, in_data, out_data): method backward (line 91) | def backward(self, out_grad, in_data, out_data, in_grad): method infer_shape (line 103) | def infer_shape(self, in_shape): method list_outputs (line 122) | def list_outputs(self): method list_arguments (line 132) | def list_arguments(self): method need_top_grad (line 143) | def need_top_grad(self): class NumpyOp (line 155) | class NumpyOp(PythonOp): method __init__ (line 164) | def __init__(self, need_top_grad=True): method get_symbol (line 168) | def get_symbol(self, *args, **kwargs): class NDArrayOp (line 260) | class NDArrayOp(PythonOp): method __init__ (line 269) | def __init__(self, need_top_grad=True): method get_symbol (line 273) | def get_symbol(self, *args, **kwargs): method declare_backward_dependency (line 409) | def declare_backward_dependency(self, out_grad, in_data, out_data): class CustomOp (line 434) | class CustomOp(object): method __init__ (line 436) | def __init__(self): method forward (line 439) | def forward(self, is_train, req, in_data, out_data, aux): method backward (line 456) | def backward(self, req, out_grad, in_data, out_data, in_grad, aux): method assign (line 471) | def assign(self, dst, req, src): class CustomOpProp (line 487) | class CustomOpProp(object): method __init__ (line 496) | def __init__(self, need_top_grad=True): method infer_shape (line 499) | def infer_shape(self, in_shape): method infer_type (line 521) | def infer_type(self, in_type): method infer_storage_type (line 544) | def infer_storage_type(self, in_stype): method infer_storage_type_backward (line 575) | def infer_storage_type_backward(self, ograd_stype, in_stype, out_stype... method list_outputs (line 629) | def list_outputs(self): method list_arguments (line 639) | def list_arguments(self): method list_auxiliary_states (line 649) | def list_auxiliary_states(self): method declare_backward_dependency (line 659) | def declare_backward_dependency(self, out_grad, in_data, out_data): method create_operator (line 683) | def create_operator(self, ctx, in_shapes, in_dtypes): class _Registry (line 690) | class _Registry(object): method __init__ (line 692) | def __init__(self): method inc (line 698) | def inc(self): function register (line 710) | def register(reg_name): function get_all_registered_operators (line 1128) | def get_all_registered_operators(): function get_all_registered_operators_grouped (line 1145) | def get_all_registered_operators_grouped(): function get_operator_arguments (line 1174) | def get_operator_arguments(op_name): FILE: python/mxnet/optimizer/adabelief.py class AdaBelief (line 32) | class AdaBelief(Optimizer): method __init__ (line 79) | def __init__(self, learning_rate=0.001, beta1=0.9, beta2=0.999, epsilo... method create_state (line 91) | def create_state(self, index, weight): method step (line 96) | def step(self, indices, weights, grads, states): method fused_step (line 141) | def fused_step(self, indices, weights, grads, states): FILE: python/mxnet/optimizer/adadelta.py class AdaDelta (line 28) | class AdaDelta(Optimizer): method __init__ (line 61) | def __init__(self, learning_rate=1.0, rho=0.9, epsilon=1e-6, use_fused... method create_state (line 68) | def create_state(self, index, weight): method step (line 72) | def step(self, indices, weights, grads, states): FILE: python/mxnet/optimizer/adagrad.py class AdaGrad (line 28) | class AdaGrad(Optimizer): method __init__ (line 63) | def __init__(self, learning_rate=0.01, epsilon=1e-6, use_fused_step=Tr... method create_state (line 72) | def create_state(self, index, weight): method step (line 75) | def step(self, indices, weights, grads, states): method fused_step (line 110) | def fused_step(self, indices, weights, grads, states): FILE: python/mxnet/optimizer/adam.py class Adam (line 29) | class Adam(Optimizer): method __init__ (line 85) | def __init__(self, learning_rate=0.001, beta1=0.9, beta2=0.999, epsilo... method create_state (line 99) | def create_state(self, index, weight): method step (line 106) | def step(self, indices, weights, grads, states): method fused_step (line 149) | def fused_step(self, indices, weights, grads, states): FILE: python/mxnet/optimizer/adamW.py class AdamW (line 32) | class AdamW(Optimizer): method __init__ (line 80) | def __init__(self, learning_rate=0.001, beta1=0.9, beta2=0.999, epsilo... method create_state (line 92) | def create_state(self, index, weight): method step (line 97) | def step(self, indices, weights, grads, states): method fused_step (line 142) | def fused_step(self, indices, weights, grads, states): FILE: python/mxnet/optimizer/adamax.py class Adamax (line 29) | class Adamax(Optimizer): method __init__ (line 61) | def __init__(self, learning_rate=0.002, beta1=0.9, beta2=0.999, epsilo... method create_state (line 70) | def create_state(self, index, weight): method step (line 74) | def step(self, indices, weights, grads, states): FILE: python/mxnet/optimizer/contrib.py class GroupAdaGrad (line 26) | class GroupAdaGrad(Optimizer): method __init__ (line 63) | def __init__(self, learning_rate=0.01, epsilon=1e-6, use_fused_step=Tr... method create_state (line 69) | def create_state(self, index, weight): method step (line 75) | def step(self, indices, weights, grads, states): method fused_step (line 110) | def fused_step(self, indices, weights, grads, states): FILE: python/mxnet/optimizer/dcasgd.py class DCASGD (line 29) | class DCASGD(Optimizer): method __init__ (line 55) | def __init__(self, learning_rate=0.1, momentum=0.0, lamda=0.04, method create_state (line 64) | def create_state(self, index, weight): method step (line 71) | def step(self, indices, weights, grads, states): FILE: python/mxnet/optimizer/ftml.py class FTML (line 28) | class FTML(Optimizer): method __init__ (line 66) | def __init__(self, learning_rate=0.0025, beta1=0.6, beta2=0.999, epsil... method create_state (line 75) | def create_state(self, index, weight): method step (line 80) | def step(self, indices, weights, grads, states): method fused_step (line 127) | def fused_step(self, indices, weights, grads, states): FILE: python/mxnet/optimizer/ftrl.py class Ftrl (line 29) | class Ftrl(Optimizer): method __init__ (line 84) | def __init__(self, learning_rate=0.1, lamda1=0.01, beta=1., method create_state (line 92) | def create_state(self, index, weight): method step (line 96) | def step(self, indices, weights, grads, states): method fused_step (line 139) | def fused_step(self, indices, weights, grads, states): FILE: python/mxnet/optimizer/lamb.py class LAMB (line 32) | class LAMB(Optimizer): method __init__ (line 66) | def __init__(self, learning_rate=0.001, beta1=0.9, beta2=0.999, epsilo... method create_state (line 83) | def create_state(self, index, weight): method step (line 88) | def step(self, indices, weights, grads, states): method fused_step (line 159) | def fused_step(self, indices, weights, grads, states): method update_multi_precision (line 255) | def update_multi_precision(self, indices, weights, grads, states): FILE: python/mxnet/optimizer/lans.py class LANS (line 30) | class LANS(Optimizer): method __init__ (line 62) | def __init__(self, learning_rate=0.001, beta1=0.9, beta2=0.999, epsilo... method create_state (line 78) | def create_state(self, index, weight): method step (line 83) | def step(self, indices, weights, grads, states): method fused_step (line 165) | def fused_step(self, indices, weights, grads, states): method update_multi_precision (line 214) | def update_multi_precision(self, indices, weights, grads, states): FILE: python/mxnet/optimizer/lars.py class LARS (line 36) | class LARS(Optimizer): method __init__ (line 77) | def __init__(self, learning_rate=0.1, momentum=0.0, eta=0.001, method create_state (line 96) | def create_state(self, index, weight): method _l2norm (line 103) | def _l2norm(self, v, rescale=False): method _get_lars (line 111) | def _get_lars(self, index, weight, grad, wd): method step (line 130) | def step(self, indices, weights, grads, states): method fused_step (line 173) | def fused_step(self, indices, weights, grads, states): method update_multi_precision (line 277) | def update_multi_precision(self, indices, weights, grads, states): FILE: python/mxnet/optimizer/nadam.py class Nadam (line 29) | class Nadam(Optimizer): method __init__ (line 59) | def __init__(self, learning_rate=0.001, beta1=0.9, beta2=0.999, epsilo... method create_state (line 70) | def create_state(self, index, weight): method step (line 74) | def step(self, indices, weights, grads, states): FILE: python/mxnet/optimizer/nag.py class NAG (line 29) | class NAG(Optimizer): method __init__ (line 58) | def __init__(self, learning_rate=0.1, momentum=0.9, multi_precision=Fa... method create_state (line 66) | def create_state(self, index, weight): method step (line 72) | def step(self, indices, weights, grads, states): method fused_step (line 111) | def fused_step(self, indices, weights, grads, states): method update_multi_precision (line 156) | def update_multi_precision(self, indices, weights, grads, states): FILE: python/mxnet/optimizer/optimizer.py class Optimizer (line 29) | class Optimizer(object): method __init__ (line 91) | def __init__(self, rescale_grad=1., param_idx2name=None, wd=0., method register (line 140) | def register(klass): method create_optimizer (line 165) | def create_optimizer(name, **kwargs): method learning_rate (line 199) | def learning_rate(self): method create_state (line 205) | def create_state(self, index, weight): method create_state_multi_precision (line 226) | def create_state_multi_precision(self, index, weight): method step (line 255) | def step(self, indices, weights, grads, states): method fused_step (line 273) | def fused_step(self, indices, weights, grads, states): method update (line 292) | def update(self, indices, weights, grads, states): method update_multi_precision (line 317) | def update_multi_precision(self, indices, weights, grads, states): method set_learning_rate (line 351) | def set_learning_rate(self, lr): method set_lr_mult (line 368) | def set_lr_mult(self, args_lr_mult): method set_wd_mult (line 401) | def set_wd_mult(self, args_wd_mult): method _set_current_context (line 430) | def _set_current_context(self, device_id): method _set_current_device (line 436) | def _set_current_device(self, device_id): method _update_count (line 448) | def _update_count(self, index): method _get_lrs (line 464) | def _get_lrs(self, indices): method _get_lr (line 492) | def _get_lr(self, index): method _get_wds (line 507) | def _get_wds(self, indices): method _get_wd (line 531) | def _get_wd(self, index): method __getstate__ (line 547) | def __getstate__(self): method __setstate__ (line 553) | def __setstate__(self, state): class Test (line 564) | class Test(Optimizer): method __init__ (line 566) | def __init__(self, **kwargs): method create_state (line 569) | def create_state(self, index, weight): method step (line 573) | def step(self, indices, weights, grads, states): FILE: python/mxnet/optimizer/rmsprop.py class RMSProp (line 27) | class RMSProp(Optimizer): method __init__ (line 70) | def __init__(self, learning_rate=0.001, rho=0.9, momentum=0.9, method create_state (line 88) | def create_state(self, index, weight): method step (line 97) | def step(self, indices, weights, grads, states): method fused_step (line 149) | def fused_step(self, indices, weights, grads, states): FILE: python/mxnet/optimizer/sgd.py class SGD (line 33) | class SGD(Optimizer): method __init__ (line 95) | def __init__(self, learning_rate=0.1, momentum=0.0, lazy_update=False, method create_state (line 111) | def create_state(self, index, weight): method step (line 118) | def step(self, indices, weights, grads, states): method fused_step (line 156) | def fused_step(self, indices, weights, grads, states): method update_multi_precision (line 236) | def update_multi_precision(self, indices, weights, grads, states): FILE: python/mxnet/optimizer/sgld.py class SGLD (line 31) | class SGLD(Optimizer): method __init__ (line 50) | def __init__(self, learning_rate=0.1, use_fused_step=False, **kwargs): method create_state (line 55) | def create_state(self, index, weight): method step (line 58) | def step(self, indices, weights, grads, states): FILE: python/mxnet/optimizer/signum.py class Signum (line 28) | class Signum(Optimizer): method __init__ (line 67) | def __init__(self, learning_rate=0.01, momentum=0.9, wd_lh=0.0, use_fu... method create_state (line 74) | def create_state(self, index, weight): method step (line 80) | def step(self, indices, weights, grads, states): method fused_step (line 121) | def fused_step(self, indices, weights, grads, states): FILE: python/mxnet/optimizer/updater.py class Updater (line 31) | class Updater(object): method __init__ (line 33) | def __init__(self, optimizer): method __call__ (line 39) | def __call__(self, index, grad, weight): method sync_state_context (line 95) | def sync_state_context(self, state, context): method set_states (line 108) | def set_states(self, states): method get_states (line 117) | def get_states(self, dump_optimizer=False): function get_updater (line 129) | def get_updater(optimizer): FILE: python/mxnet/optimizer/utils.py function _flatten_list (line 22) | def _flatten_list(nested_list): function _as_classic (line 26) | def _as_classic(a, allow_np): FILE: python/mxnet/profiler.py function set_kvstore_handle (line 30) | def set_kvstore_handle(handle): function set_config (line 34) | def set_config(**kwargs): function profiler_set_config (line 73) | def profiler_set_config(mode='symbolic', filename='profile.json'): function set_state (line 92) | def set_state(state='stop', profile_process='worker'): function profiler_set_state (line 112) | def profiler_set_state(state='stop'): function dump (line 125) | def dump(finished=True, profile_process='worker'): function dump_profile (line 146) | def dump_profile(): function dumps (line 154) | def dumps(reset=False, format='table', sort_by='total', ascending=False): function pause (line 196) | def pause(profile_process='worker'): function resume (line 212) | def resume(profile_process='worker'): class Domain (line 228) | class Domain(object): method __init__ (line 239) | def __init__(self, name): method __str__ (line 244) | def __str__(self): method new_task (line 247) | def new_task(self, name): method new_frame (line 257) | def new_frame(self, name): method new_counter (line 267) | def new_counter(self, name, value=None): method new_marker (line 277) | def new_marker(self, name): class Task (line 287) | class Task(object): method __init__ (line 306) | def __init__(self, domain, name): method __del__ (line 313) | def __del__(self): method start (line 317) | def start(self): method stop (line 321) | def stop(self): method __str__ (line 325) | def __str__(self): class Frame (line 329) | class Frame(object): method __init__ (line 348) | def __init__(self, domain, name): method __del__ (line 355) | def __del__(self): method start (line 359) | def start(self): method stop (line 363) | def stop(self): method __str__ (line 367) | def __str__(self): class Event (line 371) | class Event(object): method __init__ (line 386) | def __init__(self, name): method __del__ (line 391) | def __del__(self): method start (line 395) | def start(self): method stop (line 399) | def stop(self): method __str__ (line 403) | def __str__(self): class Counter (line 407) | class Counter(object): method __init__ (line 421) | def __init__(self, domain, name, value=None): method __del__ (line 430) | def __del__(self): method set_value (line 435) | def set_value(self, value): method increment (line 445) | def increment(self, delta=1): method decrement (line 455) | def decrement(self, delta=1): method __iadd__ (line 465) | def __iadd__(self, delta): method __isub__ (line 469) | def __isub__(self, delta): method __str__ (line 473) | def __str__(self): class Marker (line 477) | class Marker(object): method __init__ (line 489) | def __init__(self, domain, name): method mark (line 493) | def mark(self, scope='process'): # pylint: disable=redefined-outer-name function scope (line 507) | def scope(name=':', append_mode=True): FILE: python/mxnet/random.py function seed (line 31) | def seed(seed_state, device="all"): FILE: python/mxnet/recordio.py class MXRecordIO (line 36) | class MXRecordIO(object): method __init__ (line 64) | def __init__(self, uri, flag): method open (line 72) | def open(self): method __del__ (line 87) | def __del__(self): method __getstate__ (line 90) | def __getstate__(self): method __setstate__ (line 106) | def __setstate__(self, d): method _check_pid (line 116) | def _check_pid(self, allow_reset=False): method close (line 126) | def close(self): method reset (line 137) | def reset(self): method write (line 158) | def write(self, buf): method read (line 179) | def read(self): class MXIndexedRecordIO (line 215) | class MXIndexedRecordIO(MXRecordIO): method __init__ (line 238) | def __init__(self, idx_path, uri, flag, key_type=int): method open (line 246) | def open(self): method close (line 259) | def close(self): method __getstate__ (line 266) | def __getstate__(self): method seek (line 272) | def seek(self, idx): method tell (line 282) | def tell(self): method read_idx (line 304) | def read_idx(self, idx): method write_idx (line 320) | def write_idx(self, idx, buf): function pack (line 362) | def pack(header, s): function unpack (line 397) | def unpack(s): function unpack_img (line 427) | def unpack_img(s, iscolor=-1): function pack_img (line 470) | def pack_img(header, img, quality=95, img_fmt='.jpg'): FILE: python/mxnet/registry.py function get_registry (line 31) | def get_registry(base_class): function get_register_func (line 48) | def get_register_func(base_class, nickname): function get_alias_func (line 85) | def get_alias_func(base_class, nickname): function get_create_func (line 112) | def get_create_func(base_class, nickname): FILE: python/mxnet/rtc.py class CudaModule (line 41) | class CudaModule(object): method __init__ (line 94) | def __init__(self, source, options=(), exports=()): method __del__ (line 108) | def __del__(self): method get_kernel (line 111) | def get_kernel(self, name, signature): class CudaKernel (line 173) | class CudaKernel(object): method __init__ (line 177) | def __init__(self, handle, name, is_ndarray, dtypes): method __del__ (line 183) | def __del__(self): method launch (line 186) | def launch(self, args, ctx, grid_dims, block_dims, shared_mem=0): FILE: python/mxnet/runtime.py class Feature (line 52) | class Feature(ctypes.Structure): method name (line 60) | def name(self): method enabled (line 65) | def enabled(self): method __repr__ (line 69) | def __repr__(self): function feature_list (line 75) | def feature_list(): class Features (line 89) | class Features(collections.OrderedDict): method __new__ (line 92) | def __new__(cls): method __repr__ (line 98) | def __repr__(self): method is_enabled (line 101) | def is_enabled(self, feature_name): function get_branch (line 120) | def get_branch(): function get_commit_hash (line 125) | def get_commit_hash(): FILE: python/mxnet/symbol/contrib.py function rand_zipfian (line 39) | def rand_zipfian(true_classes, num_sampled, range_max): function _flatten (line 101) | def _flatten(args, inout_str): function _regroup (line 119) | def _regroup(args, fmt): function _get_sym_uniq_name (line 138) | def _get_sym_uniq_name(sym): function _get_graph_inputs (line 141) | def _get_graph_inputs(subg): function _cut_subgraph (line 153) | def _cut_subgraph(subg): function _get_unique_subgraph_name (line 165) | def _get_unique_subgraph_name(subgraph_name): function _construct_subgraph (line 176) | def _construct_subgraph(sym_out, sym_states, name): function _check_data (line 201) | def _check_data(inputs, in_type, msg): function foreach (line 212) | def foreach(body, data, init_states, name="foreach"): function while_loop (line 374) | def while_loop(cond, func, loop_vars, max_iterations=None, name="while_l... function cond (line 597) | def cond(pred, then_func, else_func, name="cond"): function adamw_update (line 730) | def adamw_update(weight, grad, mean, var, rescale_grad, lr, eta, beta1=0... function mp_adamw_update (line 740) | def mp_adamw_update(weight, grad, mean, var, weight32, rescale_grad, lr,... FILE: python/mxnet/symbol/numpy/_symbol.py class _Symbol (line 62) | class _Symbol(Symbol): method __getitem__ (line 63) | def __getitem__(self, key): # pylint: disable = too-many-return-statem... method __setitem__ (line 158) | def __setitem__(self, key, value): method __repr__ (line 161) | def __repr__(self): method name (line 173) | def name(self): method __iter__ (line 194) | def __iter__(self): method __add__ (line 199) | def __add__(self, other): method __invert__ (line 203) | def __invert__(self): method __and__ (line 207) | def __and__(self, other): method __or__ (line 211) | def __or__(self, other): method __xor__ (line 215) | def __xor__(self, other): method __round__ (line 219) | def __round__(self, n=0): method __abs__ (line 223) | def __abs__(self): method __ceil__ (line 227) | def __ceil__(self): method __floor__ (line 231) | def __floor__(self): method __trunc__ (line 235) | def __trunc__(self): method __sub__ (line 239) | def __sub__(self, other): method __rsub__ (line 243) | def __rsub__(self, other): method __mul__ (line 247) | def __mul__(self, other): method __rmul__ (line 251) | def __rmul__(self, other): method __div__ (line 255) | def __div__(self, other): method __rdiv__ (line 259) | def __rdiv__(self, other): method __mod__ (line 263) | def __mod__(self, other): method __rmod__ (line 267) | def __rmod__(self, other): method __idiv__ (line 271) | def __idiv__(self, other): method __truediv__ (line 274) | def __truediv__(self, other): method __rtruediv__ (line 278) | def __rtruediv__(self, other): method __itruediv__ (line 282) | def __itruediv__(self, other): method __pow__ (line 285) | def __pow__(self, other): method __rpow__ (line 289) | def __rpow__(self, other): method __neg__ (line 292) | def __neg__(self): method __deepcopy__ (line 296) | def __deepcopy__(self, _): method __eq__ (line 299) | def __eq__(self, other): method __ne__ (line 303) | def __ne__(self, other): method __gt__ (line 307) | def __gt__(self, other): method __ge__ (line 311) | def __ge__(self, other): method __lt__ (line 315) | def __lt__(self, other): method __le__ (line 319) | def __le__(self, other): method __len__ (line 323) | def __len__(self): method num_outputs (line 329) | def num_outputs(self): method as_nd_ndarray (line 336) | def as_nd_ndarray(self): method as_np_ndarray (line 342) | def as_np_ndarray(self): method T (line 348) | def T(self): method astype (line 353) | def astype(self, dtype, order='K', casting='unsafe', subok=True, copy=... method dot (line 410) | def dot(self, b, out=None): method reshape (line 415) | def reshape(self, *args, **kwargs): # pylint: disable=arguments-differ method argmax (line 443) | def argmax(self, axis=None, out=None): # pylint: disable=arguments-di... method reshape_like (line 448) | def reshape_like(self, *args, **kwargs): method zeros_like (line 456) | def zeros_like(self, *args, **kwargs): method ones_like (line 464) | def ones_like(self, *args, **kwargs): method broadcast_axes (line 472) | def broadcast_axes(self, *args, **kwargs): method repeat (line 480) | def repeat(self, repeats, axis=None): # pylint: disable=arguments-differ method pad (line 484) | def pad(self, *args, **kwargs): method swapaxes (line 492) | def swapaxes(self, axis1, axis2): # pylint: disable=arguments-differ method split (line 498) | def split(self, *args, **kwargs): method split_v2 (line 506) | def split_v2(self, *args, **kwargs): method slice (line 514) | def slice(self, *args, **kwargs): method slice_axis (line 522) | def slice_axis(self, *args, **kwargs): method slice_like (line 530) | def slice_like(self, *args, **kwargs): method take (line 538) | def take(self, indices, axis=None, mode='raise'): # pylint: disable=a... method one_hot (line 546) | def one_hot(self, *args, **kwargs): method pick (line 554) | def pick(self, *args, **kwargs): method sort (line 562) | def sort(self, axis=-1, kind=None, order=None): # pylint: disable=arg... method topk (line 570) | def topk(self, *args, **kwargs): method argsort (line 578) | def argsort(self, axis=-1, kind=None, order=None): # pylint: disable=... method argmax_channel (line 586) | def argmax_channel(self, *args, **kwargs): method argmin (line 594) | def argmin(self, axis=None, out=None): # pylint: disable=arguments-di... method clip (line 599) | def clip(self, min=None, max=None, out=None): # pylint: disable=argum... method abs (line 605) | def abs(self, *args, **kwargs): method sign (line 613) | def sign(self, *args, **kwargs): method flatten (line 621) | def flatten(self, order='C'): # pylint: disable=arguments-differ method shape_array (line 625) | def shape_array(self, *args, **kwargs): method size_array (line 633) | def size_array(self, *args, **kwargs): method expand_dims (line 641) | def expand_dims(self, *args, **kwargs): # pylint: disable=arguments-d... method tile (line 649) | def tile(self, *args, **kwargs): method transpose (line 657) | def transpose(self, *axes): # pylint: disable=arguments-differ method flip (line 670) | def flip(self, *args, **kwargs): method depth_to_space (line 678) | def depth_to_space(self, *args, **kwargs): method space_to_depth (line 686) | def space_to_depth(self, *args, **kwargs): method diag (line 694) | def diag(self, k=0, **kwargs): method diagonal (line 702) | def diagonal(self, offset=0, axis1=0, axis2=1): # pylint: disable=arg... method sum (line 712) | def sum(self, axis=None, dtype=None, out=None, keepdims=False): # pyl... method nansum (line 716) | def nansum(self, *args, **kwargs): method prod (line 724) | def prod(self, axis=None, dtype=None, out=None, keepdims=False): # py... method nanprod (line 728) | def nanprod(self, *args, **kwargs): method mean (line 736) | def mean(self, axis=None, dtype=None, out=None, keepdims=False): # py... method std (line 740) | def std(self, axis=None, dtype=None, out=None, ddof=0, keepdims=False)... method var (line 744) | def var(self, axis=None, dtype=None, out=None, ddof=0, keepdims=False)... method cumsum (line 748) | def cumsum(self, axis=None, dtype=None, out=None): method max (line 752) | def max(self, axis=None, out=None, keepdims=False): # pylint: disable... method min (line 756) | def min(self, axis=None, out=None, keepdims=False): # pylint: disable... method norm (line 760) | def norm(self, *args, **kwargs): method round (line 768) | def round(self, decimals=0, out=None, **kwargs): # pylint: disable=arg... method rint (line 776) | def rint(self, *args, **kwargs): method fix (line 784) | def fix(self, *args, **kwargs): method floor (line 792) | def floor(self, *args, **kwargs): method ceil (line 800) | def ceil(self, *args, **kwargs): method trunc (line 808) | def trunc(self, *args, **kwargs): method sin (line 816) | def sin(self, *args, **kwargs): method cos (line 824) | def cos(self, *args, **kwargs): method tan (line 832) | def tan(self, *args, **kwargs): method arcsin (line 840) | def arcsin(self, *args, **kwargs): method arccos (line 848) | def arccos(self, *args, **kwargs): method arctan (line 856) | def arctan(self, *args, **kwargs): method degrees (line 864) | def degrees(self, *args, **kwargs): method radians (line 872) | def radians(self, *args, **kwargs): method sinh (line 880) | def sinh(self, *args, **kwargs): method cosh (line 888) | def cosh(self, *args, **kwargs): method tanh (line 896) | def tanh(self, *args, **kwargs): method arcsinh (line 904) | def arcsinh(self, *args, **kwargs): method arccosh (line 912) | def arccosh(self, *args, **kwargs): method arctanh (line 920) | def arctanh(self, *args, **kwargs): method exp (line 928) | def exp(self, *args, **kwargs): method expm1 (line 936) | def expm1(self, *args, **kwargs): method log (line 944) | def log(self, *args, **kwargs): method log10 (line 952) | def log10(self, *args, **kwargs): method log2 (line 960) | def log2(self, *args, **kwargs): method log1p (line 968) | def log1p(self, *args, **kwargs): method sqrt (line 976) | def sqrt(self, *args, **kwargs): method rsqrt (line 984) | def rsqrt(self, *args, **kwargs): method cbrt (line 992) | def cbrt(self, *args, **kwargs): method rcbrt (line 1000) | def rcbrt(self, *args, **kwargs): method square (line 1008) | def square(self, *args, **kwargs): method reciprocal (line 1016) | def reciprocal(self, *args, **kwargs): method relu (line 1024) | def relu(self, *args, **kwargs): method sigmoid (line 1032) | def sigmoid(self, *args, **kwargs): method softmax (line 1040) | def softmax(self, *args, **kwargs): method log_softmax (line 1048) | def log_softmax(self, *args, **kwargs): method softmin (line 1056) | def softmin(self, *args, **kwargs): method squeeze (line 1064) | def squeeze(self, axis=None): # pylint: disable=arguments-differ method broadcast_to (line 1068) | def broadcast_to(self, *args, **kwargs): method broadcast_like (line 1071) | def broadcast_like(self, *args, **kwargs): method optimize_for (line 1075) | def optimize_for(self, backend, args=None, aux=None, ctx=None, function zeros (line 1084) | def zeros(shape, dtype=float, order='C', ctx=None): function ones (line 1121) | def ones(shape, dtype=None, order='C', ctx=None): function invert (line 1156) | def invert(x, out=None, **kwargs): function bitwise_not (line 1202) | def bitwise_not(x, out=None, **kwargs): function broadcast_to (line 1247) | def broadcast_to(array, shape): function full (line 1277) | def full(shape, fill_value, dtype=None, order='C', ctx=None, out=None): ... function full_like (line 1342) | def full_like(a, fill_value, dtype=None, order='C', ctx=None, out=None):... function zeros_like (line 1387) | def zeros_like(a, dtype=None, order='C', ctx=None, out=None): # pylint:... function ones_like (line 1430) | def ones_like(a, dtype=None, order='C', ctx=None, out=None): # pylint: ... function identity (line 1473) | def identity(n, dtype=None, ctx=None): function take (line 1508) | def take(a, indices, axis=None, mode='raise', out=None): function _ufunc_helper (line 1575) | def _ufunc_helper(lhs, rhs, fn_array, fn_scalar, lfn_scalar, rfn_scalar=... function add (line 1627) | def add(x1, x2, out=None, **kwargs): function subtract (line 1633) | def subtract(x1, x2, out=None, **kwargs): function multiply (line 1640) | def multiply(x1, x2, out=None, **kwargs): function divide (line 1646) | def divide(x1, x2, out=None, **kwargs): function true_divide (line 1652) | def true_divide(x1, x2, out=None): function mod (line 1659) | def mod(x1, x2, out=None, **kwargs): function fmod (line 1665) | def fmod(x1, x2, out=None, **kwargs): function remainder (line 1671) | def remainder(x1, x2, out=None, **kwargs): function power (line 1677) | def power(x1, x2, out=None, **kwargs): function gcd (line 1683) | def gcd(x1, x2, out=None, **kwargs): function matmul (line 1714) | def matmul(a, b, out=None, **kwargs): function lcm (line 1770) | def lcm(x1, x2, out=None, **kwargs): function argsort (line 1800) | def argsort(a, axis=-1, kind=None, order=None): function sort (line 1839) | def sort(a, axis=-1, kind=None, order=None): function dot (line 1871) | def dot(a, b, out=None): function tensordot (line 1933) | def tensordot(a, b, axes=2): function histogram (line 1988) | def histogram(a, bins=10, range=None, normed=None, weights=None, density... function eye (line 2035) | def eye(N, M=None, k=0, dtype=float, **kwargs): function empty_like (line 2070) | def empty_like(prototype, dtype=None, order='C', subok=False, shape=None... function linspace (line 2131) | def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=No... function logspace (line 2204) | def logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None, ... function expand_dims (line 2287) | def expand_dims(a, axis): function tril (line 2309) | def tril(m, k=0): function triu (line 2336) | def triu(m, k=0): function tril_indices (line 2362) | def tril_indices(n, k=0, m=None): function trace (line 2445) | def trace(a, offset=0, axis1=0, axis2=1, out=None): function transpose (line 2479) | def transpose(a, axes=None): function tri (line 2500) | def tri(N, M=None, k=0, dtype=None, ctx=None): function repeat (line 2533) | def repeat(a, repeats, axis=None): function _unary_func_helper (line 2581) | def _unary_func_helper(x, fn_array, fn_scalar, out=None, **kwargs): function sin (line 2610) | def sin(x, out=None, **kwargs): function cos (line 2636) | def cos(x, out=None, **kwargs): function sinh (line 2661) | def sinh(x, out=None, **kwargs): function cosh (line 2687) | def cosh(x, out=None, **kwargs): function tanh (line 2713) | def tanh(x, out=None, **kwargs): function log10 (line 2762) | def log10(x, out=None, **kwargs): function sqrt (line 2788) | def sqrt(x, out=None, **kwargs): function cbrt (line 2814) | def cbrt(x, out=None, **kwargs): function abs (line 2836) | def abs(x, out=None, **kwargs): function fabs (line 2858) | def fabs(x, out=None, **kwargs): function absolute (line 2884) | def absolute(x, out=None, **kwargs): function sign (line 2906) | def sign(x, out=None, **kwargs): function exp (line 2937) | def exp(x, out=None, **kwargs): function expm1 (line 2959) | def expm1(x, out=None, **kwargs): function arcsin (line 2981) | def arcsin(x, out=None, **kwargs): function arccos (line 3025) | def arccos(x, out=None, **kwargs): function arctan (line 3061) | def arctan(x, out=None, **kwargs): function log (line 3096) | def log(x, out=None, **kwargs): function degrees (line 3134) | def degrees(x, out=None, **kwargs): function rad2deg (line 3167) | def rad2deg(x, out=None, **kwargs): function rint (line 3197) | def rint(x, out=None, **kwargs): function log2 (line 3227) | def log2(x, out=None, **kwargs): function log1p (line 3257) | def log1p(x, out=None, **kwargs): function radians (line 3296) | def radians(x, out=None, **kwargs): function deg2rad (line 3330) | def deg2rad(x, out=None, **kwargs): function reciprocal (line 3362) | def reciprocal(x, out=None, **kwargs): function square (line 3398) | def square(x, out=None, **kwargs): function negative (line 3428) | def negative(x, out=None, **kwargs): function fix (line 3458) | def fix(x, out=None, **kwargs): function tan (line 3485) | def tan(x, out=None, **kwargs): function ceil (line 3511) | def ceil(x, out=None, **kwargs): function insert (line 3546) | def insert(arr, obj, values, axis=None): function floor (line 3610) | def floor(x, out=None, **kwargs): function trunc (line 3646) | def trunc(x, out=None, **kwargs): function logical_not (line 3679) | def logical_not(x, out=None, **kwargs): function arcsinh (line 3710) | def arcsinh(x, out=None, **kwargs): function arccosh (line 3748) | def arccosh(x, out=None, **kwargs): function arctanh (line 3786) | def arctanh(x, out=None, **kwargs): function tile (line 3823) | def tile(A, reps): function arange (line 3856) | def arange(start, stop=None, step=1, dtype=None, ctx=None): function delete (line 3908) | def delete(arr, obj, axis=None): function split (line 3948) | def split(ary, indices_or_sections, axis=0): function array_split (line 3994) | def array_split(ary, indices_or_sections, axis=0): function hsplit (line 4042) | def hsplit(ary, indices_or_sections): function vsplit (line 4147) | def vsplit(ary, indices_or_sections): function dsplit (line 4208) | def dsplit(ary, indices_or_sections): function concatenate (line 4246) | def concatenate(seq, axis=0, out=None): function append (line 4287) | def append(arr, values, axis=None): # pylint: disable=redefined-outer-name function stack (line 4327) | def stack(arrays, axis=0, out=None): function vstack (line 4353) | def vstack(arrays, out=None): function row_stack (line 4385) | def row_stack(arrays): function column_stack (line 4414) | def column_stack(tup): function hstack (line 4450) | def hstack(arrays): function dstack (line 4489) | def dstack(arrays): function maximum (line 4519) | def maximum(x1, x2, out=None, **kwargs): function fmax (line 4525) | def fmax(x1, x2, out=None, **kwargs): function minimum (line 4531) | def minimum(x1, x2, out=None, **kwargs): function fmin (line 4537) | def fmin(x1, x2, out=None, **kwargs): function max (line 4542) | def max(a, axis=None, out=None, keepdims=False): function min (line 4589) | def min(a, axis=None, out=None, keepdims=False): function amax (line 4634) | def amax(a, axis=None, out=None, keepdims=False): function amin (line 4681) | def amin(a, axis=None, out=None, keepdims=False): function all (line 4726) | def all(a, axis=None, out=None, keepdims=False): function any (line 4756) | def any(a, axis=None, out=None, keepdims=False): function clip (line 4787) | def clip(a, a_min, a_max, out=None): function swapaxes (line 4834) | def swapaxes(a, axis1, axis2): function argmax (line 4855) | def argmax(a, axis=None, out=None): function argmin (line 4894) | def argmin(a, axis=None, out=None): function average (line 4932) | def average(a, axis=None, weights=None, returned=False, out=None): function mean (line 5027) | def mean(a, axis=None, dtype=None, out=None, keepdims=False): # pylint:... function std (line 5090) | def std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False): # ... function var (line 5140) | def var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False): # ... function indices (line 5194) | def indices(dimensions, dtype=None, ctx=None): function copysign (line 5262) | def copysign(x1, x2, out=None, **kwargs): function ravel (line 5295) | def ravel(x, order='C'): function unravel_index (line 5333) | def unravel_index(indices, shape, order='C'): # pylint: disable=redefine... function flatnonzero (line 5365) | def flatnonzero(a): function diag_indices_from (line 5391) | def diag_indices_from(arr): function hanning (line 5431) | def hanning(M, dtype=None, ctx=None): function hamming (line 5513) | def hamming(M, dtype=None, ctx=None): function blackman (line 5593) | def blackman(M, dtype=None, ctx=None): function flip (line 5671) | def flip(m, axis=None, out=None): function flipud (line 5709) | def flipud(m): function fliplr (line 5733) | def fliplr(m): function around (line 5757) | def around(x, decimals=0, out=None, **kwargs): function round (line 5800) | def round(x, decimals=0, out=None, **kwargs): function round_ (line 5818) | def round_(x, decimals=0, out=None, **kwargs): function arctan2 (line 5837) | def arctan2(x1, x2, out=None, **kwargs): function hypot (line 5904) | def hypot(x1, x2, out=None, **kwargs): function bitwise_and (line 5937) | def bitwise_and(x1, x2, out=None, **kwargs): function bitwise_xor (line 5961) | def bitwise_xor(x1, x2, out=None, **kwargs): function bitwise_or (line 5985) | def bitwise_or(x1, x2, out=None, **kwargs): function unique (line 6008) | def unique(ar, return_index=False, return_inverse=False, return_counts=F... function ldexp (line 6069) | def ldexp(x1, x2, out=None, **kwargs): function vdot (line 6100) | def vdot(a, b): function inner (line 6140) | def inner(a, b): function outer (line 6196) | def outer(a, b): function cross (line 6248) | def cross(a, b, axisa=-1, axisb=-1, axisc=-1, axis=None): # pylint: disa... function kron (line 6300) | def kron(a, b): function equal (line 6341) | def equal(x1, x2, out=None): function not_equal (line 6373) | def not_equal(x1, x2, out=None): function greater (line 6405) | def greater(x1, x2, out=None): function less (line 6438) | def less(x1, x2, out=None): function greater_equal (line 6470) | def greater_equal(x1, x2, out=None): function less_equal (line 6503) | def less_equal(x1, x2, out=None): function roll (line 6536) | def roll(a, shift, axis=None): function logical_and (line 6571) | def logical_and(x1, x2, out=None): function logical_or (line 6606) | def logical_or(x1, x2, out=None): function logical_xor (line 6641) | def logical_xor(x1, x2, out=None): function rot90 (line 6675) | def rot90(m, k=1, axes=(0, 1)): function einsum (line 6718) | def einsum(*operands, **kwargs): function percentile (line 6845) | def percentile(a, q, axis=None, out=None, overwrite_input=None, interpol... function median (line 6896) | def median(a, axis=None, out=None, overwrite_input=None, keepdims=False): function quantile (line 6933) | def quantile(a, q, axis=None, out=None, overwrite_input=None, interpolat... function shares_memory (line 6994) | def shares_memory(a, b, max_work=None): function may_share_memory (line 7011) | def may_share_memory(a, b, max_work=None): function diff (line 7033) | def diff(a, n=1, axis=-1, prepend=None, append=None): # pylint: disable... function ediff1d (line 7081) | def ediff1d(ary, to_end=None, to_begin=None): function interp (line 7119) | def interp(x, xp, fp, left=None, right=None, period=None): # pylint: di... function resize (line 7172) | def resize(a, new_shape): function nan_to_num (line 7224) | def nan_to_num(x, copy=True, nan=0.0, posinf=None, neginf=None, **kwargs): function squeeze (line 7288) | def squeeze(x, axis=None): function isnan (line 7340) | def isnan(x, out=None, **kwargs): function isinf (line 7378) | def isinf(x, out=None, **kwargs): function isposinf (line 7415) | def isposinf(x, out=None, **kwargs): function isneginf (line 7444) | def isneginf(x, out=None, **kwargs): function isfinite (line 7473) | def isfinite(x, out=None, **kwargs): function atleast_1d (line 7506) | def atleast_1d(*arys): function atleast_2d (line 7530) | def atleast_2d(*arys): function atleast_3d (line 7552) | def atleast_3d(*arys): function where (line 7576) | def where(condition, x, y): function load (line 7614) | def load(fname): function load_json (line 7646) | def load_json(json_str): function polyval (line 7671) | def polyval(p, x): function bincount (line 7709) | def bincount(x, weights=None, minlength=0): function pad (line 7743) | def pad(x, pad_width, mode='constant', **kwargs): # pylint: disable=too-... function prod (line 7877) | def prod(a, axis=None, dtype=None, keepdims=False, initial=None, output=... function cumsum (line 7955) | def cumsum(a, axis=None, dtype=None, out=None): function reshape (line 7989) | def reshape(a, newshape, reverse=False, order='C'): function moveaxis (line 8053) | def moveaxis(a, source, destination): function copy (line 8097) | def copy(a): # pylint: disable=redefined-outer-name function rollaxis (line 8126) | def rollaxis(a, axis, start=0): function diag (line 8161) | def diag(v, k=0): function diagflat (line 8183) | def diagflat(v, k=0): function diagonal (line 8224) | def diagonal(a, offset=0, axis1=0, axis2=1): function sum (line 8257) | def sum(a, axis=None, dtype=None, out=None, keepdims=False, initial=None... FILE: