SYMBOL INDEX (589 symbols across 57 files)

FILE: examples/assistant.py
  function get_slot (line 51) | def get_slot(results, name, default='', threshold=0, merge=True):
  function generate_response (line 77) | def generate_response(query):

FILE: examples/nlp_qa.py
  function print_context (line 42) | def print_context():
  function parse_commands (line 46) | def parse_commands(entry):

FILE: jetson_voice/asr.py
  function ASR (line 7) | def ASR(resource, *args, **kwargs):
  class ASRService (line 21) | class ASRService():
    method __init__ (line 25) | def __init__(self, config, *args, **kwargs):
    method __call__ (line 28) | def __call__(self, samples):
    method classification (line 49) | def classification(self):
    method sample_rate (line 57) | def sample_rate(self):
    method frame_length (line 65) | def frame_length(self):
    method chunk_size (line 72) | def chunk_size(self):

FILE: jetson_voice/auto.py
  function AutoModel (line 11) | def AutoModel(resource, domain=None, *args, **kwargs):

FILE: jetson_voice/backends/onnxruntime/ort_model.py
  class OnnxRuntimeModel (line 16) | class OnnxRuntimeModel:
    method __init__ (line 20) | def __init__(self, config, *args, **kwargs):
    method execute (line 40) | def execute(self, inputs, return_dict=False, **kwargs):

FILE: jetson_voice/backends/riva/riva_asr.py
  class RivaASRService (line 18) | class RivaASRService(ASRService):
    method __init__ (line 22) | def __init__(self, config, *args, **kwargs):
    method __call__ (line 67) | def __call__(self, samples):
    method __next__ (line 99) | def __next__(self):
    method recieve_responses (line 111) | def recieve_responses(self):
    method sample_rate (line 140) | def sample_rate(self):
    method frame_length (line 148) | def frame_length(self):
    method chunk_size (line 155) | def chunk_size(self):

FILE: jetson_voice/backends/riva/riva_tts.py
  class RivaTTSService (line 16) | class RivaTTSService(TTSService):
    method __init__ (line 20) | def __init__(self, config, *args, **kwargs):
    method __call__ (line 37) | def __call__(self, text):
    method sample_rate (line 60) | def sample_rate(self):

FILE: jetson_voice/backends/tensorrt/trt_binding.py
  class Binding (line 11) | class Binding:
    method __init__ (line 15) | def __init__(self, model, index):
    method alloc (line 43) | def alloc(self, shape=None):
    method set_shape (line 61) | def set_shape(self, shape):
    method query_shape (line 85) | def query_shape(self):
    method __str__ (line 109) | def __str__(self):

FILE: jetson_voice/backends/tensorrt/trt_builder.py
  function build_engine (line 15) | def build_engine(config,

FILE: jetson_voice/backends/tensorrt/trt_model.py
  class TRTModel (line 20) | class TRTModel:
    method __init__ (line 24) | def __init__(self, config, dynamic_shapes=None, *args, **kwargs):
    method execute (line 81) | def execute(self, inputs, sync=True, return_dict=False, **kwargs):
    method find_binding (line 154) | def find_binding(self, name):
    method set_shape (line 164) | def set_shape(self, binding, shape):

FILE: jetson_voice/models/asr/asr_engine.py
  class ASREngine (line 19) | class ASREngine(ASRService):
    method __init__ (line 24) | def __init__(self, config, *args, **kwargs):
    method __call__ (line 140) | def __call__(self, samples):
    method classification (line 199) | def classification(self):
    method sample_rate (line 206) | def sample_rate(self):
    method frame_length (line 214) | def frame_length(self):
    method frame_overlap (line 221) | def frame_overlap(self):
    method chunk_size (line 228) | def chunk_size(self):
  function torch_to_numpy (line 235) | def torch_to_numpy(tensor):

FILE: jetson_voice/models/asr/ctc_beamsearch.py
  class CTCBeamSearchDecoder (line 16) | class CTCBeamSearchDecoder(CTCDecoder):
    method __init__ (line 20) | def __init__(self, config, vocab, resource_path=None):
    method decode (line 61) | def decode(self, logits):
    method reset (line 143) | def reset(self):
    method language_model (line 152) | def language_