python/mxnet/symbol/numpy/linalg.py function matrix_rank (line 29) | def matrix_rank(M, tol=None, hermitian=False): function lstsq (line 62) | def lstsq(a, b, rcond='warn'): function pinv (line 128) | def pinv(a, rcond=1e-15, hermitian=False): function norm (line 201) | def norm(x, ord=None, axis=None, keepdims=False): function svd (line 364) | def svd(a): function cholesky (line 425) | def cholesky(a): function qr (line 484) | def qr(a, mode='reduced'): function inv (line 543) | def inv(a): function det (line 585) | def det(a): function slogdet (line 629) | def slogdet(a): function solve (line 695) | def solve(a, b): function tensorinv (line 749) | def tensorinv(a, ind=2): function tensorsolve (line 804) | def tensorsolve(a, b, axes=None): function eigvals (line 852) | def eigvals(a): function eigvalsh (line 897) | def eigvalsh(a, UPLO='L'): function eig (line 947) | def eig(a): function eigh (line 1001) | def eigh(a, UPLO='L'): FILE: python/mxnet/symbol/numpy/random.py function randint (line 32) | def randint(low, high=None, size=None, dtype=None, ctx=None, out=None): function rand (line 93) | def rand(*size, **kwargs): function uniform (line 120) | def uniform(low=0.0, high=1.0, size=None, dtype=None, ctx=None, out=None): function normal (line 175) | def normal(loc=0.0, scale=1.0, size=None, dtype=None, ctx=None, out=None): function lognormal (line 224) | def lognormal(mean=0.0, sigma=1.0, size=None, dtype=None, ctx=None, out=... function logistic (line 258) | def logistic(loc=0.0, scale=1.0, size=None, ctx=None, out=None): function gumbel (line 304) | def gumbel(loc=0.0, scale=1.0, size=None, ctx=None, out=None): function choice (line 347) | def choice(a, size=None, replace=True, p=None, ctx=None, out=None): function laplace (line 421) | def laplace(loc=0.0, scale=1.0, size=None, dtype=None, ctx=None, out=None): function gamma (line 471) | def gamma(shape, scale=1.0, size=None, dtype=None, ctx=None, out=None): function rayleigh (line 530) | def rayleigh(scale=0.0, size=None, ctx=None, out=None): function beta (line 563) | def beta(a, b, size=None, dtype=None, ctx=None): function f (line 622) | def f(dfnum, dfden, size=None, ctx=None): function chisquare (line 659) | def chisquare(df, size=None, dtype=None, ctx=None): function exponential (line 732) | def exponential(scale=1.0, size=None, ctx=None, out=None): function weibull (line 767) | def weibull(a, size=None, ctx=None, out=None): function pareto (line 824) | def pareto(a, size=None, ctx=None, out=None): function power (line 869) | def power(a, size=None, ctx=None, out=None): function multivariate_normal (line 914) | def multivariate_normal(mean, cov, size=None, check_valid=None, tol=None): function shuffle (line 995) | def shuffle(x): FILE: python/mxnet/symbol/numpy_extension/random.py function bernoulli (line 26) | def bernoulli(prob=None, logit=None, size=None, dtype=None, ctx=None, ou... function uniform_n (line 104) | def uniform_n(low=0.0, high=1.0, batch_shape=None, dtype=None, ctx=None): function normal_n (line 184) | def normal_n(loc=0.0, scale=1.0, batch_shape=None, dtype=None, ctx=None): FILE: python/mxnet/symbol/random.py function _random_helper (line 29) | def _random_helper(random, sampler, params, shape, dtype, kwargs): function uniform (line 48) | def uniform(low=0, high=1, shape=_Null, dtype=_Null, **kwargs): function normal (line 82) | def normal(loc=0, scale=1, shape=_Null, dtype=_Null, **kwargs): function randn (line 116) | def randn(*shape, **kwargs): function poisson (line 146) | def poisson(lam=1, shape=_Null, dtype=_Null, **kwargs): function exponential (line 176) | def exponential(scale=1, shape=_Null, dtype=_Null, **kwargs): function gamma (line 210) | def gamma(alpha=1, beta=1, shape=_Null, dtype=_Null, **kwargs): function binomial (line 243) | def binomial(n=1, p=0.5, shape=_Null, dtype=_Null, **kwargs): function negative_binomial (line 275) | def negative_binomial(k=1, p=1, shape=_Null, dtype=_Null, **kwargs): function generalized_negative_binomial (line 310) | def generalized_negative_binomial(mu=1, alpha=1, shape=_Null, dtype=_Nul... function categorical (line 346) | def categorical(data, shape=_Null, get_prob=True, dtype='int32', **kwargs): function multinomial (line 390) | def multinomial(n=[1], p=[[1.0]], shape=_Null, dtype='float32', **kwargs): function shuffle (line 424) | def shuffle(data, **kwargs): function randint (line 461) | def randint(low, high, shape=_Null, dtype=_Null, **kwargs): FILE: python/mxnet/symbol/register.py function _verify_np_symbol (line 36) | def _verify_np_symbol(op_name, func_name, sym): function _verify_legacy_symbol (line 61) | def _verify_legacy_symbol(op_name, func_name, sym): function _generate_symbol_function_code (line 84) | def _generate_symbol_function_code(handle, op_name, func_name, signature... function _make_symbol_function (line 260) | def _make_symbol_function(handle, name, func_name): FILE: python/mxnet/symbol/symbol.py class Symbol (line 54) | class Symbol(SymbolBase): method as_np_ndarray (line 63) | def as_np_ndarray(self): method as_nd_ndarray (line 70) | def as_nd_ndarray(self): method __repr__ (line 74) | def __repr__(self): method __iter__ (line 86) | def __iter__(self): method __abs__ (line 109) | def __abs__(self): method __add__ (line 113) | def __add__(self, other): method __bool__ (line 125) | def __bool__(self): method __iadd__ (line 130) | def __iadd__(self, other): method __radd__ (line 133) | def __radd__(self, other): method __sub__ (line 136) | def __sub__(self, other): method __isub__ (line 148) | def __isub__(self, other): method __rsub__ (line 151) | def __rsub__(self, other): method __mul__ (line 171) | def __mul__(self, other): method __imul__ (line 183) | def __imul__(self, other): method __rmul__ (line 186) | def __rmul__(self, other): method __div__ (line 189) | def __div__(self, other): method __rdiv__ (line 201) | def __rdiv__(self, other): method __mod__ (line 221) | def __mod__(self, other): method __rmod__ (line 233) | def __rmod__(self, other): method __idiv__ (line 253) | def __idiv__(self, other): method __truediv__ (line 256) | def __truediv__(self, other): method __rtruediv__ (line 259) | def __rtruediv__(self, other): method __itruediv__ (line 262) | def __itruediv__(self, other): method __pow__ (line 265) | def __pow__(self, other): method __rpow__ (line 277) | def __rpow__(self, other): method __neg__ (line 286) | def __neg__(self): method __copy__ (line 307) | def __copy__(self): method __deepcopy__ (line 310) | def __deepcopy__(self, _): method __eq__ (line 333) | def __eq__(self, other): method __ne__ (line 345) | def __ne__(self, other): method __gt__ (line 357) | def __gt__(self, other): method __ge__ (line 369) | def __ge__(self, other): method __lt__ (line 381) | def __lt__(self, other): method __le__ (line 393) | def __le__(self, other): method __getstate__ (line 405) | def __getstate__(self): method __setstate__ (line 412) | def __setstate__(self, state): method __call__ (line 423) | def __call__(self, *args, **kwargs): method _compose (line 459) | def _compose(self, *args, **kwargs): method __getitem__ (line 514) | def __getitem__(self, index): method name (line 564) | def name(self): method attr (line 581) | def attr(self, key): method list_attr (line 611) | def list_attr(self, recursive=False): method attr_dict (line 634) | def attr_dict(self): method _set_attr (line 665) | def _set_attr(self, **kwargs): method get_inputs (line 682) | def get_inputs(self): method get_internals (line 709) | def get_internals(self): method get_children (line 737) | def get_children(self): method list_arguments (line 769) | def list_arguments(self): method list_outputs (line 791) | def list_outputs(self): method __len__ (line 817) | def __len__(self): method list_auxiliary_states (line 836) | def list_auxiliary_states(self): method list_inputs (line 874) | def list_inputs(self): method infer_type (line 898) | def infer_type(self, *args, **kwargs): method infer_type_partial (line 967) | def infer_type_partial(self, *args, **kwargs): method _infer_type_impl (line 1015) | def _infer_type_impl(self, partial, *args, **kwargs): method infer_shape (line 1068) | def infer_shape(self, *args, **kwargs): method infer_shape_partial (line 1155) | def infer_shape_partial(self, *args, **kwargs): method _infer_shape_impl (line 1204) | def _infer_shape_impl(self, partial, *args, **kwargs): method debug_str (line 1306) | def debug_str(self): method save (line 1359) | def save(self, fname, remove_amp_cast=True): method tojson (line 1392) | def tojson(self, remove_amp_cast=True): method _get_ndarray_inputs (line 1409) | def _get_ndarray_inputs(arg_key, args, arg_names, allow_missing): method _gen_atomic_symbol (line 1467) | def _gen_atomic_symbol(self): method optimize_for (line 1474) | def optimize_for(self, backend, args=None, aux=None, ctx=None, method _simple_bind (line 1681) | def _simple_bind(self, ctx, grad_req='write', type_dict=None, stype_di... method _bind (line 1786) | def _bind(self, ctx, args, args_grad=None, grad_req='write', method gradient (line 1873) | def gradient(self, wrt): method eval (line 1900) | def eval(self, ctx=None, **kwargs): method reshape (line 1940) | def reshape(self, *args, **kwargs): method reshape_like (line 1948) | def reshape_like(self, *args, **kwargs): method astype (line 1956) | def astype(self, *args, **kwargs): method zeros_like (line 1964) | def zeros_like(self, *args, **kwargs): method ones_like (line 1972) | def ones_like(self, *args, **kwargs): method broadcast_axes (line 1980) | def broadcast_axes(self, *args, **kwargs): method repeat (line 1988) | def repeat(self, *args, **kwargs): method pad (line 1996) | def pad(self, *args, **kwargs): method swapaxes (line 2004) | def swapaxes(self, *args, **kwargs): method split (line 2012) | def split(self, *args, **kwargs): method split_v2 (line 2020) | def split_v2(self, *args, **kwargs): method slice (line 2028) | def slice(self, *args, **kwargs): method slice_axis (line 2036) | def slice_axis(self, *args, **kwargs): method slice_like (line 2044) | def slice_like(self, *args, **kwargs): method take (line 2052) | def take(self, *args, **kwargs): method one_hot (line 2060) | def one_hot(self, *args, **kwargs): method pick (line 2068) | def pick(self, *args, **kwargs): method sort (line 2076) | def sort(self, *args, **kwargs): method topk (line 2084) | def topk(self, *args, **kwargs): method argsort (line 2092) | def argsort(self, *args, **kwargs): method argmax (line 2100) | def argmax(self, *args, **kwargs): method argmax_channel (line 2108) | def argmax_channel(self, *args, **kwargs): method argmin (line 2116) | def argmin(self, *args, **kwargs): method clip (line 2124) | def clip(self, *args, **kwargs): method abs (line 2132) | def abs(self, *args, **kwargs): method sign (line 2140) | def sign(self, *args, **kwargs): method flatten (line 2148) | def flatten(self, inplace=False, **kwargs): # pylint: disable=unused-a... method shape_array (line 2156) | def shape_array(self, *args, **kwargs): method size_array (line 2164) | def size_array(self, *args, **kwargs): method expand_dims (line 2172) | def expand_dims(self, axis, inplace=False, **kwargs): # pylint: disabl... method broadcast_to (line 2180) | def broadcast_to(self, *args, **kwargs): method broadcast_like (line 2188) | def broadcast_like(self, *args, **kwargs): method tile (line 2196) | def tile(self, *args, **kwargs): method transpose (line 2204) | def transpose(self, *args, **kwargs): method flip (line 2212) | def flip(self, *args, **kwargs): method depth_to_space (line 2220) | def depth_to_space(self, *args, **kwargs): method space_to_depth (line 2228) | def space_to_depth(self, *args, **kwargs): method diag (line 2236) | def diag(self, k=0, **kwargs): method sum (line 2244) | def sum(self, *args, **kwargs): method nansum (line 2252) | def nansum(self, *args, **kwargs): method prod (line 2260) | def prod(self, *args, **kwargs): method nanprod (line 2268) | def nanprod(self, *args, **kwargs): method mean (line 2276) | def mean(self, *args, **kwargs): method max (line 2284) | def max(self, *args, **kwargs): method min (line 2292) | def min(self, *args, **kwargs): method norm (line 2300) | def norm(self, *args, **kwargs): method round (line 2308) | def round(self, *args, **kwargs): method rint (line 2316) | def rint(self, *args, **kwargs): method fix (line 2324) | def fix(self, *args, **kwargs): method floor (line 2332) | def floor(self, *args, **kwargs): method ceil (line 2340) | def ceil(self, *args, **kwargs): method trunc (line 2348) | def trunc(self, *args, **kwargs): method sin (line 2356) | def sin(self, *args, **kwargs): method cos (line 2364) | def cos(self, *args, **kwargs): method tan (line 2372) | def tan(self, *args, **kwargs): method arcsin (line 2380) | def arcsin(self, *args, **kwargs): method arccos (line 2388) | def arccos(self, *args, **kwargs): method arctan (line 2396) | def arctan(self, *args, **kwargs): method degrees (line 2404) | def degrees(self, *args, **kwargs): method radians (line 2412) | def radians(self, *args, **kwargs): method sinh (line 2420) | def sinh(self, *args, **kwargs): method cosh (line 2428) | def cosh(self, *args, **kwargs): method tanh (line 2436) | def tanh(self, *args, **kwargs): method arcsinh (line 2444) | def arcsinh(self, *args, **kwargs): method arccosh (line 2452) | def arccosh(self, *args, **kwargs): method arctanh (line 2460) | def arctanh(self, *args, **kwargs): method exp (line 2468) | def exp(self, *args, **kwargs): method expm1 (line 2476) | def expm1(self, *args, **kwargs): method log (line 2484) | def log(self, *args, **kwargs): method log10 (line 2492) | def log10(self, *args, **kwargs): method log2 (line 2500) | def log2(self, *args, **kwargs): method log1p (line 2508) | def log1p(self, *args, **kwargs): method log_sigmoid (line 2516) | def log_sigmoid(self, *args, **kwargs): method mish (line 2524) | def mish(self, *args, **kwargs): method sqrt (line 2532) | def sqrt(self, *args, **kwargs): method rsqrt (line 2540) | def rsqrt(self, *args, **kwargs): method cbrt (line 2548) | def cbrt(self, *args, **kwargs): method rcbrt (line 2556) | def rcbrt(self, *args, **kwargs): method square (line 2564) | def square(self, *args, **kwargs): method reciprocal (line 2572) | def reciprocal(self, *args, **kwargs): method relu (line 2580) | def relu(self, *args, **kwargs): method sigmoid (line 2588) | def sigmoid(self, *args, **kwargs): method softmax (line 2596) | def softmax(self, *args, **kwargs): method log_softmax (line 2604) | def log_softmax(self, *args, **kwargs): method softmin (line 2612) | def softmin(self, *args, **kwargs): method squeeze (line 2620) | def squeeze(self, axis=None, inplace=False, **kwargs): # pylint: disab... method get_backend_symbol (line 2628) | def get_backend_symbol(self, backend): method wait_to_read (line 2645) | def wait_to_read(self): method asnumpy (line 2648) | def asnumpy(self): method asscalar (line 2651) | def asscalar(self): method copy (line 2654) | def copy(self): method as_in_context (line 2657) | def as_in_context(self): method detach (line 2660) | def detach(self): method backward (line 2663) | def backward(self): method has_dynamic_shape_op (line 2667) | def has_dynamic_shape_op(self): function var (line 2675) | def var(name, attr=None, shape=None, lr_mult=None, wd_mult=None, dtype=N... function Group (line 2761) | def Group(symbols, create_fn=Symbol): function load (line 2797) | def load(fname): function fromjson (line 2830) | def fromjson(json_str): function pow (line 2856) | def pow(base, exp): function power (line 2904) | def power(base, exp): function maximum (line 2943) | def maximum(left, right): function minimum (line 2987) | def minimum(left, right): function hypot (line 3031) | def hypot(left, right): function eye (line 3074) | def eye(N, M=0, k=0, dtype=None, **kwargs): function zeros (line 3099) | def zeros(shape, dtype=None, **kwargs): function ones (line 3119) | def ones(shape, dtype=None, **kwargs): function full (line 3139) | def full(shape, val, dtype=None, **kwargs): function arange (line 3161) | def arange(start, stop=None, step=1.0, repeat=1, infer_range=False, name... function linspace (line 3196) | def linspace(start, stop, num, endpoint=True, name=None, dtype=None): function histogram (line 3230) | def histogram(a, bins=10, range=None, **kwargs): function split_v2 (line 3260) | def split_v2(ary, indices_or_sections, axis=0, squeeze_axis=False): FILE: python/mxnet/symbol_doc.py class SymbolDoc (line 52) | class SymbolDoc(object): method get_output_shape (line 56) | def get_output_shape(sym, **input_shapes): function _build_doc (line 61) | def _build_doc(func_name, FILE: python/mxnet/test_utils.py function default_device (line 58) | def default_device(): function set_default_device (line 65) | def set_default_device(device): function default_dtype (line 70) | def default_dtype(): function default_rtols (line 75) | def default_rtols(): function default_atols (line 88) | def default_atols(): function default_numeric_eps (line 101) | def default_numeric_eps(): function effective_dtype (line 109) | def effective_dtype(dat): function get_tolerance (line 136) | def get_tolerance(dat, tol, default_tol): function get_tols (line 155) | def get_tols(x, y, rtol, atol): function get_atol (line 172) | def get_atol(atol=None, dtype=np.dtype(np.float64)): function get_rtol (line 176) | def get_rtol(rtol=None, dtype=np.dtype(np.float64)): function get_etol (line 180) | def get_etol(etol=None): function random_arrays (line 186) | def random_arrays(*shapes): function random_uniform_arrays (line 196) | def random_uniform_arrays(*shapes, **kwargs): function random_sample (line 208) | def random_sample(population, k): function _sorted_items (line 216) | def _sorted_items(d): function _sorted_dict (line 221) | def _sorted_dict(d): function _validate_csr_generation_inputs (line 226) | def _validate_csr_generation_inputs(num_rows, num_cols, density, function shuffle_csr_column_indices (line 245) | def shuffle_csr_column_indices(csr): function _get_uniform_dataset_csr (line 259) | def _get_uniform_dataset_csr(num_rows, num_cols, density=0.1, dtype=None, function _get_powerlaw_dataset_csr (line 290) | def _get_powerlaw_dataset_csr(num_rows, num_cols, density=0.1, dtype=None): function assign_each (line 340) | def assign_each(the_input, function): function assign_each2 (line 358) | def assign_each2(input1, input2, function): function create_2d_np_tensor (line 380) | def create_2d_np_tensor(rows, columns, dtype=np.int64): function create_2d_tensor (line 386) | def create_2d_tensor(rows, columns, dtype=np.int64): function create_vector (line 392) | def create_vector(size, dtype=np.int64): function rand_sparse_ndarray (line 396) | def rand_sparse_ndarray(shape, stype, density=None, dtype=None, distribu... function rand_ndarray (line 484) | def rand_ndarray(shape, stype='default', density=None, dtype=None, modif... function create_sparse_array (line 498) | def create_sparse_array(shape, stype, data_init=None, rsp_indices=None, function create_sparse_array_zd (line 529) | def create_sparse_array_zd(shape, stype, density, data_init=None, function rand_shape_2d (line 546) | def rand_shape_2d(dim0=10, dim1=10, allow_zero_size=False): function rand_shape_3d (line 551) | def rand_shape_3d(dim0=10, dim1=10, dim2=10, allow_zero_size=False): function rand_shape_nd (line 556) | def rand_shape_nd(num_dim, dim=10, allow_zero_size=False): function rand_coord_2d (line 561) | def rand_coord_2d(x_low, x_high, y_low, y_high): function np_reduce (line 567) | def np_reduce(dat, axis, keepdims, numpy_reduce_func): function _find_max_violation (line 599) | def _find_max_violation(a, b, rtol, atol): function same (line 610) | def same(a, b): function checkShapes (line 621) | def checkShapes(a, b): function almost_equal (line 629) | def almost_equal(a, b, rtol=None, atol=None, equal_nan=False, use_broadc... function locationError (line 638) | def locationError(a, b, index, names, maxError=False): function assert_almost_equal (line 653) | def assert_almost_equal(a, b, rtol=None, atol=None, names=('a', 'b'), eq... function assert_allclose (line 741) | def assert_allclose(a, b, rtol=1e-07, atol=0, equal_nan=True): function assert_almost_equal_with_err (line 745) | def assert_almost_equal_with_err(a, b, rtol=None, atol=None, etol=None, function assert_almost_equal_ignore_nan (line 810) | def assert_almost_equal_ignore_nan(a, b, rtol=None, atol=None, names=('a... function assert_exception (line 834) | def assert_exception(f, exception_type, *args, **kwargs): function _parse_location (line 843) | def _parse_location(sym, location, ctx, dtype=default_dtype()): function _parse_aux_states (line 902) | def _parse_aux_states(sym, aux_states, ctx, dtype=default_dtype()): function numeric_grad (line 965) | def numeric_grad(executor, location, aux_states=None, eps=1e-4, function check_numeric_gradient (line 1038) | def check_numeric_gradient(sym, location, aux_states=None, numeric_eps=N... function check_symbolic_forward (line 1188) | def check_symbolic_forward(sym, location, expected, rtol=None, atol=None, function check_symbolic_backward (line 1271) | def check_symbolic_backward(sym, location, out_grads, expected, rtol=Non... function check_speed (line 1411) | def check_speed(sym, location=None, ctx=None, N=20, grad_req=None, typ="... function check_consistency (line 1485) | def check_consistency(sym, ctx_list, scale=1.0, grad_req='write', function list_gpus (line 1680) | def list_gpus(): function download (line 1691) | def download(url, fname=None, dirname=None, overwrite=False, retries=5): function get_mnist (line 1762) | def get_mnist(path='data'): function get_mnist_ubyte (line 1796) | def get_mnist_ubyte(path='data'): function get_cifar10 (line 1813) | def get_cifar10(path='data'): function get_mnist_iterator (line 1830) | def get_mnist_iterator(batch_size, input_shape, num_parts=1, part_index=... function get_bz2_data (line 1858) | def get_bz2_data(data_dir, data_name, url, data_origin_name): function same_array (line 1892) | def same_array(array1, array2): function discard_stderr (line 1917) | def discard_stderr(): class DummyIter (line 1939) | class DummyIter(mx.io.DataIter): method __init__ (line 1948) | def __init__(self, real_iter): method __iter__ (line 1956) | def __iter__(self): method next (line 1959) | def next(self): function gen_buckets_probs_with_ppf (line 1970) | def gen_buckets_probs_with_ppf(ppf, nbuckets): function mean_check (line 1994) | def mean_check(generator, mu, sigma, nsamples=1000000): function get_im2rec_path (line 2033) | def get_im2rec_path(home_env="MXNET_HOME"): function var_check (line 2063) | def var_check(generator, sigma, nsamples=1000000): function chi_square_check (line 2102) | def chi_square_check(generator, buckets, probs, nsamples=1000000): function verify_generator (line 2180) | def verify_generator(generator, buckets, probs, nsamples=1000000, nrepea... function compare_ndarray_tuple (line 2228) | def compare_ndarray_tuple(t1, t2, rtol=None, atol=None): function compare_optimizer (line 2240) | def compare_optimizer(opt1, opt2, shapes, dtype, w_stype='default', g_st... function compare_optimizer_noise_seeded (line 2285) | def compare_optimizer_noise_seeded(opt1, opt2, shapes, dtype, noise_seed, function same_symbol_structure (line 2336) | def same_symbol_structure(sym1, sym2): function environment (line 2352) | def environment(*args): function collapse_sum_like (line 2426) | def collapse_sum_like(a, shape): function is_cd_run (line 2444) | def is_cd_run(): function has_tvm_ops (line 2452) | def has_tvm_ops(): function is_op_runnable (line 2470) | def is_op_runnable(): function check_gluon_hybridize_consistency (line 2492) | def check_gluon_hybridize_consistency(net_builder, data_l, numpy_func=No... function new_matrix_with_real_eigvals_2d (line 2558) | def new_matrix_with_real_eigvals_2d(n): function new_matrix_with_real_eigvals_nd (line 2577) | def new_matrix_with_real_eigvals_nd(shape): function new_orthonormal_matrix_2d (line 2583) | def new_orthonormal_matrix_2d(n): function new_sym_matrix_with_real_eigvals_2d (line 2591) | def new_sym_matrix_with_real_eigvals_2d(n): function new_sym_matrix_with_real_eigvals_nd (line 2598) | def new_sym_matrix_with_real_eigvals_nd(shape): FILE: python/mxnet/util.py function get_gpu_count (line 48) | def get_gpu_count(): function get_gpu_memory (line 54) | def get_gpu_memory(gpu_dev_id): function set_np_shape (line 61) | def set_np_shape(active): function is_np_shape (line 108) | def is_np_shape(): class _NumpyShapeScope (line 142) | class _NumpyShapeScope(object): method __init__ (line 157) | def __init__(self, is_np_shape): #pylint: disable=redefined-outer-name method __enter__ (line 161) | def __enter__(self): method __exit__ (line 165) | def __exit__(self, ptype, value, trace): function np_shape (line 170) | def np_shape(active=True): function use_np_shape (line 239) | def use_np_shape(func): function _sanity_check_params (line 314) | def _sanity_check_params(func_name, unsupported_params, param_dict): function set_module (line 321) | def set_module(module): class _NumpyArrayScope (line 339) | class _NumpyArrayScope(object): method __init__ (line 348) | def __init__(self, is_np_array): # pylint: disable=redefined-outer-name method __enter__ (line 352) | def __enter__(self): method __exit__ (line 359) | def __exit__(self, ptype, value, trace): function np_array (line 364) | def np_array(active=True): function is_np_array (line 393) | def is_np_array(): function use_np_array (line 416) | def use_np_array(func): function use_np (line 496) | def use_np(func): function np_ufunc_legal_option (line 558) | def np_ufunc_legal_option(key, value): function wrap_np_unary_func (line 593) | def wrap_np_unary_func(func): function wrap_np_binary_func (line 626) | def wrap_np_binary_func(func): function wrap_data_api_statical_func (line 656) | def wrap_data_api_statical_func(func): function wrap_data_api_linalg_func (line 679) | def wrap_data_api_linalg_func(func): function wrap_sort_functions (line 712) | def wrap_sort_functions(func): function wrap_ctx_to_device_func (line 737) | def wrap_ctx_to_device_func(func): function numpy_fallback (line 760) | def numpy_fallback(func): function _set_np_array (line 846) | def _set_np_array(active): function set_np (line 872) | def set_np(shape=True, array=True, dtype=False): function reset_np (line 959) | def reset_np(): function get_cuda_compute_capability (line 967) | def get_cuda_compute_capability(device): function default_array (line 1025) | def default_array(source_array, device=None, dtype=None): class _NumpyDefaultDtypeScope (line 1051) | class _NumpyDefaultDtypeScope(object): method __init__ (line 1066) | def __init__(self, is_np_default_dtype): #pylint: disable=redefined-o... method __enter__ (line 1070) | def __enter__(self): method __exit__ (line 1074) | def __exit__(self, ptype, value, trace): function np_default_dtype (line 1079) | def np_default_dtype(active=True): function use_np_default_dtype (line 1113) | def use_np_default_dtype(func): function is_np_default_dtype (line 1186) | def is_np_default_dtype(): function set_np_default_dtype (line 1218) | def set_np_default_dtype(is_np_default_dtype=True): # pylint: disable=r... function getenv (line 1259) | def getenv(name): function setenv (line 1277) | def setenv(name, value): function get_max_supported_compute_capability (line 1291) | def get_max_supported_compute_capability(): function get_rtc_compile_opts (line 1299) | def get_rtc_compile_opts(device): function set_flush_denorms (line 1314) | def set_flush_denorms(value): function dtype_from_number (line 1339) | def dtype_from_number(number): function TemporaryDirectory (line 1372) | def TemporaryDirectory(*args, **kwargs): FILE: python/mxnet/visualization.py function _str2tuple (line 31) | def _str2tuple(string): function print_summary (line 46) | def print_summary(symbol, shape=None, line_length=120, positions=[.44, .... function plot_network (line 210) | def plot_network(symbol, title="plot", save_format='pdf', shape=None, dt... FILE: python/setup.py function config_cython (line 62) | def config_cython(): FILE: src/api/_api_internal/_api_internal.cc type mxnet (line 35) | namespace mxnet { FILE: src/api/cached_op_api.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/numpy/linalg/np_det.cc type mxnet (line 28) | namespace mxnet { FILE: src/api/operator/numpy/linalg/np_eig.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/numpy/linalg/np_eigvals.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/linalg/np_gesvd.cc type mxnet (line 28) | namespace mxnet { FILE: src/api/operator/numpy/linalg/np_inv.cc type mxnet (line 28) | namespace mxnet { FILE: src/api/operator/numpy/linalg/np_lstsq.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/linalg/np_matrix_rank.cc type mxnet (line 29) | namespace mxnet { function _npi_matrix_rank_none_tol (line 31) | inline static void _npi_matrix_rank_none_tol(runtime::MXNetArgs args, ... function _npi_matrix_rank (line 49) | inline static void _npi_matrix_rank(runtime::MXNetArgs args, runtime::... FILE: src/api/operator/numpy/linalg/np_norm.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/linalg/np_pinv.cc type mxnet (line 29) | namespace mxnet { function _npi_pinv (line 31) | inline static void _npi_pinv(runtime::MXNetArgs args, runtime::MXNetRe... function _npi_pinv_scalar_rcond (line 47) | inline static void _npi_pinv_scalar_rcond(runtime::MXNetArgs args, run... FILE: src/api/operator/numpy/linalg/np_potrf.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/linalg/np_qr.cc type mxnet (line 28) | namespace mxnet { FILE: src/api/operator/numpy/linalg/np_slogdet.cc type mxnet (line 28) | namespace mxnet { FILE: src/api/operator/numpy/linalg/np_solve.cc type mxnet (line 28) | namespace mxnet { FILE: src/api/operator/numpy/linalg/np_tensorinv.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/linalg/np_tensorsolve.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/np_bincount_op.cc type mxnet (line 28) | namespace mxnet { FILE: src/api/operator/numpy/np_broadcast_reduce_op_boolean.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/numpy/np_broadcast_reduce_op_index.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/numpy/np_broadcast_reduce_op_value.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/numpy/np_cross.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/np_cumsum.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/np_delete_op.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/numpy/np_diff_op.cc type mxnet (line 28) | namespace mxnet { FILE: src/api/operator/numpy/np_dot_op.cc type mxnet (line 28) | namespace mxnet { FILE: src/api/operator/numpy/np_ediff1d_op.cc type mxnet (line 28) | namespace mxnet { FILE: src/api/operator/numpy/np_einsum_op.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/numpy/np_elemwise_broadcast_logic_op.cc type mxnet (line 30) | namespace mxnet { function SetUFuncHelper (line 47) | void SetUFuncHelper(runtime::MXNetArgs args, FILE: src/api/operator/numpy/np_elemwise_broadcast_op.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/np_elemwise_broadcast_op_extended_sec.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/numpy/np_elemwise_unary_op_basic.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/numpy/np_fill_diagonal_op.cc type mxnet (line 27) | namespace mxnet { FILE: src/api/operator/numpy/np_histogram_op.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/numpy/np_init_op.cc type mxnet (line 32) | namespace mxnet { FILE: src/api/operator/numpy/np_insert_op.cc type mxnet (line 33) | namespace mxnet { FILE: src/api/operator/numpy/np_interp_op.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/np_kron.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/np_matmul_op.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/np_matrix_op.cc type mxnet (line 32) | namespace mxnet { FILE: src/api/operator/numpy/np_memory_op.cc type mxnet (line 28) | namespace mxnet { FILE: src/api/operator/numpy/np_moments_op.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/numpy/np_nan_to_num_op.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/np_nonzero_op.cc type mxnet (line 28) | namespace mxnet { FILE: src/api/operator/numpy/np_ordering_op.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/np_pad_op.cc type mxnet (line 31) | namespace mxnet { function String2MXNetPadType (line 33) | inline int String2MXNetPadType(const std::string& s) { function BroadcastPadWidth (line 54) | inline Tuple> BroadcastPadWidth(int ndim, runtime::ADT adt) { FILE: src/api/operator/numpy/np_percentile_op.cc type mxnet (line 29) | namespace mxnet { function String2MXNetPercentileType (line 31) | inline int String2MXNetPercentileType(const std::string& s) { FILE: src/api/operator/numpy/np_polynomial_op.cc type mxnet (line 28) | namespace mxnet { FILE: src/api/operator/numpy/np_repeat_op.cc type mxnet (line 28) | namespace mxnet { FILE: src/api/operator/numpy/np_tensordot_op.cc type mxnet (line 28) | namespace mxnet { function _npi_tensordot_int_axes (line 30) | inline static void _npi_tensordot_int_axes(runtime::MXNetArgs args, ru... function _npi_tensordot (line 47) | inline static void _npi_tensordot(runtime::MXNetArgs args, runtime::MX... FILE: src/api/operator/numpy/np_trace_op.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/np_tri_op.cc type mxnet (line 28) | namespace mxnet { FILE: src/api/operator/numpy/np_tril_op.cc type mxnet (line 28) | namespace mxnet { FILE: src/api/operator/numpy/np_triu_op.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/np_unique_op.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/numpy/np_where_op.cc type mxnet (line 29) | namespace mxnet { function isScalar (line 31) | inline static bool isScalar(const runtime::MXNetArgValue& arg) { function _npi_where (line 35) | inline static void _npi_where(runtime::MXNetArgs args, runtime::MXNetR... function _npi_where_scalar1 (line 49) | inline static void _npi_where_scalar1(runtime::MXNetArgs args, function _npi_where_scalar2 (line 69) | inline static void _npi_where_scalar2(runtime::MXNetArgs args, runtime... FILE: src/api/operator/numpy/np_window_op.cc type mxnet (line 30) | namespace mxnet { function SetNumpyWindowsParam (line 32) | inline static void SetNumpyWindowsParam(runtime::MXNetArgs args, FILE: src/api/operator/numpy/random/np_choice_op.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/random/np_exponential_op.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/random/np_laplace_op.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/random/np_location_scale_op.cc type mxnet (line 30) | namespace mxnet { function scalar_number (line 32) | int scalar_number(const runtime::MXNetArgs& args) { FILE: src/api/operator/numpy/random/np_multinomial_op.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/numpy/random/np_pareto_op.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/random/np_power_op.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/random/np_rayleigh_op.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy/random/np_weibull_op.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy_extension/npx_activation_op.cc type mxnet (line 30) | namespace mxnet { function String2MXNetActType (line 32) | inline int String2MXNetActType(const std::string& s) { FILE: src/api/operator/numpy_extension/npx_arange_like_op.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/numpy_extension/npx_batch_dot_op.cc type mxnet (line 29) | namespace mxnet { function String2ForwardStype (line 31) | inline int String2ForwardStype(const std::string& s) { FILE: src/api/operator/numpy_extension/npx_batch_norm_op.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/numpy_extension/npx_broadcast_like_op.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/numpy_extension/npx_control_flow_op.cc type mxnet (line 31) | namespace mxnet { FILE: src/api/operator/numpy_extension/npx_convolution_op.cc type mxnet (line 30) | namespace mxnet { function String2Layout (line 32) | inline int String2Layout(const std::string& s) { function String2CudnnTune (line 51) | inline int String2CudnnTune(const std::string& s) { FILE: src/api/operator/numpy_extension/npx_deconvolution_op.cc type mxnet (line 30) | namespace mxnet { function String2Layout (line 32) | inline int String2Layout(const std::string& s) { function String2CudnnTune (line 51) | inline int String2CudnnTune(const std::string& s) { FILE: src/api/operator/numpy_extension/npx_dropout_op.cc type mxnet (line 29) | namespace mxnet { function String2Mode (line 31) | inline int String2Mode(const std::string& s) { FILE: src/api/operator/numpy_extension/npx_embedding_op.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy_extension/npx_fully_connected_op.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/numpy_extension/npx_group_norm_op.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/numpy_extension/npx_layer_norm_op.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/numpy_extension/npx_leaky_relu_op.cc type mxnet (line 30) | namespace mxnet { function String2ActType (line 32) | inline int String2ActType(const std::string& s) { FILE: src/api/operator/numpy_extension/npx_one_hot_op.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy_extension/npx_pick_op.cc type mxnet (line 29) | namespace mxnet { function String2PickMode (line 31) | inline int String2PickMode(const std::string& s) { FILE: src/api/operator/numpy_extension/npx_pooling_op.cc type mxnet (line 29) | namespace mxnet { function String2PoolingLayout (line 31) | inline int String2PoolingLayout(const std::string& s) { function String2PoolType (line 52) | inline int String2PoolType(const std::string& s) { function String2Convention (line 69) | inline int String2Convention(const std::string& s) { FILE: src/api/operator/numpy_extension/npx_rnn_op.cc type mxnet (line 29) | namespace mxnet { function String2ComputeMode (line 31) | inline int String2ComputeMode(const std::string& s) { FILE: src/api/operator/numpy_extension/npx_softmax_op.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/numpy_extension/npx_topk_op.cc type mxnet (line 29) | namespace mxnet { function String2ReturnType (line 31) | inline int String2ReturnType(const std::string& s) { FILE: src/api/operator/op_utils.cc type mxnet (line 29) | namespace mxnet { function MXNetTypeWithBool2String (line 31) | std::string MXNetTypeWithBool2String(int dtype) { function MXNetPercentileType2String (line 56) | std::string MXNetPercentileType2String(int interpolation) { FILE: src/api/operator/op_utils.h function namespace (line 29) | namespace mxnet { FILE: src/api/operator/random/np_gamma_op.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/random/np_normal_op.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/random/np_randint_op.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/random/np_uniform_op.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/random/shuffle_op.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/tensor/elemwise_binary_broadcast_op_extended.cc type mxnet (line 30) | namespace mxnet { FILE: src/api/operator/tensor/indexing_op.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/tensor/matrix_op.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/tensor/unravel.cc type mxnet (line 29) | namespace mxnet { FILE: src/api/operator/ufunc_helper.cc type mxnet (line 29) | namespace mxnet { function UFuncHelper (line 38) | void UFuncHelper(NDArray* lhs, function UFuncHelper (line 58) | void UFuncHelper(NDArray* lhs, function UFuncHelper (line 83) | void UFuncHelper(NDArray* lhs, function UFuncHelper (line 108) | void UFuncHelper(int64_t lhs, function UFuncHelper (line 133) | void UFuncHelper(double lhs, function UFuncHelper (line 158) | void UFuncHelper(runtime::MXNetArgs args, function UFuncHelper (line 188) | void UFuncHelper(runtime::MXNetArgs args, runtime::MXNetRetValue* ret,... FILE: src/api/operator/ufunc_helper.h function namespace (line 27) | namespace mxnet { FILE: src/api/operator/utils.cc type mxnet (line 27) | namespace mxnet { function is_recording (line 29) | bool is_recording() { function is_deferred_compute (line 33) | bool is_deferred_compute() { function SetInOut (line 37) | void SetInOut(std::vector* ndinputs, function Invoke (line 79) | std::vector Invoke(const nnvm::Op* op, FILE: src/api/operator/utils.h function namespace (line 32) | namespace mxnet { FILE: src/base.cc type mxnet (line 26) | namespace mxnet { FILE: src/c_api/c_api.cc function MXAPIGetFunctionRegInfo (line 92) | inline int MXAPIGetFunctionRegInfo(const FunRegType* e, function getExtensionMsgs (line 126) | std::string getExtensionMsgs(mxnet::ext::msgSize_t msgSize, mxnet::ext::... function CustomFComputeDispatcher (line 145) | void CustomFComputeDispatcher(const std::string op_name, function registerOp (line 447) | void registerOp(const char* name, function registerOperators (line 682) | void registerOperators(void* lib, function registerPartitioners (line 1430) | void registerPartitioners(void* lib, function registerPasses (line 1529) | void registerPasses(void* lib, function MXLoadLib (line 1795) | int MXLoadLib(const char* path, unsigned verbose, void** lib) { function MXLibInfoFeatures (line 1830) | int MXLibInfoFeatures(const struct LibFeature** lib_features, size_t* si... function MXLibInfoCompiledWithCXX11ABI (line 1839) | int MXLibInfoCompiledWithCXX11ABI(int* result) { function MXRandomSeed (line 1849) | int MXRandomSeed(int seed) { function MXRandomSeedContext (line 1855) | int MXRandomSeedContext(int seed, int dev_type, int dev_id) { function MXSetFlushDenorms (line 1862) | int MXSetFlushDenorms(bool value, bool* prev_state) { function MXNotifyShutdown (line 1913) | int MXNotifyShutdown() { function MXSetNumOMPThreads (line 1921) | int MXSetNumOMPThreads(int thread_num) { function MXEngineSetBulkSize (line 1927) | int MXEngineSetBulkSize(int bulk_size, int* prev_bulk_size) { function MXGetGPUCount (line 1933) | int MXGetGPUCount(int* out) { function MXGetGPUMemoryInformation (line 1940) | int MXGetGPUMemoryInformation(int dev, int* free_mem, int* total_mem) { function MXGetGPUMemoryInformation64 (line 1950) | int MXGetGPUMemoryInformation64(int dev, uint64_t* free_mem, uint64_t* t... function MXGetVersion (line 1956) | int MXGetVersion(int* out) { function MXGetBranch (line 1962) | int MXGetBranch(const char** out) { function MXGetCommitHash (line 1968) | int MXGetCommitHash(const char** out) { function MXLoadTVMOp (line 1975) | int MXLoadTVMOp(const char* libpath) { function MXLoadTVMConfig (line 1990) | int MXLoadTVMConfig(ConfigSpaces config) { function MXNDArrayCreateNone (line 2015) | int MXNDArrayCreateNone(NDArrayHandle* out) { function CreateNDArray (line 2022) | void CreateNDArray(const DataType* shape, function MXNDArrayCreate64 (line 2044) | int MXNDArrayCreate64(const int64_t* shape, function MXNDArrayCreate (line 2056) | int MXNDArrayCreate(const uint32_t* shape, function CreateSparseNDArray (line 2069) | void CreateSparseNDArray(int storage_type, function MXNDArrayCreateSparseEx (line 2103) | int MXNDArrayCreateSparseEx(int storage_type, function MXNDArrayCreateSparseEx64 (line 2131) | int MXNDArrayCreateSparseEx64(int storage_type, function MXNDArrayLoadFromRawBytes (line 2159) | int MXNDArrayLoadFromRawBytes(const void* buf, size_t size, NDArrayHandl... function MXNDArraySaveRawBytes (line 2171) | int MXNDArraySaveRawBytes(NDArrayHandle handle, size_t* out_size, const ... function MXNDArraySyncCopyFromCPU (line 2182) | int MXNDArraySyncCopyFromCPU(NDArrayHandle handle, const void* data, siz... function MXNDArraySyncCopyToCPU (line 2188) | int MXNDArraySyncCopyToCPU(NDArrayHandle handle, void* data, size_t size) { function MXNDArraySyncCopyFromNDArray (line 2201) | int MXNDArraySyncCopyFromNDArray(NDArrayHandle handle_dst, function MXNDArraySyncCheckFormat (line 2211) | int MXNDArraySyncCheckFormat(NDArrayHandle handle, const bool full_check) { function MXNDArrayWaitToRead (line 2218) | int MXNDArrayWaitToRead(NDArrayHandle handle) { function MXNDArrayWaitToWrite (line 2224) | int MXNDArrayWaitToWrite(NDArrayHandle handle) { function MXNDArrayWaitAll (line 2230) | int MXNDArrayWaitAll() { function MXNDArrayLegacySave (line 2236) | int MXNDArrayLegacySave(const char* fname, function MXNDArraySave (line 2259) | int MXNDArraySave(const char* fname, uint32_t num_args, NDArrayHandle* a... function MXNDArrayLoad (line 2303) | int MXNDArrayLoad(const char* fname, function MXNDArrayLoadFromBuffer (line 2372) | int MXNDArrayLoadFromBuffer(const void* ndarray_buffer, function MXNDArrayFree (line 2406) | int MXNDArrayFree(NDArrayHandle handle) { function SliceArray (line 2413) | void SliceArray(NDArrayHandle handle, function MXNDArraySlice (line 2422) | int MXNDArraySlice(NDArrayHandle handle, function MXNDArraySlice64 (line 2432) | int MXNDArraySlice64(NDArrayHandle handle, function MXNDArrayAt (line 2442) | int MXNDArrayAt(NDArrayHandle handle, uint32_t idx, NDArrayHandle* out) { function MXNDArrayAt64 (line 2450) | int MXNDArrayAt64(NDArrayHandle handle, int64_t idx, NDArrayHandle* out) { function MXNDArrayReshape (line 2458) | int MXNDArrayReshape(NDArrayHandle handle, int ndim, int* dims, NDArrayH... function MXNDArrayReshape64 (line 2488) | int MXNDArrayReshape64(NDArrayHandle handle, function MXNDArrayGetStorageType (line 2503) | int MXNDArrayGetStorageType(NDArrayHandle handle, int* out_storage_type) { function GetShape (line 2515) | inline void GetShape(NDArrayHandle handle, function MXNDArrayGetShape (line 2555) | int MXNDArrayGetShape(NDArrayHandle handle, int* out_dim, const int** ou... function MXNDArrayGetShape64 (line 2562) | int MXNDArrayGetShape64(NDArrayHandle handle, int* out_dim, const int64_... function MXNDArrayGetData (line 2569) | int MXNDArrayGetData(NDArrayHandle handle, void** out_pdata) { function MXNDArrayToDLPack (line 2586) | int MXNDArrayToDLPack(NDArrayHandle handle, DLManagedTensorHandle* out_d... function MXNDArrayFromDLPack (line 2593) | int MXNDArrayFromDLPack(DLManagedTensorHandle dlpack, function MXNDArrayCallDLPackDeleter (line 2602) | int MXNDArrayCallDLPackDeleter(DLManagedTensorHandle dlpack) { function MXNDArrayGetDType (line 2611) | int MXNDArrayGetDType(NDArrayHandle handle, int* out_dtype) { function MXNDArrayGetAuxType (line 2622) | int MXNDArrayGetAuxType(NDArrayHandle handle, uint32_t i, int* out_type) { function MXNDArrayGetAuxNDArray (line 2634) | int MXNDArrayGetAuxNDArray(NDArrayHandle handle, uint32_t i, NDArrayHand... function MXNDArrayGetDataNDArray (line 2646) | int MXNDArrayGetDataNDArray(NDArrayHandle handle, NDArrayHandle* out) { function MXNDArrayGetContext (line 2653) | int MXNDArrayGetContext(NDArrayHandle handle, int* out_dev_type, int* ou... function MXNDArrayGetGrad (line 2667) | int MXNDArrayGetGrad(NDArrayHandle handle, NDArrayHandle* out) { function MXNDArrayDetach (line 2679) | int MXNDArrayDetach(NDArrayHandle handle, NDArrayHandle* out) { function MXNDArraySetGradState (line 2686) | int MXNDArraySetGradState(NDArrayHandle handle, int state) { function MXNDArrayGetGradState (line 2693) | int MXNDArrayGetGradState(NDArrayHandle handle, int* out) { function MXListFunctions (line 2700) | int MXListFunctions(uint32_t* out_size, FunctionHandle** out_array) { function MXGetFunction (line 2708) | int MXGetFunction(const char* name, FunctionHandle* out) { function MXFuncGetInfo (line 2714) | int MXFuncGetInfo(FunctionHandle fun, function MXFuncDescribe (line 2732) | int MXFuncDescribe(FunctionHandle fun, function MXFuncInvoke (line 2746) | int MXFuncInvoke(FunctionHandle fun, function MXListDataIters (line 2767) | int MXListDataIters(uint32_t* out_size, DataIterCreator** out_array) { function MXDataIterGetIterInfo (line 2775) | int MXDataIterGetIterInfo(DataIterCreator creator, function MXDataIterCreateIter (line 2787) | int MXDataIterCreateIter(DataIterCreator creator, function MXDataIterFree (line 2805) | int MXDataIterFree(DataIterHandle handle) { function MXDataIterBeforeFirst (line 2811) | int MXDataIterBeforeFirst(DataIterHandle handle) { function MXDataIterGetLenHint (line 2817) | int MXDataIterGetLenHint(DataIterHandle handle, int64_t* len) { function MXDataIterNext (line 2823) | int MXDataIterNext(DataIterHandle handle, int* out) { function MXDataIterGetLabel (line 2829) | int MXDataIterGetLabel(DataIterHandle handle, NDArrayHandle* out) { function MXDataIterGetItems (line 2853) | int MXDataIterGetItems(DataIterHandle handle, int* num_outputs, NDArrayH... function MXDataIterGetIndex (line 2886) | int MXDataIterGetIndex(DataIterHandle handle, uint64_t** out_index, uint... function MXDataIterGetData (line 2894) | int MXDataIterGetData(DataIterHandle handle, NDArrayHandle* out) { function MXDataIterGetPadNum (line 2903) | int MXDataIterGetPadNum(DataIterHandle handle, int* pad) { function MXListDatasets (line 2910) | int MXListDatasets(uint32_t* out_size, DatasetCreator** out_array) { function MXDatasetCreateDataset (line 2918) | int MXDatasetCreateDataset(DatasetCreator handle, function MXDatasetGetDatasetInfo (line 2935) | int MXDatasetGetDatasetInfo(DatasetCreator creator, function MXDatasetFree (line 2947) | int MXDatasetFree(DatasetHandle handle) { function MXDatasetGetLen (line 2953) | int MXDatasetGetLen(DatasetHandle handle, uint64_t* out) { function MXDatasetGetItems (line 2960) | int MXDatasetGetItems(DatasetHandle handle, function MXListBatchifyFunctions (line 2997) | int MXListBatchifyFunctions(uint32_t* out_size, BatchifyFunctionCreator*... function MXBatchifyFunctionCreateFunction (line 3005) | int MXBatchifyFunctionCreateFunction(BatchifyFunctionCreator handle, function MXBatchifyFunctionGetFunctionInfo (line 3022) | int MXBatchifyFunctionGetFunctionInfo(BatchifyFunctionCreator creator, function MXBatchifyFunctionInvoke (line 3033) | int MXBatchifyFunctionInvoke(BatchifyFunctionHandle handle, function MXBatchifyFunctionFree (line 3085) | int MXBatchifyFunctionFree(BatchifyFunctionHandle handle) { function MXKVStoreCreate (line 3094) | int MXKVStoreCreate(const char* type, KVStoreHandle* out) { function MXKVStoreSetGradientCompression (line 3100) | int MXKVStoreSetGradientCompression(KVStoreHandle handle, function MXKVStoreFree (line 3116) | int MXKVStoreFree(KVStoreHandle handle) { function MXKVStoreInit (line 3122) | int MXKVStoreInit(KVStoreHandle handle, uint32_t num, const int* keys, N... function MXKVStoreInitEx (line 3134) | int MXKVStoreInitEx(KVStoreHandle handle, uint32_t num, const char** key... function MXKVStorePush (line 3146) | int MXKVStorePush(KVStoreHandle handle, function MXKVStorePushEx (line 3162) | int MXKVStorePushEx(KVStoreHandle handle, function MXKVStorePull (line 3178) | int MXKVStorePull(KVStoreHandle handle, function MXKVStorePullEx (line 3194) | int MXKVStorePullEx(KVStoreHandle handle, function MXKVStoreBroadcast (line 3210) | int MXKVStoreBroadcast(KVStoreHandle handle, function MXKVStoreBroadcastEx (line 3235) | int MXKVStoreBroadcastEx(KVStoreHandle handle, function MXKVStorePushPull (line 3260) | int MXKVStorePushPull(KVStoreHandle handle, function MXKVStorePushPullEx (line 3285) | int MXKVStorePushPullEx(KVStoreHandle handle, function MXKVStorePullWithSparse (line 3310) | int MXKVStorePullWithSparse(KVStoreHandle handle, function MXKVStorePullWithSparseEx (line 3327) | int MXKVStorePullWithSparseEx(KVStoreHandle handle, function MXKVStorePullRowSparse (line 3344) | int MXKVStorePullRowSparse(KVStoreHandle handle, function MXKVStorePullRowSparseEx (line 3362) | int MXKVStorePullRowSparseEx(KVStoreHandle handle, function MXKVStoreSetUpdaterImpl (line 3380) | void MXKVStoreSetUpdaterImpl(KVStoreHandle handle, MXKVStoreUpdater upda... function MXKVStoreSetUpdater (line 3394) | int MXKVStoreSetUpdater(KVStoreHandle handle, MXKVStoreUpdater updater, ... function MXKVStoreSetUpdaterEx (line 3400) | int MXKVStoreSetUpdaterEx(KVStoreHandle handle, function MXKVStoreGetRank (line 3423) | int MXKVStoreGetRank(KVStoreHandle handle, int* rank) { function MXKVStoreGetGroupSize (line 3429) | int MXKVStoreGetGroupSize(KVStoreHandle handle, int* size) { function MXKVStoreBarrier (line 3435) | int MXKVStoreBarrier(KVStoreHandle handle) { function MXKVStoreSetBarrierBeforeExit (line 3441) | int MXKVStoreSetBarrierBeforeExit(KVStoreHandle handle, const int barrie... function MXInitPSEnv (line 3447) | int MXInitPSEnv(uint32_t num_vars, const char** keys, const char** vals) { function MXKVStoreIsWorkerNode (line 3457) | int MXKVStoreIsWorkerNode(int* ret) { function MXKVStoreIsServerNode (line 3463) | int MXKVStoreIsServerNode(int* ret) { function MXKVStoreIsSchedulerNode (line 3469) | int MXKVStoreIsSchedulerNode(int* ret) { function MXKVStoreRunServer (line 3475) | int MXKVStoreRunServer(KVStoreHandle handle, function MXKVStoreSendCommmandToServers (line 3488) | int MXKVStoreSendCommmandToServers(KVStoreHandle handle, int cmd_id, con... function MXKVStoreGetType (line 3494) | int MXKVStoreGetType(KVStoreHandle handle, const char** type) { function MXKVStoreGetNumDeadNode (line 3500) | int MXKVStoreGetNumDeadNode(KVStoreHandle handle, type MXRecordIOContext (line 3509) | struct MXRecordIOContext { function MXRecordIOWriterCreate (line 3516) | int MXRecordIOWriterCreate(const char* uri, RecordIOHandle* out) { function MXRecordIOWriterFree (line 3528) | int MXRecordIOWriterFree(RecordIOHandle handle) { function MXRecordIOWriterWriteRecord (line 3537) | int MXRecordIOWriterWriteRecord(RecordIOHandle handle, const char* buf, ... function MXRecordIOWriterTell (line 3544) | int MXRecordIOWriterTell(RecordIOHandle handle, size_t* pos) { function MXRecordIOReaderCreate (line 3551) | int MXRecordIOReaderCreate(const char* uri, RecordIOHandle* out) { function MXRecordIOReaderFree (line 3563) | int MXRecordIOReaderFree(RecordIOHandle handle) { function MXRecordIOReaderReadRecord (line 3573) | int MXRecordIOReaderReadRecord(RecordIOHandle handle, char const** buf, ... function MXRecordIOReaderSeek (line 3586) | int MXRecordIOReaderSeek(RecordIOHandle handle, size_t pos) { function MXRecordIOReaderTell (line 3593) | int MXRecordIOReaderTell(RecordIOHandle handle, size_t* pos) { function MXRtcCreate (line 3600) | int MXRtcCreate(char* name, function MXRtcPush (line 3614) | int MXRtcPush(RtcHandle handle, function MXRtcFree (line 3630) | int MXRtcFree(RtcHandle handle) { function MXCustomOpRegister (line 3636) | int MXCustomOpRegister(const char* op_type, CustomOpPropCreator creator) { function MXRtcCudaModuleCreate (line 3642) | int MXRtcCudaModuleCreate(const char* source, function MXRtcCudaModuleFree (line 3663) | int MXRtcCudaModuleFree(CudaModuleHandle handle) { function MXRtcCudaKernelCreate (line 3673) | int MXRtcCudaKernelCreate(CudaModuleHandle handle, function MXRtcCudaKernelFree (line 3697) | int MXRtcCudaKernelFree(CudaKernelHandle handle) { function MXRtcCudaKernelCall (line 3707) | int MXRtcCudaKernelCall(CudaKernelHandle handle, function MXNDArrayGetSharedMemHandle (line 3745) | int MXNDArrayGetSharedMemHandle(NDArrayHandle handle, int* shared_pid, i... function MXNDArrayCreateFromSharedMem (line 3765) | int MXNDArrayCreateFromSharedMem(int shared_pid, function AssertValidNumberVars (line 3783) | void AssertValidNumberVars(int num_const_vars, int num_mutable_vars) { function MXEnginePushAsync (line 3788) | int MXEnginePushAsync(EngineAsyncFunc async_func, function MXEnginePushSync (line 3835) | int MXEnginePushSync(EngineSyncFunc sync_func, function MXEnginePushAsyncND (line 3877) | int MXEnginePushAsyncND(EngineAsyncFunc async_func, function MXEnginePushSyncND (line 3913) | int MXEnginePushSyncND(EngineSyncFunc sync_func, function MXStorageEmptyCache (line 3947) | int MXStorageEmptyCache(int dev_type, int dev_id) { function MXShallowCopyNDArray (line 3954) | int MXShallowCopyNDArray(NDArrayHandle src_handle, NDArrayHandle* out) { function MXPushStreamDep (line 3963) | int MXPushStreamDep(NDArrayHandle handle, int stream) { function MXGetCurrentStream (line 3969) | int MXGetCurrentStream(int device_id, int* stream) { function MXNVTXRangePush (line 3981) | int MXNVTXRangePush(const char* name, mx_uint color) { function MXNVTXRangePop (line 3991) | int MXNVTXRangePop() { function MXCUDAProfilerStart (line 4001) | int MXCUDAProfilerStart() { function MXCUDAProfilerStop (line 4011) | int MXCUDAProfilerStop() { function MXSetOptimizeLayout (line 4021) | int MXSetOptimizeLayout(bool val) { function MXGetOptimizeLayout (line 4027) | int MXGetOptimizeLayout(bool* val) { FILE: src/c_api/c_api_common.h function SetupShapeArrayReturnWithBuffer (line 93) | inline static void SetupShapeArrayReturnWithBuffer(const mxnet::ShapeVec... function SetupShapeArrayReturnWithBufferEx (line 111) | inline static void SetupShapeArrayReturnWithBufferEx(const mxnet::ShapeV... function CopyAttr (line 142) | void CopyAttr(const nnvm::IndexedGraph& idx, FILE: src/c_api/c_api_function.cc type mxnet (line 34) | namespace mxnet { type custom_function (line 35) | namespace custom_function { type CustomFunctionParam (line 37) | struct CustomFunctionParam { function Gradient (line 44) | std::vector Gradient(const nnvm::ObjectPtr& n, function OpStatePtr (line 64) | OpStatePtr CreateState(const nnvm::NodeAttrs& attrs, function Forward (line 72) | void Forward(const OpStatePtr& state, function Backward (line 80) | void Backward(const OpStatePtr& state, function InferStorageType (line 128) | inline bool InferStorageType(const nnvm::NodeAttrs& attrs, function MXCustomFunctionRecord (line 193) | int MXCustomFunctionRecord(int num_inputs, FILE: src/c_api/c_api_ndarray.cc function SetNDInputsOutputs (line 44) | void SetNDInputsOutputs(const nnvm::Op* op, function MXImperativeInvokeImpl (line 89) | void MXImperativeInvokeImpl(AtomicSymbolCreator creator, function MXImperativeInvoke (line 146) | int MXImperativeInvoke(AtomicSymbolCreator creator, function MXCreateCachedOp (line 171) | int MXCreateCachedOp(SymbolHandle handle, function MXFreeCachedOp (line 192) | int MXFreeCachedOp(CachedOpHandle handle) { function MXCachedOpGetOptimizedSymbol (line 202) | int MXCachedOpGetOptimizedSymbol(CachedOpHandle handle, SymbolHandle* ou... function MXInvokeCachedOp (line 211) | int MXInvokeCachedOp(CachedOpHandle handle, function MXAutogradIsTraining (line 270) | int MXAutogradIsTraining(bool* curr) { function MXAutogradSetIsTraining (line 276) | int MXAutogradSetIsTraining(int is_training, int* prev) { function MXAutogradIsRecording (line 282) | int MXAutogradIsRecording(bool* curr) { function MXAutogradSetIsRecording (line 288) | int MXAutogradSetIsRecording(int is_recording, int* prev) { function MXSetOptimizationConstraints (line 294) | int MXSetOptimizationConstraints(unsigned int constraints, unsigned int*... function MXGetOptimizationConstraints (line 301) | int MXGetOptimizationConstraints(unsigned int* curr) { function MXIsNumpyShape (line 307) | int MXIsNumpyShape(int* curr) { function MXSetIsNumpyShape (line 313) | int MXSetIsNumpyShape(int is_np_shape, int* prev) { function MXIsNumpyDefaultDtype (line 319) | int MXIsNumpyDefaultDtype(bool* curr) { function MXSetIsNumpyDefaultDtype (line 325) | int MXSetIsNumpyDefaultDtype(bool default_dtype, bool* prev) { function MXAutogradMarkVariables (line 331) | int MXAutogradMarkVariables(uint32_t num_var, function MXAutogradDropGrads (line 350) | int MXAutogradDropGrads(uint32_t num_var, NDArrayHandle* var_handles) { function MXAutogradComputeGradient (line 361) | int MXAutogradComputeGradient(uint32_t num_output, NDArrayHandle* output... function MXAutogradBackward (line 365) | int MXAutogradBackward(uint32_t num_output, function MXAutogradBackwardEx (line 381) | int MXAutogradBackwardEx(uint32_t num_output, function MXAutogradGetSymbol (line 431) | int MXAutogradGetSymbol(NDArrayHandle handle, SymbolHandle* out) { function MXCachedOpRegisterOpHook (line 439) | int MXCachedOpRegisterOpHook(CachedOpHandle handle, function MXNDArrayIsDeferredCompute (line 458) | int MXNDArrayIsDeferredCompute(int* curr) { function MXNDArraySetIsDeferredCompute (line 464) | int MXNDArraySetIsDeferredCompute(int deferred_compute, int* prev) { function MXNDArraySetDeferredComputeVariable (line 470) | int MXNDArraySetDeferredComputeVariable(NDArrayHandle* arrays, SymbolHan... function MXNDArrayClearDeferredCompute (line 476) | int MXNDArrayClearDeferredCompute(NDArrayHandle* arrays, int num) { function MXNDArrayGetDeferredComputeSymbol (line 482) | int MXNDArrayGetDeferredComputeSymbol(NDArrayHandle* output_handles, FILE: src/c_api/c_api_profile.cc type mxnet (line 37) | namespace mxnet { type APICallTimingData (line 44) | struct APICallTimingData { class ProfilingThreadData (line 52) | class ProfilingThreadData { method ProfilingThreadData (line 57) | inline ProfilingThreadData() = default; function on_enter_api (line 93) | extern void on_enter_api(const char* function) { function on_exit_api (line 105) | extern void on_exit_api() { type IgnoreProfileCallScope (line 120) | struct IgnoreProfileCallScope { method IgnoreProfileCallScope (line 121) | IgnoreProfileCallScope() { type PythonProfileObjects (line 141) | struct PythonProfileObjects { type ProfileProcess (line 160) | enum class ProfileProcess { kWorker, kServer } type PrintFormat (line 162) | enum class PrintFormat { table, json } type ProfileConfigParam (line 164) | struct ProfileConfigParam : public dmlc::Parameter { method DMLC_DECLARE_PARAMETER (line 176) | DMLC_DECLARE_PARAMETER(ProfileConfigParam) { type ProfileMarkerScopeParam (line 224) | struct ProfileMarkerScopeParam : public dmlc::Parameter ReadOnlyArgIndices(const nnvm::IndexedGraph& idx) { function MatchArguments (line 503) | void MatchArguments(const nnvm::IndexedGraph& idx, function MXListAllOpNames (line 81) | int MXListAllOpNames(nn_uint* out_size, const char*** out_array) { function MXSymbolListAtomicSymbolCreators (line 87) | int MXSymbolListAtomicSymbolCreators(uint32_t* out_size, AtomicSymbolCre... function MXSymbolGetAtomicSymbolInfo (line 93) | int MXSymbolGetAtomicSymbolInfo(AtomicSymbolCreator creator, function MXSymbolCreateAtomicSymbol (line 122) | int MXSymbolCreateAtomicSymbol(AtomicSymbolCreator creator, function MXSymbolCreateVariable (line 156) | int MXSymbolCreateVariable(const char* name, SymbolHandle* out) { function MXSymbolCreateGroup (line 160) | int MXSymbolCreateGroup(uint32_t num_symbols, SymbolHandle* symbols, Sym... function MXSymbolGetOutput (line 164) | int MXSymbolGetOutput(SymbolHandle symbol, uint32_t index, SymbolHandle*... function MXSymbolGetInputs (line 168) | int MXSymbolGetInputs(SymbolHandle symbol, SymbolHandle* out) { function MXSymbolGetInternals (line 181) | int MXSymbolGetInternals(SymbolHandle symbol, SymbolHandle* out) { function MXSymbolGetChildren (line 189) | int MXSymbolGetChildren(SymbolHandle symbol, SymbolHandle* out) { function MXSymbolFree (line 197) | int MXSymbolFree(SymbolHandle symbol) { function MXSymbolCopy (line 201) | int MXSymbolCopy(SymbolHandle symbol, SymbolHandle* out) { function MXSymbolPrint (line 205) | int MXSymbolPrint(SymbolHandle symbol, const char** out_str) { function MXSymbolGetName (line 209) | int MXSymbolGetName(SymbolHandle symbol, const char** out, int* success) { function MXSymbolGetAttr (line 213) | int MXSymbolGetAttr(SymbolHandle symbol, const char* key, const char** o... function MXSymbolSetAttr (line 234) | int MXSymbolSetAttr(SymbolHandle symbol, const char* key, const char* va... function MXSymbolListAttr (line 257) | int MXSymbolListAttr(SymbolHandle symbol, uint32_t* out_size, const char... function MXSymbolListAttrShallow (line 284) | int MXSymbolListAttrShallow(SymbolHandle symbol, uint32_t* out_size, con... function MXSymbolListOutputs (line 311) | int MXSymbolListOutputs(SymbolHandle symbol, uint32_t* out_size, const c... function MXSymbolGetNumOutputs (line 315) | int MXSymbolGetNumOutputs(SymbolHandle symbol, uint32_t* output_count) { function MXSymbolCompose (line 319) | int MXSymbolCompose(SymbolHandle sym, function MXSymbolListArguments (line 328) | int MXSymbolListArguments(SymbolHandle symbol, uint32_t* out_size, const... function MXSymbolListAuxiliaryStates (line 332) | int MXSymbolListAuxiliaryStates(SymbolHandle symbol, function MXSymbolGetAtomicSymbolName (line 338) | int MXSymbolGetAtomicSymbolName(AtomicSymbolCreator creator, const char*... type mxnet (line 345) | namespace mxnet { type op (line 38) | namespace op { function Symbol2Graph (line 55) | nnvm::Graph Symbol2Graph(const nnvm::Symbol& s) { function ReadOnlyArgIndices (line 66) | std::vector ReadOnlyArgIndices(const nnvm::IndexedGraph& idx) { function MatchArguments (line 503) | void MatchArguments(const nnvm::IndexedGraph& idx, function MXSymbolGetInputSymbols (line 354) | int MXSymbolGetInputSymbols(SymbolHandle sym, SymbolHandle** input_arr, ... function MXSymbolCutSubgraph (line 369) | int MXSymbolCutSubgraph(SymbolHandle sym, SymbolHandle** input_symbols, ... function ConvertShapeAttrToNumPyCompatible (line 422) | void ConvertShapeAttrToNumPyCompatible(nnvm::Graph* g) { function MXSymbolCreateFromFile (line 442) | int MXSymbolCreateFromFile(const char* fname, SymbolHandle* out) { function MXSymbolCreateFromJSON (line 458) | int MXSymbolCreateFromJSON(const char* json, SymbolHandle* out) { function MXSymbolRemoveAmpCast (line 470) | int MXSymbolRemoveAmpCast(SymbolHandle sym_handle, SymbolHandle* ret_sym... function MXSymbolSaveToFile (line 480) | int MXSymbolSaveToFile(SymbolHandle symbol, const char* fname) { function MXSymbolSaveToJSON (line 491) | int MXSymbolSaveToJSON(SymbolHandle symbol, const char** out_json) { type mxnet (line 500) | namespace mxnet { type op (line 38) | namespace op { function Symbol2Graph (line 55) | nnvm::Graph Symbol2Graph(const nnvm::Symbol& s) { function ReadOnlyArgIndices (line 66) | std::vector ReadOnlyArgIndices(const nnvm::IndexedGraph& idx) { function MatchArguments (line 503) | void MatchArguments(const nnvm::IndexedGraph& idx, function SymbolInferShape (line 539) | inline void SymbolInferShape(const char** keys, function MXSymbolInferShape (line 631) | int MXSymbolInferShape(SymbolHandle sym, function MXSymbolInferShape64 (line 689) | int MXSymbolInferShape64(SymbolHandle sym, function MXSymbolInferShapePartial (line 747) | int MXSymbolInferShapePartial(SymbolHandle sym, function MXSymbolInferShapePartial64 (line 802) | int MXSymbolInferShapePartial64(SymbolHandle sym, function MXSymbolInferType (line 836) | int MXSymbolInferType(SymbolHandle sym, function MXSymbolInferTypePartial (line 884) | int MXSymbolInferTypePartial(SymbolHandle sym, function MXSymbolGrad (line 910) | int MXSymbolGrad(SymbolHandle sym, uint32_t num_wrt, const char** wrt, S... function MXQuantizeSymbol (line 916) | int MXQuantizeSymbol(SymbolHandle sym_handle, function MXReducePrecisionSymbol (line 974) | int MXReducePrecisionSymbol(SymbolHandle sym_handle, function MXSetCalibTableToQuantizedSymbol (line 1031) | int MXSetCalibTableToQuantizedSymbol(SymbolHandle qsym_handle, function MXGenBackendSubgraph (line 1052) | int MXGenBackendSubgraph(SymbolHandle sym_handle, function MXGenAtomicSymbolFromSymbol (line 1083) | int MXGenAtomicSymbolFromSymbol(SymbolHandle sym_handle, SymbolHandle* r... function MXShallowCopySymbol (line 1101) | int MXShallowCopySymbol(SymbolHandle src, SymbolHandle* out) { function MXOptimizeForBackend (line 1110) | int MXOptimizeForBackend(SymbolHandle sym_handle, function MXCheckDynamicShapeOp (line 1344) | int MXCheckDynamicShapeOp(SymbolHandle sym_handle, bool* has_dynamic_sha... FILE: src/c_api/c_api_test.cc function MXBuildSubgraphByOpNames (line 30) | int MXBuildSubgraphByOpNames(SymbolHandle sym_handle, function MXSetSubgraphPropertyOpNames (line 64) | int MXSetSubgraphPropertyOpNames(const char* prop_name, function MXSetSubgraphPropertyOpNamesV2 (line 76) | int MXSetSubgraphPropertyOpNamesV2(const char* prop_name, function MXRemoveSubgraphPropertyOpNames (line 92) | int MXRemoveSubgraphPropertyOpNames(const char* prop_name) { function MXRemoveSubgraphPropertyOpNamesV2 (line 98) | int MXRemoveSubgraphPropertyOpNamesV2(const char* prop_name) { function MXGetEnv (line 108) | int MXGetEnv(const char* name, const char** value) { function MXSetEnv (line 114) | int MXSetEnv(const char* name, const char* value) { function MXGetMaxSupportedArch (line 128) | int MXGetMaxSupportedArch(uint32_t* max_arch) { FILE: src/common/alm.cc type mxnet (line 37) | namespace mxnet { type alm (line 38) | namespace alm { function CreateTransposeNode (line 42) | nnvm::ObjectPtr CreateTransposeNode(const std::string& name, const a... function TargetLayout (line 54) | mshadow::LayoutFlag TargetLayout(const nnvm::ObjectPtr& node) { function OptimizeLayout (line 81) | nnvm::Graph OptimizeLayout(nnvm::Graph&& g) { function Transpose (line 147) | Transpose Reverse(const Transpose& axes) { function Transpose (line 154) | Transpose Compose(const Transpose& lhs, const Transpose& rhs) { function IsIdentity (line 166) | bool IsIdentity(const Transpose& t) { function ApplyTranspose (line 174) | mshadow::LayoutFlag ApplyTranspose(mshadow::LayoutFlag layout, const... function ApplyTranspose (line 180) | std::string ApplyTranspose(const std::string& layout, const Transpos... function Transpose (line 187) | Transpose FromTShape(const mxnet::TShape& s) { function Transpose (line 193) | Transpose FactorCommonTranspose(std::vector* axes) { FILE: src/common/alm.h function namespace (line 37) | namespace mxnet { FILE: src/common/cuda/cudnn_cxx.cc type mxnet (line 33) | namespace mxnet { type cudnn_cxx (line 34) | namespace cudnn_cxx { function Descriptor (line 36) | Descriptor Make(cudnnBackendDescriptorType_t type) { function MakeRawDescriptors (line 42) | std::vector MakeRawDescriptors(size_t n, function SetAttr (line 50) | void SetAttr(const Descriptor& desc, cudnnBackendAttributeName_t nam... function SetAttr (line 55) | void SetAttr(const Descriptor& desc, cudnnBackendAttributeName_t nam... function SetAttr (line 60) | void SetAttr(const Descriptor& desc, function Descriptor (line 69) | Descriptor GetAttr(const Descriptor& desc, function GetAllAttrs (line 81) | std::vector GetAllAttrs(const Descriptor& desc, function GetSomeAttrs (line 98) | std::vector GetSomeAttrs(size_t max_n, function GetPlans (line 115) | std::vector GetPlans(cudnnBackendHeurMode_t h_mode, function Sampler (line 187) | Sampler MakeAvgSampler(size_t n, float max_cutoff_msec, size_t warmu... function FindTopPlans (line 207) | std::vector FindTopPlans(std::vector&& plans, function NoteStr (line 261) | std::string NoteStr(cudnnBackendNumericalNote_t note) { function KnobStr (line 274) | std::string KnobStr(cudnnBackendKnobType_t knob) { function PlanStr (line 297) | std::string PlanStr(const Descriptor& plan) { FILE: src/common/cuda/cudnn_cxx.h function namespace (line 49) | namespace mxnet { function T (line 204) | T ret{} function IsCompatible (line 259) | bool IsCompatible(const std::vector& notes, FILE: src/common/cuda/nvtx.h function namespace (line 32) | namespace common { FILE: src/common/cuda/rtc.cc type mxnet (line 66) | namespace mxnet { type common (line 67) | namespace common { type cuda (line 68) | namespace cuda { type rtc (line 69) | namespace rtc { type util (line 79) | namespace util { function to_string (line 81) | std::string to_string(OpReqType req) { function GetMaxSupportedArch (line 97) | int GetMaxSupportedArch() { function GetCompileLog (line 127) | std::string GetCompileLog(nvrtcProgram program) { function GetCompiledCode (line 137) | std::string GetCompiledCode(nvrtcProgram program, bool use_cubin) { function GetArchString (line 153) | std::tuple GetArchString(const int sm_arch) { function CUfunction (line 166) | CUfunction get_function(const std::string& parameters, function launch (line 289) | void launch(CUfunction function, FILE: src/common/cuda/rtc.h function namespace (line 41) | namespace mxnet { FILE: src/common/cuda/rtc/backward_functions-inl.h function namespace (line 25) | namespace mxnet { FILE: src/common/cuda/rtc/forward_functions-inl.h function namespace (line 25) | namespace mxnet { function isnan (line 220) | bool isnan(const DType val) { function bool_t (line 225) | inline bool_t isinf(const DType val) { function bool_t (line 230) | inline bool_t isposinf(const DType val) { function bool_t (line 235) | inline bool_t isneginf(const DType val) { function bool_t (line 240) | inline bool_t isfinite(const DType val) { function DType (line 404) | inline DType equal(const DType a, const DType2 b) { function DType (line 411) | inline DType not_equal(const DType a, const DType2 b) { function DType (line 418) | inline DType greater(const DType a, const DType2 b) { function DType (line 425) | inline DType greater_equal(const DType a, const DType2 b) { function DType (line 432) | inline DType less(const DType a, const DType2 b) { function DType (line 439) | inline DType less_equal(const DType a, const DType2 b) { function bool_t (line 446) | inline bool_t np_equal(const DType a, const DType2 b) { function bool_t (line 453) | inline bool_t np_not_equal(const DType a, const DType2 b) { function bool_t (line 460) | inline bool_t np_greater(const DType a, const DType2 b) { function bool_t (line 467) | inline bool_t np_greater_equal(const DType a, const DType2 b) { function bool_t (line 474) | inline bool_t np_less(const DType a, const DType2 b) { function bool_t (line 481) | inline bool_t np_less_equal(const DType a, const DType2 b) { function DType (line 488) | inline DType logical_and(const DType a, const DType2 b) { function DType (line 493) | inline DType logical_or(const DType a, const DType2 b) { function DType (line 498) | inline DType logical_xor(const DType a, const DType2 b) { function DType (line 503) | inline DType copysign(const DType a, const DType2 b) { function DType2 (line 508) | inline DType2 rcopysign(const DType a, const DType2 b) { function np_logical_and (line 689) | inline bool np_logical_and(const DType val, const DType2 val2) { function np_logical_or (line 694) | inline bool np_logical_or(const DType val, const DType2 val2) { function np_logical_xor (line 699) | inline bool np_logical_xor(const DType val, const DType2 val2) { function DType (line 704) | inline DType left(const DType left_val, const DType2 right_val) { function DType2 (line 709) | inline DType2 right(const DType left_val, const DType2 right_val) { function DType (line 720) | inline DType identity(const DType val) { function DType (line 725) | inline DType negation(const DType val) { function typename (line 730) | inline typename LoadType::Type cast(const DType val) { function DType (line 737) | inline DType relu(const DType val) { function DType (line 742) | inline DType sigmoid(const DType val) { function DType (line 751) | inline DType log_sigmoid(const DType val) { function DType (line 760) | inline DType softrelu(const DType val) { function DType (line 773) | inline DType softsign(const DType val) { function DType (line 805) | inline DType degrees(const DType val) { function DType (line 814) | inline DType radians(const DType val) { function DType (line 837) | inline DType mish(const DType val) { function DType (line 849) | inline DType square(const DType val) { function typename (line 854) | inline typename LoadType::Type zero(const DType val, const DTypes... function typename (line 859) | inline typename LoadType::Type zero() { function typename (line 864) | inline typename LoadType::Type one(const DType val, const DTypes.... function typename (line 869) | inline typename LoadType::Type one() { function typename (line 874) | inline typename LoadType::Type negone(const DType val, const DTyp... function typename (line 879) | inline typename LoadType::Type negone() { function DType (line 884) | inline DType round(const DType val) { function DType (line 895) | inline DType floor(const DType val) { function DType (line 906) | inline DType ceil(const DType val) { function DType (line 917) | inline DType rint(const DType val) { function DType (line 928) | inline DType fix(const DType val) { function DType (line 935) | inline DType trunc(const DType val) { function DType (line 946) | inline DType clip(const DType val, const float a_min, const float a_max) { function DType (line 957) | inline DType sign(const DType val) { function DType (line 963) | inline DType reciprocal(const DType val) { function DType (line 974) | inline DType gelu_erf(const DType val) { function DType1 (line 979) | inline DType1 smooth_l1(const DType1 val, const DType2 scalar) { function DType (line 992) | inline DType digamma(const DType val) { function DType (line 1001) | inline DType logical_not(const DType val) { function bool_t (line 1006) | inline bool_t np_logical_not(const DType val) { function bool_t (line 1011) | inline bool_t NonZero(const DType val) { function DType (line 1018) | inline DType bitwise_not(const DType a) { FILE: src/common/cuda/rtc/half-inl.h function namespace (line 25) | namespace mxnet { FILE: src/common/cuda/rtc/reducer-inl.h function namespace (line 25) | namespace mxnet { type nanprod (line 196) | struct nanprod { function Reduce (line 205) | inline static void Reduce(volatile DType& dst, volatile DType src, function Merge (line 211) | inline static void Merge(volatile DType& dst_val, volatile DType& src_va... function Merge (line 216) | inline static void Merge(volatile DType& dst_val, volatile DType& dst_re... function Finalize (line 222) | inline static void Finalize(volatile DType& dst) {} function Finalize (line 225) | inline static void Finalize(volatile DType& dst, volatile DType& none) {} function SetInitValue (line 230) | inline static void SetInitValue(DType & initv) { function SetInitValue (line 237) | inline static void SetInitValue(DType &initv, DType &none) { type nrm2 (line 242) | struct nrm2 { function Merge (line 264) | inline static void Merge(volatile DType& dst_val, volatile DType& src_va... function Merge (line 269) | inline static void Merge(volatile DType& dst_ssq, volatile DType& dst_sc... function Finalize (line 280) | inline static void Finalize(volatile DType& sum_of_squares) { function Finalize (line 285) | inline static void Finalize(volatile DType& sum_of_squares, volatile DTy... function SetInitValue (line 292) | inline static void SetInitValue(DType &sum_of_squares) { function SetInitValue (line 299) | inline static void SetInitValue(DType &sum_of_squares, DType &scale) { function else (line 305) | struct nrmlp { function Reduce (line 322) | inline void Reduce(volatile AType& sum_of_powers, volatile DType src) { function Reduce (line 330) | inline void Reduce(volatile AType& sum_of_powers, volatile DType src, function Merge (line 346) | inline static void Merge(volatile DType& dst_val, volatile DType& src_va... function Merge (line 352) | inline static void Merge(volatile DType& dst_ssq, volatile DType& dst_sc... function Finalize (line 364) | inline void Finalize(volatile DType& sum_of_powers) { function Finalize (line 372) | inline void Finalize(volatile DType& sum_of_powers, volatile DType& scal... function SetInitValue (line 382) | inline static void SetInitValue(DType &sum_of_powers) { function SetInitValue (line 390) | inline static void SetInitValue(DType &sum_of_powers, DType &scale) { type maximum (line 402) | struct maximum { function Merge (line 418) | inline static void Merge(volatile DType& dst_val, volatile DType& src_va... function Merge (line 423) | inline static void Merge(volatile DType& dst_val, volatile DType& dst_re... function Finalize (line 429) | inline static void Finalize(volatile DType& dst) {} function Finalize (line 432) | inline static void Finalize(volatile DType& dst, volatile DType& none) {} function SetInitValue (line 437) | inline static void SetInitValue(DType &initv) { function SetInitValue (line 444) | inline static void SetInitValue(DType &initv, DType &none) { type minimum (line 449) | struct minimum { function Merge (line 465) | inline static void Merge(volatile DType& dst_val, volatile DType& src_va... function Merge (line 470) | inline static void Merge(volatile DType& dst_val, volatile DType& dst_re... function Finalize (line 476) | inline static void Finalize(volatile DType& dst) {} function Finalize (line 479) | inline static void Finalize(volatile DType& dst, volatile DType& none) {} function SetInitValue (line 484) | inline static void SetInitValue(DType &initv) { function SetInitValue (line 491) | inline static void SetInitValue(DType &initv, DType &none) { type argmax (line 496) | struct argmax { function Merge (line 516) | inline static void Merge(volatile DType& dst, volatile DType& src) { function Merge (line 524) | inline static void Merge(volatile DType& dst, volatile DType&, function Finalize (line 533) | inline static void Finalize(volatile DType& dst) {} function Finalize (line 536) | inline static void Finalize(volatile DType& dst, volatile DType&) {} function SetInitValue (line 541) | inline static void SetInitValue(DType &initv) { function SetInitValue (line 548) | inline static void SetInitValue(DType &initv, DType &) { type argmin (line 553) | struct argmin { function Merge (line 573) | inline static void Merge(volatile DType& dst, volatile DType& src) { function Merge (line 581) | inline static void Merge(volatile DType& dst, volatile DType&, function Finalize (line 590) | inline static void Finalize(volatile DType& dst) {} function Finalize (line 593) | inline static void Finalize(volatile DType& dst, volatile DType& residua... function SetInitValue (line 598) | inline static void SetInitValue(DType &initv) { function SetInitValue (line 605) | inline static void SetInitValue(DType &initv, DType &residual) { FILE: src/common/cuda/rtc/special_functions-inl.h function namespace (line 26) | namespace mxnet { FILE: src/common/cuda/rtc/util-inl.h function namespace (line 27) | namespace mxnet { type mixed_type_helper (line 295) | struct mixed_type_helper type mixed_type_helper (line 300) | struct mixed_type_helper type mixed_type_helper (line 305) | struct mixed_type_helper type mixed_type_helper (line 310) | struct mixed_type_helper type mixed_type_helper (line 315) | struct mixed_type_helper type mixed_type_helper (line 320) | struct mixed_type_helper type mixed_type_helper (line 325) | struct mixed_type_helper type mixed_type_helper (line 330) | struct mixed_type_helper type mixed_type_helper (line 335) | struct mixed_type_helper type mixed_type_helper (line 340) | struct mixed_type_helper type mixed_type_helper (line 345) | struct mixed_type_helper type mixed_type_helper (line 350) | struct mixed_type_helper type mixed_type_helper (line 355) | struct mixed_type_helper type mixed_type_helper (line 360) | struct mixed_type_helper type multi_mixed_type_helper (line 393) | struct multi_mixed_type_helper<> { function namespace (line 426) | namespace util { function namespace (line 600) | namespace limits { FILE: src/common/cuda/rtc/vectorization-inl.h function namespace (line 35) | namespace mxnet { FILE: src/common/cuda/utils.cc type mxnet (line 35) | namespace mxnet { type common (line 36) | namespace common { type cuda (line 37) | namespace cuda { function get_load_type (line 39) | int get_load_type(size_t N) { function get_rows_per_block (line 52) | int get_rows_per_block(size_t row_size, int num_threads_per_block) { FILE: src/common/cuda/utils.h function __syncthreads (line 41) | inline void __syncthreads() {} function __threadfence_block (line 42) | inline void __threadfence_block() {} function T (line 44) | T __clz(const T val) { type __cuda_fake_struct (line 47) | struct __cuda_fake_struct { function __device__ (line 81) | inline __device__ bool __is_supported_cuda_architecture() { function namespace (line 205) | namespace mxnet { function cudaAttributeLookup (line 461) | inline int cudaAttributeLookup(int device_id, function ComputeCapabilityMajor (line 480) | inline int ComputeCapabilityMajor(int device_id) { function ComputeCapabilityMinor (line 491) | inline int ComputeCapabilityMinor(int device_id) { function SMArch (line 502) | inline int SMArch(int device_id) { function MultiprocessorCount (line 513) | inline int MultiprocessorCount(int device_id) { function MaxSharedMemoryPerMultiprocessor (line 524) | inline int MaxSharedMemoryPerMultiprocessor(int device_id) { function SupportsCooperativeLaunch (line 537) | inline bool SupportsCooperativeLaunch(int device_id) { function SupportsFloat16Compute (line 549) | inline bool SupportsFloat16Compute(int device_id) { function SupportsTensorCore (line 566) | inline bool SupportsTensorCore(int device_id) { function GetEnvAllowTensorCore (line 578) | inline bool GetEnvAllowTensorCore() { function GetEnvAllowTensorCoreConversion (line 601) | inline bool GetEnvAllowTensorCoreConversion() { function cublasMath_t (line 612) | inline cublasMath_t SetCublasMathMode(cublasHandle_t blas_handle, cublas... function MaxForwardAlgos (line 671) | inline int MaxForwardAlgos(cudnnHandle_t cudnn_handle) { function MaxBackwardFilterAlgos (line 685) | inline int MaxBackwardFilterAlgos(cudnnHandle_t cudnn_handle) { function MaxBackwardDataAlgos (line 699) | inline int MaxBackwardDataAlgos(cudnnHandle_t cudnn_handle) { function __device__ (line 711) | static inline __device__ void atomicAdd(double* address, double val) { function __device__ (line 731) | static inline __device__ void atomicAdd(mshadow::half::half_t* address, ... function __device__ (line 748) | static inline __device__ void atomicAdd(uint8_t* address, uint8_t val) { function __device__ (line 763) | static inline __device__ void atomicAdd(int8_t* address, int8_t val) { function __device__ (line 779) | static inline __device__ void atomicAdd(int64_t* address, int64_t val) { function DType (line 785) | inline DType ldg(const DType* address) { function namespace (line 793) | namespace mxnet { FILE: src/common/exec_utils.cc type mxnet (line 30) | namespace mxnet { type common (line 31) | namespace common { function CopyGraph (line 33) | void CopyGraph(nnvm::Graph* dst, const nnvm::Graph& src, bool copy_v... function CheckForInputNameDuplicates (line 65) | bool CheckForInputNameDuplicates(const nnvm::IndexedGraph& idx) { FILE: src/common/exec_utils.h function namespace (line 36) | namespace mxnet { function CastNonDefaultStorage (line 172) | inline void CastNonDefaultStorage(const std::vector& src, function SameType (line 193) | inline bool SameType(const nnvm::NodeAttrs& attrs, function LogInferStorage (line 344) | inline void LogInferStorage(const nnvm::Graph& g) { function NDArray (line 381) | inline NDArray ReshapeOrCreate(const std::string& name, function nnvm (line 428) | inline nnvm::Graph AssignContext(nnvm::Graph g, FILE: src/common/lazy_alloc_array.h function namespace (line 35) | namespace mxnet { FILE: src/common/object_pool.h function namespace (line 28) | namespace mxnet { FILE: src/common/rtc.cc type mxnet (line 28) | namespace mxnet { type rtc (line 29) | namespace rtc { function CUfunction (line 92) | CUfunction CudaModule::Chunk::GetFunction(const std::string& mangled... FILE: src/common/static_array.h function namespace (line 28) | namespace mxnet { FILE: src/common/tensor_inspector.h function namespace (line 36) | namespace mxnet { type CheckerType (line 70) | enum CheckerType { function class (line 102) | class TensorInspector { FILE: src/common/utils.cc type mxnet (line 29) | namespace mxnet { type common (line 30) | namespace common { function ExecuteMonInputCallback (line 54) | void ExecuteMonInputCallback( function ExecuteMonOutputCallback (line 82) | void ExecuteMonOutputCallback( function MShadowTypeInfo (line 109) | MShadowTypeInfo mshadow_type_info(const int type_flag) { FILE: src/common/utils.h function namespace (line 61) | namespace mxnet { type rsp_idx_check (line 114) | struct rsp_idx_check { function full_check (line 144) | bool full_check) { function full_check (line 202) | bool full_check) { function full_check (line 240) | bool full_check) { function ContainsOnlyStorage (line 271) | inline bool ContainsOnlyStorage(const StorageTypeVector& vstorage, const... function ContainsOnlyStorage (line 286) | inline bool ContainsOnlyStorage(const StorageTypeVector& vstorage, function ContainsOnlyStorage (line 315) | inline bool ContainsOnlyStorage(const std::vector& ndarrays, function ContainsOnlyStorage (line 331) | inline bool ContainsOnlyStorage(const std::vector& ndarrays, function std (line 474) | inline std::string operator_stype_string(const nnvm::NodeAttrs& attrs, function LogOnce (line 517) | inline void LogOnce(const std::string& message) { function LogStorageFallback (line 528) | inline void LogStorageFallback(const nnvm::NodeAttrs& attrs, function GetNumThreadsPerGPU (line 566) | inline int GetNumThreadsPerGPU() { function GetExecNumMatchColor (line 573) | inline int GetExecNumMatchColor() { type std (line 642) | typedef std::mt19937 RANDOM_ENGINE; function namespace (line 647) | namespace helper { function MaxIntegerValue (line 745) | size_t MaxIntegerValue() { function MaxIntegerValue (line 751) | constexpr size_t MaxIntegerValue() { function MaxIntegerValue (line 756) | constexpr size_t MaxIntegerValue() { function MSHADOW_XINLINE (line 760) | MSHADOW_XINLINE int ilog2ul(size_t a) { function MSHADOW_XINLINE (line 767) | MSHADOW_XINLINE int ilog2ui(unsigned int a) { function NDArray (line 777) | inline NDArray InitZeros(const NDArrayStorageType stype, function EmplaceBackZeros (line 794) | inline void EmplaceBackZeros(const NDArrayStorageType stype, function ParallelCopy (line 813) | void ParallelCopy(DType* dst, const DType* src, index_t size) { function ParallelAdd (line 834) | void ParallelAdd(DType* dst, const DType* src, index_t size) { function ConvertToNumpyShape (line 866) | inline void ConvertToNumpyShape(mxnet::TShape* shape) { function ConvertToNumpyShape (line 878) | inline void ConvertToNumpyShape(mxnet::ShapeVector* shapes) { function ConvertToLegacyShape (line 888) | inline void ConvertToLegacyShape(mxnet::TShape* shape) { function ConvertToLegacyShape (line 900) | inline void ConvertToLegacyShape(mxnet::ShapeVector* shapes) { function CanonicalizeAxes (line 911) | void ExecuteMonOutputCallback( function is_float (line 931) | inline bool is_float(const int dtype) { function is_int (line 936) | inline bool is_int(const int dtype) { function is_signed_int (line 942) | inline bool is_signed_int(const int dtype) { function is_unsigned_int (line 947) | inline bool is_unsigned_int(const int dtype) { function bits_of (line 952) | static int bits_of(const int type_flag) { function type_promotion (line 983) | inline int type_promotion(const int type1, const int type2) { function std (line 1067) | inline const std::string NodeAttrsGetProfilerScope(const nnvm::NodeAttrs... function GetDefaultDtype (line 1079) | inline int GetDefaultDtype() { function GetDefaultDtype (line 1083) | inline int GetDefaultDtype(int dtype) { function AlignedMemFree (line 1089) | struct MShadowTypeInfo { function index_t (line 1123) | inline index_t div_round(const index_t a, const index_t b) { function IsPower2 (line 1127) | inline bool IsPower2(size_t N) { function RoundToPower2 (line 1131) | inline size_t RoundToPower2(size_t N) { FILE: src/engine/engine.cc type mxnet (line 30) | namespace mxnet { type engine (line 31) | namespace engine { function Engine (line 32) | inline Engine* CreateEngine() { function Engine (line 92) | Engine* Engine::Get() { FILE: src/engine/engine_impl.h function namespace (line 32) | namespace mxnet { FILE: src/engine/naive_engine.cc type mxnet (line 35) | namespace mxnet { type engine (line 36) | namespace engine { class NaiveVar (line 42) | class NaiveVar final : public Var, public common::ObjectPoolAllocata... method NaiveVar (line 44) | inline static NaiveVar* CastFromBase(Var* ptr) { class NaiveEngine (line 50) | class NaiveEngine final : public Engine { type NaiveOpr (line 52) | struct NaiveOpr : public Opr { method NaiveEngine (line 64) | NaiveEngine() { method Stop (line 87) | void Stop() override {} method Start (line 89) | void Start() override {} method VarHandle (line 92) | VarHandle NewVariable() override { method OprHandle (line 96) | OprHandle NewOperator(AsyncFn fn, method DeleteOperator (line 111) | void DeleteOperator(OprHandle op) override { method Push (line 116) | void Push(OprHandle op, Context exec_ctx, int priority = 0, bool p... method PushAsync (line 149) | void PushAsync(AsyncFn exec_fun, method DeleteVariable (line 210) | void DeleteVariable(SyncFn delete_fn, Context exec_ctx, VarHandle ... method WaitForVar (line 228) | void WaitForVar(VarHandle var) override {} method WaitForAll (line 230) | void WaitForAll() override {} method Throw (line 232) | void Throw(VarHandle var) override {} method NotifyShutdown (line 234) | void NotifyShutdown() override { method OnStart (line 240) | static void OnStart(Engine* engine, void* param, const dmlc::Error... method OnComplete (line 242) | static void OnComplete(Engine* engine, void* param, const dmlc::Er... function Engine (line 265) | Engine* CreateNaiveEngine() { FILE: src/engine/openmp.cc type mxnet (line 25) | namespace mxnet { type engine (line 26) | namespace engine { function is_env_set (line 32) | static inline bool is_env_set(const char* var) { function OpenMP (line 36) | OpenMP* OpenMP::Get() { FILE: src/engine/openmp.h function namespace (line 22) | namespace mxnet { FILE: src/engine/stream_manager.h function StreamManager (line 42) | size_t kStreams> FILE: src/engine/thread_pool.h function namespace (line 33) | namespace engine { FILE: src/engine/threaded_engine.cc type mxnet (line 34) | namespace mxnet { type engine (line 35) | namespace engine { function ThreadedVar (line 206) | ThreadedVar* ThreadedEngine::NewVariable() { function ThreadedOpr (line 210) | ThreadedOpr* ThreadedEngine::NewOperator(ThreadedEngine::AsyncFn fn, function AddEventHelper (line 554) | static inline void AddEventHelper(std::unordered_map ExceptionRef; type OprBlock (line 74) | struct OprBlock function profiling (line 86) | bool profiling{false}; type VersionedVarBlock (line 107) | struct VersionedVarBlock function write (line 113) | bool write{false}; function version (line 171) | inline size_t version() override; function num_pending_reads_ (line 203) | int num_pending_reads_{0} function VersionedVarBlock (line 212) | VersionedVarBlock* head_{nullptr}; type GPUWorkerSyncInfo (line 444) | struct GPUWorkerSyncInfo type BulkStatus (line 455) | struct BulkStatus { type dmlc (line 470) | typedef dmlc::ThreadLocalStore BulkStatusStore; function OnStart (line 496) | inline void OnStart(ThreadedOpr* threaded_opr) { function AddToGlobalExceptions (line 519) | inline void AddToGlobalExceptions(const ExceptionRef& opr_exception) { function BulkAppend (line 528) | inline void BulkAppend(SyncFn exec_fn, FILE: src/engine/threaded_engine_perdevice.cc type mxnet (line 40) | namespace mxnet { type engine (line 41) | namespace engine { class ThreadedEnginePerDevice (line 50) | class ThreadedEnginePerDevice : public ThreadedEngine { method ThreadedEnginePerDevice (line 59) | ThreadedEnginePerDevice() noexcept(false) { method StopNoWait (line 71) | void StopNoWait() { method Stop (line 84) | void Stop() override { method WaitForAll (line 92) | void WaitForAll() override { method Start (line 100) | void Start() override { method PushToExecute (line 120) | void PushToExecute(OprBlock* opr_block, bool pusher_thread) overri... type ThreadWorkerBlock (line 235) | struct ThreadWorkerBlock { method ThreadWorkerBlock (line 241) | ThreadWorkerBlock() = default; method GPUWorker (line 277) | inline void GPUWorker(Context ctx, method CPUWorker (line 350) | inline void CPUWorker(Context ctx, method GetReserveCoreCount (line 384) | int GetReserveCoreCount(const bool using_gpu) const { method SignalQueueForKill (line 399) | static inline void SignalQueueForKill(common::LazyAllocArray& bwd_in_dep, function OpStatePtr (line 385) | OpStatePtr CachedOp::GetCachedOpState(const Context& ctx) { function PrepareOutputs (line 653) | static void PrepareOutputs(const nnvm::Graph& g, function OpStatePtr (line 680) | OpStatePtr CachedOp::StaticForward(const Context& default_ctx, function OpStatePtr (line 743) | OpStatePtr CachedOp::DynamicForward(const Context& default_ctx, function OpStatePtr (line 833) | OpStatePtr CachedOp::Forward(const std::shared_ptr& op_ptr, type CachedOpActualState (line 1145) | struct CachedOpActualState { method CachedOpActualState (line 1149) | explicit CachedOpActualState(std::shared_ptr op) { function CachedOpForward (line 1158) | void CachedOpForward(const OpStatePtr& state_ptr, function CachedOpBackward (line 1201) | void CachedOpBackward(const OpStatePtr& state_ptr, function OpStatePtr (line 1289) | OpStatePtr CreateCachedOpState(const NodeAttrs& attrs, function CachedOpParamParser (line 1343) | void CachedOpParamParser(nnvm::NodeAttrs* attrs) { FILE: src/imperative/cached_op.h function namespace (line 37) | namespace mxnet { function CreateFullGraph (line 268) | void CreateFullGraph(const nnvm::Symbol& sym, function OptimizeGraph (line 333) | void OptimizeGraph(nnvm::Graph* full_graph, function SetInputIndices (line 395) | void SetInputIndices(const nnvm::Graph& fwd_graph, type CachedOpConfig (line 415) | struct CachedOpConfig function DMLC_DECLARE_PARAMETER (line 425) | DMLC_DECLARE_PARAMETER(CachedOpConfig) { function namespace (line 461) | namespace io { function class (line 465) | class CachedOp { type GraphInfo (line 527) | struct GraphInfo { type DynamicRuntime (line 624) | struct DynamicRuntime function monitor_all_ (line 654) | bool monitor_all_{false}; function DynamicRuntime (line 664) | struct CachedOp::DynamicRuntime { FILE: src/imperative/cached_op_threadsafe.cc type mxnet (line 29) | namespace mxnet { type CachedOpThreadSafe::GraphInfo (line 33) | struct CachedOpThreadSafe::GraphInfo { type CachedOpThreadSafe::DynamicRuntime (line 37) | struct CachedOpThreadSafe::DynamicRuntime { function OpStatePtr (line 42) | OpStatePtr CachedOpThreadSafe::GetCachedOpState(const Context& ctx) { function OpStatePtr (line 80) | OpStatePtr CachedOpThreadSafe::DynamicForward(const Context& default_ctx, function OpStatePtr (line 152) | OpStatePtr CachedOpThreadSafe::Forward(const std::shared_ptr... type CachedOpThreadSafeActualState (line 195) | struct CachedOpThreadSafeActualState { method CachedOpThreadSafeActualState (line 199) | explicit CachedOpThreadSafeActualState(std::shared_ptr op) { function OpStatePtr (line 203) | OpStatePtr CreateCachedOpThreadSafeState(const NodeAttrs& attrs, function CachedOpThreadSafeForward (line 211) | void CachedOpThreadSafeForward(const OpStatePtr& state_ptr, function CachedOpThreadSafeParamParser (line 239) | void CachedOpThreadSafeParamParser(nnvm::NodeAttrs* attrs) { FILE: src/imperative/cached_op_threadsafe.h function namespace (line 33) | namespace mxnet { FILE: src/imperative/cuda_graphs.h function namespace (line 46) | namespace mxnet { FILE: src/imperative/eliminate_common_expr_pass.cc type mxnet (line 34) | namespace mxnet { type exec (line 35) | namespace exec { function ConvertInputs (line 50) | std::vector ConvertInputs(const std::vector > GetCommonNodes(const G... function EliminateCommonNodes (line 147) | void EliminateCommonNodes(Graph* g, function EliminateCommonExpr (line 223) | nnvm::Graph EliminateCommonExpr(nnvm::Graph&& g) { FILE: src/imperative/exec_pass.h function namespace (line 40) | namespace mxnet { function namespace (line 280) | namespace nnvm { FILE: src/imperative/imperative.cc type nnvm (line 27) | namespace nnvm { type mxnet (line 31) | namespace mxnet { function Imperative (line 46) | Imperative* Imperative::Get() { function OpStatePtr (line 51) | OpStatePtr Imperative::InvokeOp(const Context& ctx, function OpStatePtr (line 107) | OpStatePtr Imperative::Invoke(const Context& default_ctx, FILE: src/imperative/imperative_utils.cc function NodeInputs (line 26) | std::vector NodeInputs(const nnvm::IndexedGraph& idx, function NodeOutputs (line 40) | std::vector NodeOutputs(const nnvm::IndexedGraph& idx, function NodeReq (line 54) | std::vector NodeReq(const nnvm::IndexedGraph& idx, function InvokeOperator (line 68) | void InvokeOperator(const nnvm::IndexedGraph& idx, type mxnet (line 126) | namespace mxnet { type imperative (line 127) | namespace imperative { function RunGraph (line 129) | void RunGraph(const bool retain_graph, function NaiveRunGraph (line 172) | void NaiveRunGraph(const bool retain_graph, FILE: src/imperative/imperative_utils.h function namespace (line 42) | namespace mxnet { function SetNumOutputs (line 468) | inline void SetNumOutputs(const nnvm::Op* op, function DerefInputOutput (line 498) | inline void DerefInputOutput(const std::vector& inputs, function std (line 1022) | inline std::vector PlaceDevice(const nnvm::IndexedGraph& idx) { function AllocateMemory (line 1128) | size_t, NDArray> AllocateMemory( function SetupOpExec (line 1199) | inline void SetupOpExec(const nnvm::Graph& g, function Engine (line 1222) | inline Engine::OprHandle CreateEngineOp( function CreateEngineOpSeg (line 1292) | inline void CreateEngineOpSeg(const nnvm::IndexedGraph& idx, FILE: src/imperative/infer_graph_attr_pass.cc type mxnet (line 32) | namespace mxnet { type exec (line 33) | namespace exec { function ApplyOpInferAttr (line 36) | bool ApplyOpInferAttr(const nnvm::Graph& g, function GetAttrFromForwardNode (line 67) | inline void GetAttrFromForwardNode(const uint32_t nid, function GetAttrFromFusedNode (line 131) | void GetAttrFromFusedNode(uint32_t nid, function ProvideAttrToFusion (line 207) | void ProvideAttrToFusion(const uint32_t nid, function InferAttr (line 269) | nnvm::Graph InferAttr(nnvm::Graph&& ret, function InferShapeAttr (line 554) | nnvm::Graph InferShapeAttr(nnvm::Graph&& ret, function InferShape (line 818) | nnvm::Graph InferShape(nnvm::Graph&& graph, function InferType (line 854) | nnvm::Graph InferType(nnvm::Graph&& graph, function InferStorageType (line 880) | nnvm::Graph InferStorageType(nnvm::Graph&& graph, FILE: src/imperative/inplace_addto_detect_pass.cc type mxnet (line 31) | namespace mxnet { type exec (line 32) | namespace exec { function Graph (line 34) | Graph DetectInplaceAddTo(Graph g) { FILE: src/imperative/naive_cached_op.cc type mxnet (line 28) | namespace mxnet { function OpStatePtr (line 29) | OpStatePtr NaiveCachedOp::Forward(const std::shared_ptr& op_... FILE: src/imperative/naive_cached_op.h function namespace (line 33) | namespace mxnet { FILE: src/imperative/pointwise_fusion_pass.cc type mxnet (line 39) | namespace mxnet { type exec (line 40) | namespace exec { function WarnFusionNotSupported (line 42) | void WarnFusionNotSupported() { function IsFusionCompatible (line 61) | bool IsFusionCompatible(const nnvm::Node* n) { function IsInputsOnlyCompatible (line 89) | bool IsInputsOnlyCompatible(const nnvm::Node* n) { function CreateSubgraphNode (line 108) | void CreateSubgraphNode(const nnvm::Graph& subgraph, type EntryInfo (line 120) | struct EntryInfo { function SetInsert (line 125) | inline int SetInsert(const EntryInfo& new_elem, std::vector* const set_mappi... function CheckAndUpdateCombinedExcludedSets (line 224) | void CheckAndUpdateCombinedExcludedSets( FILE: src/imperative/simple_partition_pass.h function namespace (line 40) | namespace mxnet { FILE: src/initialize.cc function win_err (line 35) | void win_err(char** err) { type mxnet (line 71) | namespace mxnet { function pthread_atfork_prepare (line 75) | void pthread_atfork_prepare() { function pthread_atfork_parent (line 80) | void pthread_atfork_parent() { function pthread_atfork_child (line 85) | void pthread_atfork_child() { function printStackTrace (line 245) | static inline void printStackTrace(FILE* out = stderr, const unsigned ... function LibraryInitializerEntry (line 398) | __attribute__((constructor)) static void LibraryInitializerEntry() { FILE: src/initialize.h function class (line 43) | class LibraryInitializer { FILE: src/io/batchify.cc type mxnet (line 37) | namespace mxnet { type io (line 38) | namespace io { type GroupBatchifyParam (line 52) | struct GroupBatchifyParam : public dmlc::Parameter>& inputs, type StackBatchifyParam (line 112) | struct StackBatchifyParam : public dmlc::Parameter>& inputs, method SanityCheck (line 187) | std::size_t SanityCheck(const std::vector>& i... type PadBatchifyParam (line 207) | struct PadBatchifyParam : public dmlc::Parameter { method DMLC_DECLARE_PARAMETER (line 213) | DMLC_DECLARE_PARAMETER(PadBatchifyParam) { class PadBatchify (line 225) | class PadBatchify : public BatchifyFunction { method PadBatchify (line 227) | explicit PadBatchify(const std::vector>& inputs, method CompactShapes (line 367) | std::pair, std::vector> CompactShapes(co... FILE: src/io/dataloader.cc type mxnet (line 32) | namespace mxnet { type io (line 33) | namespace io { type ThreadedDataLoaderParam (line 34) | struct ThreadedDataLoaderParam : public dmlc::Parameter { method ThreadedDataLoader (line 62) | ThreadedDataLoader() = default; method Init (line 66) | void Init(const std::vector >&... method BeforeFirst (line 85) | void BeforeFirst() override { method GetLenHint (line 89) | int64_t GetLenHint() const override { method Next (line 93) | bool Next() override { method TBlobBatch (line 146) | const TBlobBatch& Value() const override { FILE: src/io/dataset.cc type mxnet (line 46) | namespace mxnet { type io (line 47) | namespace io { type RecordFileDatasetParam (line 49) | struct RecordFileDatasetParam : public dmlc::Parameter* ret) override { type ImageRecordFileDatasetParam (line 126) | struct ImageRecordFileDatasetParam : public dmlc::Parameter* ret) override { type ImageSequenceDatasetParam (line 269) | struct ImageSequenceDatasetParam : public dmlc::Parameter* ret) override { type NDArrayDatasetParam (line 339) | struct NDArrayDatasetParam : public dmlc::Parameter* rets) override { type GroupDatasetParam (line 401) | struct GroupDatasetParam : public dmlc::Parameter { method DMLC_DECLARE_PARAMETER (line 405) | DMLC_DECLARE_PARAMETER(GroupDatasetParam) { class GroupDataset (line 412) | class GroupDataset final : public Dataset { method GroupDataset (line 414) | explicit GroupDataset(const std::vector* ret) override { type IndexedDatasetParam (line 465) | struct IndexedDatasetParam : public dmlc::Parameter* ret) override { type LazyTransformDatasetParam (line 516) | struct LazyTransformDatasetParam : public dmlc::Parameter* outputs) override { FILE: src/io/image_aug_default.cc type dmlc (line 36) | namespace dmlc { type mxnet (line 41) | namespace mxnet { type io (line 42) | namespace io { type DefaultImageAugmentParam (line 45) | struct DefaultImageAugmentParam : public dmlc::Parameter ListDefaultAugParams() { class DefaultImageAugmenter (line 235) | class DefaultImageAugmenter : public ImageAugmenter { method DefaultImageAugmenter (line 238) | DefaultImageAugmenter() = default; method Init (line 239) | void Init(const std::vector >&... method GetInterMethod (line 260) | int GetInterMethod(int inter_method, method Process (line 281) | cv::Mat Process(const cv::Mat& src, function ImageAugmenter (line 617) | ImageAugmenter* ImageAugmenter::Create(const std::string& name) { FILE: src/io/image_augmenter.h function namespace (line 37) | namespace mxnet { function namespace (line 100) | namespace mxnet { FILE: src/io/image_det_aug_default.cc type mxnet (line 33) | namespace mxnet { type io (line 34) | namespace io { type image_det_aug_default_enum (line 38) | namespace image_det_aug_default_enum { type ImageDetAugDefaultCropEmitMode (line 39) | enum ImageDetAugDefaultCropEmitMode { kCenter, kOverlap } type ImageDetAugDefaultResizeMode (line 40) | enum ImageDetAugDefaultResizeMode { kForce, kShrink, kFit } type DefaultImageDetAugmentParam (line 44) | struct DefaultImageDetAugmentParam : public dmlc::Parameter ListDefaultDetAugParams() { class ImageDetLabel (line 248) | class ImageDetLabel { type ImageDetObject (line 251) | struct ImageDetObject { method Rect (line 260) | Rect ToRect() const { method ImageDetObject (line 265) | ImageDetObject Project(Rect box) const { method ImageDetObject (line 275) | ImageDetObject HorizontalFlip() const { method ImageDetLabel (line 284) | explicit ImageDetLabel(const std::vector& raw_label) { method FromArray (line 292) | void FromArray(const std::vector& raw_label) { method ToArray (line 319) | std::vector ToArray() const { method RectIOU (line 334) | static float RectIOU(Rect a, Rect b) { method TryCrop (line 345) | bool TryCrop(const Rect crop_box, method TryPad (line 418) | bool TryPad(const Rect pad_box) { method TryMirror (line 427) | bool TryMirror() { class DefaultImageDetAugmenter (line 445) | class DefaultImageDetAugmenter : public ImageAugmenter { method DefaultImageDetAugmenter (line 448) | DefaultImageDetAugmenter() = default; method Init (line 450) | void Init(const std::vector >&... method GetInterMethod (line 487) | int GetInterMethod(int inter_method, method ValidateCropParameters (line 511) | void ValidateCropParameters(mxnet::Tuple* param, const int ... method Rect (line 525) | Rect GenerateCropBox(const float min_crop_scale, method Rect (line 546) | Rect GeneratePadBox(const float max_pad_scale, method Process (line 558) | cv::Mat Process(const cv::Mat& src, FILE: src/io/image_io.cc type mxnet (line 46) | namespace mxnet { type io (line 47) | namespace io { function get_jpeg_size (line 52) | bool get_jpeg_size(const uint8_t* data, uint32_t data_size, int64_t*... function get_png_size (line 91) | bool get_png_size(const uint8_t* data, uint32_t data_size, int64_t* ... type ImdecodeParam (line 103) | struct ImdecodeParam : public dmlc::Parameter { method DMLC_DECLARE_PARAMETER (line 106) | DMLC_DECLARE_PARAMETER(ImdecodeParam) { type ImreadParam (line 117) | struct ImreadParam : public dmlc::Parameter { method DMLC_DECLARE_PARAMETER (line 121) | DMLC_DECLARE_PARAMETER(ImreadParam) { function ImdecodeImpl (line 134) | void ImdecodeImpl(int flag, bool to_rgb, void* data, size_t size, ND... function Imdecode (line 170) | void Imdecode(const nnvm::NodeAttrs& attrs, function Imread (line 212) | void Imread(const nnvm::NodeAttrs& attrs, type ResizeParam (line 255) | struct ResizeParam : public dmlc::Parameter { method DMLC_DECLARE_PARAMETER (line 259) | DMLC_DECLARE_PARAMETER(ResizeParam) { function ResizeShape (line 268) | inline bool ResizeShape(const nnvm::NodeAttrs& attrs, function Imresize (line 280) | inline void Imresize(const nnvm::NodeAttrs& attrs, type MakeBorderParam (line 289) | struct MakeBorderParam : public dmlc::Parameter { method DMLC_DECLARE_PARAMETER (line 294) | DMLC_DECLARE_PARAMETER(MakeBorderParam) { function MakeBorderShape (line 308) | inline bool MakeBorderShape(const nnvm::NodeAttrs& attrs, function copyMakeBorder (line 322) | inline void copyMakeBorder(const nnvm::NodeAttrs& attrs, FILE: src/io/image_iter_common.h function namespace (line 33) | namespace mxnet { FILE: src/io/image_recordio.h function namespace (line 31) | namespace mxnet { FILE: src/io/inst_vector.h function namespace (line 37) | namespace mxnet { function Index (line 97) | inline unsigned Index(unsigned i) const { function DataInst (line 102) | inline DataInst operator[](size_t i) const { function Clear (line 117) | inline void Clear(void) { function Push (line 126) | inline void Push(unsigned index, mshadow::Shape<3> dshape, mshadow::Shap... function TBlobBatch (line 154) | struct TBlobBatch { function class (line 180) | class TBlobContainer : public TBlob { FILE: src/io/io.cc type dmlc (line 26) | namespace dmlc { type mxnet (line 32) | namespace mxnet { type io (line 33) | namespace io { FILE: src/io/iter_batchloader.h function namespace (line 37) | namespace mxnet { FILE: src/io/iter_csv.cc type mxnet (line 32) | namespace mxnet { type io (line 33) | namespace io { type CSVIterParam (line 35) | struct CSVIterParam : public dmlc::Parameter { method DMLC_DECLARE_PARAMETER (line 45) | DMLC_DECLARE_PARAMETER(CSVIterParam) { class CSVIterBase (line 58) | class CSVIterBase : public IIterator { method CSVIterBase (line 60) | CSVIterBase() { method DataInst (line 72) | const DataInst& Value() const override { class CSVIterTyped (line 92) | class CSVIterTyped : public CSVIterBase { method Init (line 96) | void Init(const std::vector >&... method BeforeFirst (line 109) | void BeforeFirst() override { method Next (line 120) | bool Next() override { method TBlob (line 151) | inline TBlob AsTBlob(const dmlc::Row& row, const ... class CSVIter (line 164) | class CSVIter : public IIterator { method CSVIter (line 166) | CSVIter() = default; method Init (line 170) | void Init(const std::vector >&... method BeforeFirst (line 198) | void BeforeFirst() override { method Next (line 202) | bool Next() override { method DataInst (line 206) | const DataInst& Value() const override { FILE: src/io/iter_image_det_recordio.cc type mxnet (line 46) | namespace mxnet { type io (line 47) | namespace io { class ImageDetLabelMap (line 51) | class ImageDetLabelMap { method ImageDetLabelMap (line 58) | explicit ImageDetLabelMap(const char* path_imglist, int label_widt... method FindCopy (line 122) | inline std::vector FindCopy(size_t imid) const { method MaxLabelWidth (line 131) | inline size_t MaxLabelWidth() const { type ImageDetRecParserParam (line 151) | struct ImageDetRecParserParam : public dmlc::Parameter { method ImageDetRecordIter (line 516) | ImageDetRecordIter() : data_(nullptr) {} method Init (line 523) | void Init(const std::vector>& ... method BeforeFirst (line 542) | void BeforeFirst() override { method Next (line 548) | bool Next() override { method DataInst (line 577) | const DataInst& Value() const override { FILE: src/io/iter_image_recordio.cc type mxnet (line 46) | namespace mxnet { type io (line 47) | namespace io { class ImageRecordIOParser (line 50) | class ImageRecordIOParser { method BeforeFirst (line 56) | inline void BeforeFirst() { class ImageRecordIter (line 251) | class ImageRecordIter : public IIterator { method ImageRecordIter (line 253) | ImageRecordIter() : data_(nullptr) {} method Init (line 260) | void Init(const std::vector>& ... method BeforeFirst (line 279) | void BeforeFirst() override { method Next (line 285) | bool Next() override { method DataInst (line 314) | const DataInst& Value() const override { FILE: src/io/iter_image_recordio_2.cc type mxnet (line 47) | namespace mxnet { type io (line 49) | namespace io { class ImageRecordIOParser2 (line 52) | class ImageRecordIOParser2 { method BeforeFirst (line 58) | inline void BeforeFirst() { function is_jpeg (line 473) | bool is_jpeg(unsigned char* file) { class ImageRecordIter2 (line 707) | class ImageRecordIter2 : public IIterator { method ImageRecordIter2 (line 709) | ImageRecordIter2() = default; method Init (line 715) | void Init(const std::vector>& ... method BeforeFirst (line 733) | void BeforeFirst() override { method Next (line 738) | bool Next() override { method DataBatch (line 756) | const DataBatch& Value() const override { class ImageRecordIter2CPU (line 774) | class ImageRecordIter2CPU : public IIterator { method ImageRecordIter2CPU (line 776) | ImageRecordIter2CPU() { method Init (line 786) | void Init(const std::vector>& ... method BeforeFirst (line 790) | void BeforeFirst() override { method Next (line 795) | bool Next() override { method DataBatch (line 809) | const DataBatch& Value() const override { class ImageRecordIter2Wrapper (line 825) | class ImageRecordIter2Wrapper : public IIterator { method Init (line 831) | void Init(const std::vector>& ... method BeforeFirst (line 873) | void BeforeFirst() override { method Next (line 878) | bool Next() override { method DataBatch (line 882) | const DataBatch& Value() const override { FILE: src/io/iter_libsvm.cc type mxnet (line 32) | namespace mxnet { type io (line 33) | namespace io { type LibSVMIterParam (line 35) | struct LibSVMIterParam : public dmlc::Parameter { method DMLC_DECLARE_PARAMETER (line 49) | DMLC_DECLARE_PARAMETER(LibSVMIterParam) { class LibSVMIter (line 67) | class LibSVMIter : public SparseIIterator { method LibSVMIter (line 69) | LibSVMIter() = default; method Init (line 73) | void Init(const std::vector >&... method BeforeFirst (line 98) | void BeforeFirst() override { method Next (line 109) | bool Next() override { method DataInst (line 147) | const DataInst& Value() const override { method NDArrayStorageType (line 151) | const NDArrayStorageType GetStorageType(bool is_data) const overri... method GetShape (line 157) | const mxnet::TShape GetShape(bool is_data) const override { method TBlob (line 164) | inline TBlob AsDataBlob(const dmlc::Row& row) { method TBlob (line 170) | inline TBlob AsIdxBlob(const dmlc::Row& row) { method TBlob (line 176) | inline TBlob AsIndPtrPlaceholder(const dmlc::Row& row) { method TBlob (line 180) | inline TBlob AsScalarLabelBlob(const dmlc::Row& row) { FILE: src/io/iter_mnist.cc type mxnet (line 36) | namespace mxnet { type io (line 37) | namespace io { type MNISTParam (line 39) | struct MNISTParam : public dmlc::Parameter { method DMLC_DECLARE_PARAMETER (line 57) | DMLC_DECLARE_PARAMETER(MNISTParam) { class MNISTIter (line 80) | class MNISTIter : public IIterator { method MNISTIter (line 82) | MNISTIter() { method Init (line 90) | void Init(const std::vector >&... method BeforeFirst (line 119) | void BeforeFirst() override { method Next (line 122) | bool Next() override { method TBlobBatch (line 139) | const TBlobBatch& Value() const override { method GetPart (line 144) | inline void GetPart(int count, int* start, int* end) { method LoadImage (line 154) | inline void LoadImage() { method LoadLabel (line 186) | inline void LoadLabel() { method Shuffle (line 207) | inline void Shuffle() { method ReadInt (line 222) | inline static int ReadInt(dmlc::Stream* fi) { FILE: src/io/iter_normalize.h function namespace (line 40) | namespace mxnet { FILE: src/io/iter_prefetcher.h function namespace (line 43) | namespace mxnet { FILE: src/io/iter_sampler.cc type mxnet (line 35) | namespace mxnet { type io (line 36) | namespace io { type SequentialSamplerParam (line 37) | struct SequentialSamplerParam : public dmlc::Parameter { method Init (line 53) | void Init(const std::vector >&... method BeforeFirst (line 60) | void BeforeFirst() override { method GetLenHint (line 64) | int64_t GetLenHint() const override { method Next (line 68) | bool Next() override { method DataInst (line 83) | const DataInst& Value() const override { type RandomSamplerParam (line 105) | struct RandomSamplerParam : public dmlc::Parameter { method Init (line 118) | void Init(const std::vector >&... method BeforeFirst (line 130) | void BeforeFirst() override { method GetLenHint (line 135) | int64_t GetLenHint() const override { method Next (line 139) | bool Next() override { method DataInst (line 154) | const DataInst& Value() const override { FILE: src/io/iter_sparse.h function namespace (line 30) | namespace mxnet { FILE: src/io/iter_sparse_batchloader.h function namespace (line 39) | namespace mxnet { FILE: src/io/iter_sparse_prefetcher.h function namespace (line 45) | namespace mxnet { FILE: src/ir/expr.cc type mxnet (line 28) | namespace mxnet { FILE: src/kvstore/comm.h function namespace (line 36) | namespace mxnet { function class (line 482) | class CommDevice : public Comm { function InitBuffersAndComm (line 498) | void InitBuffersAndComm(const std::vector& src) { function NDArray (line 586) | const NDArray& ReduceCompressed(int key, const std::vector& src... function Broadcast (line 634) | void Broadcast(int key, function BroadcastRowSparse (line 656) | void BroadcastRowSparse(int key, function InitMergeBuffer (line 725) | void InitMergeBuffer(const std::vector& devs) { FILE: src/kvstore/comm_tree.h function namespace (line 37) | namespace mxnet { FILE: src/kvstore/gpu_topology.h function namespace (line 40) | namespace mxnet { function GetRoot (line 489) | inline int GetRoot(const std::vector& P, int color, const std::unor... function GetChild (line 501) | inline int GetChild(const std::vector& P, int color, int parent) { function FindBestEdge (line 519) | void FindBestEdge(const std::vector& W, function KLGenerateBinaryTree (line 555) | int KLGenerateBinaryTree(const std::vector& W, function ComputeDepth (line 643) | inline int ComputeDepth(int n) { function IsValid (line 658) | bool IsValid(const std::vector& W, function Postprocess (line 740) | inline void Postprocess(std::vector* result, int num_elements, int ... function T (line 771) | T ComputeTreeWeight(const std::vector& W, function FormTopology (line 828) | inline bool FormTopology(const std::vector& result, function RecursiveBacktrack (line 860) | bool RecursiveBacktrack(const std::vector& W, function IterativeBacktrack (line 896) | void IterativeBacktrack(const std::vector& W, function UpdateWeight (line 966) | void UpdateWeight(std::vector* W, function BacktrackGenerateBinaryTree (line 991) | bool BacktrackGenerateBinaryTree(std::vector* W, function ComputeTreesFromRoot (line 1035) | void ComputeTreesFromRoot(std::vector* W, function ComputeTrees (line 1127) | void ComputeTrees(const std::vector& W, FILE: src/kvstore/gradient_compression-inl.h function namespace (line 31) | namespace mxnet { function else (line 99) | struct dequantize_1bit { type quantize_2bit (line 135) | struct quantize_2bit { type dequantize_2bit (line 190) | struct dequantize_2bit { function Quantize1BitImpl (line 235) | inline void Quantize1BitImpl(mshadow::Stream* s, function Dequantize1BitImpl (line 241) | inline void Dequantize1BitImpl(mshadow::Stream* s, function Quantize2BitImpl (line 247) | inline void Quantize2BitImpl(mshadow::Stream* s, function Dequantize2BitImpl (line 253) | inline void Dequantize2BitImpl(mshadow::Stream* s, FILE: src/kvstore/gradient_compression.cc type mxnet (line 31) | namespace mxnet { type kvstore (line 32) | namespace kvstore { function CompressionType (line 54) | CompressionType GradientCompression::get_type() { FILE: src/kvstore/gradient_compression.h function namespace (line 35) | namespace kvstore { FILE: src/kvstore/kvstore.cc type mxnet (line 39) | namespace mxnet { function KVStore (line 41) | KVStore* KVStore::Create(const char* type_name) { FILE: src/kvstore/kvstore_dist.h function namespace (line 34) | namespace mxnet { function virtual (line 445) | virtual void PushDefault(int key, const NDArray& send_buf, const PSKV& p... function virtual (line 469) | virtual void PushRowSparse(int key, const NDArray& send_buf, int priorit... function virtual (line 501) | virtual void PullDefault(int key, const NDArray& recv_buf, int priority) { function PushAsync (line 527) | CHECK_NOTNULL(Engine::Get()) function PushAsync (line 607) | CHECK_NOTNULL(Engine::Get()) function virtual (line 690) | virtual inline PSKV& EncodeCompressedKey(const int key, function virtual (line 782) | virtual inline PSKV& EncodeRowSparseKey(const int key, FILE: src/kvstore/kvstore_dist_server.h function CommandType (line 45) | enum class CommandType { FILE: src/kvstore/kvstore_local.h function namespace (line 41) | namespace mxnet { function SetKeyType (line 336) | void SetKeyType(const KeyType key_type) { function virtual (line 342) | virtual void BroadcastImpl(const std::vector& vkeys, function virtual (line 351) | virtual void PushPullImpl(const std::vector& vkeys, function virtual (line 363) | virtual void GroupKVPairsPush(const std::vector& keys, function virtual (line 384) | virtual void GroupKVPairsPull(const std::vector& keys, type std (line 406) | typedef std::pair RSPVal; function virtual (line 410) | virtual void GroupKVPairsPullRsp(const std::vector& keys, FILE: src/kvstore/kvstore_nccl.h function class (line 62) | class KVStoreNCCL : public KVStoreLocal { function virtual (line 321) | virtual void Broadcast(const std::vector keys, function ncclDataType_t (line 462) | ncclDataType_t GetNCCLType(int dtype) { function InitNCCL (line 482) | void InitNCCL(const std::vector& devs) { function InitMergeBuffer (line 503) | void InitMergeBuffer(const std::vector& devs) { function T (line 518) | T* ptr(const T& obj) { function T (line 523) | T* ptr(T* obj) { type BufferEntry (line 543) | struct BufferEntry { type NCCLEntry (line 547) | struct NCCLEntry { FILE: src/kvstore/kvstore_utils.cc type mxnet (line 28) | namespace mxnet { type kvstore (line 29) | namespace kvstore { FILE: src/kvstore/kvstore_utils.h function namespace (line 33) | namespace mxnet { FILE: src/lib_api.cc function MX_INT_RET (line 1006) | MX_INT_RET _opVersion() { function MX_INT_RET (line 1011) | MX_INT_RET _opRegSize() { function MX_VOID_RET (line 1016) | MX_VOID_RET _opRegGet(int idx, function MX_VOID_RET (line 1054) | MX_VOID_RET _opCallFree(void* ptr) { function MX_INT_RET (line 1059) | MX_INT_RET _opCallParseAttrs(mxnet::ext::parseAttrs_t parseAttrs, function MX_INT_RET (line 1074) | MX_INT_RET _opCallInferShape(mxnet::ext::inferShape_t inferShape, function MX_INT_RET (line 1136) | MX_INT_RET _opCallInferType(mxnet::ext::inferType_t inferType, function MX_INT_RET (line 1176) | MX_INT_RET _opCallInferSType(mxnet::ext::inferSType_t inferSType, function MX_INT_RET (line 1217) | MX_INT_RET _opCallFCompute(mxnet::ext::fcomp_t fcomp, function MX_INT_RET (line 1357) | MX_INT_RET _opCallMutateInputs(mxnet::ext::mutateInputs_t mutate, function MX_INT_RET (line 1387) | MX_INT_RET _opCallCreateOpState(mxnet::ext::createOpState_t create_op, function MX_VOID_RET (line 1428) | MX_VOID_RET _opCallDestroyOpState(void* state_op) { function MX_INT_RET (line 1434) | MX_INT_RET _opCallFStatefulCompute(int is_forward, function MX_INT_RET (line 1572) | MX_INT_RET _partRegSize() { function MX_INT_RET (line 1578) | MX_INT_RET _partRegGetCount(int idx, const char** name) { function MX_VOID_RET (line 1586) | MX_VOID_RET _partRegGet(int part_idx, function MX_INT_RET (line 1603) | MX_INT_RET _partCallSupportedOps(mxnet::ext::supportedOps_t supportedOps, function MX_INT_RET (line 1631) | MX_INT_RET _partCallCreateSelector(mxnet::ext::createSelector_t createSe... function MX_VOID_RET (line 1653) | MX_VOID_RET _partCallSelect(void* sel_inst, int nodeID, int* selected) { function MX_VOID_RET (line 1659) | MX_VOID_RET _partCallSelectInput(void* sel_inst, int nodeID, int input_n... function MX_VOID_RET (line 1665) | MX_VOID_RET _partCallSelectOutput(void* sel_inst, int nodeID, int output... function MX_VOID_RET (line 1671) | MX_VOID_RET _partCallFilter(void* sel_inst, function MX_VOID_RET (line 1692) | MX_VOID_RET _partCallReset(void* sel_inst) { function MX_INT_RET (line 1698) | MX_INT_RET _partCallReviewSubgraph(mxnet::ext::reviewSubgraph_t reviewSu... function MX_INT_RET (line 1796) | MX_INT_RET _passRegSize() { function MX_VOID_RET (line 1801) | MX_VOID_RET _passRegGet(int pass_idx, mxnet::ext::graphPass_t* graphPass... function MX_INT_RET (line 1808) | MX_INT_RET _passCallGraphPass(mxnet::ext::graphPass_t graphPass, function MX_INT_RET (line 1900) | MX_INT_RET _msgSize() { function MX_VOID_RET (line 1905) | MX_VOID_RET _msgGet(int idx, const char** msg) { FILE: src/ndarray/ndarray_function.cc type mxnet (line 33) | namespace mxnet { type ndarray (line 34) | namespace ndarray { function ElementwiseSumRspImpl (line 61) | void ElementwiseSumRspImpl(mshadow::Stream* s, function GetUniqueRspRowIdx (line 125) | void GetUniqueRspRowIdx(const std::vector& nds, std::vector... function ElementwiseSumRsp (line 155) | void ElementwiseSumRsp(mshadow::Stream* s, function ElementwiseSumDnsCsrDnsImpl (line 178) | void ElementwiseSumDnsCsrDnsImpl(mshadow::Stream* s, function ElementwiseSumContainsDnsImpl (line 216) | void ElementwiseSumContainsDnsImpl(mshadow::Stream* s, FILE: src/nnvm/error.h function namespace (line 26) | namespace nnvm {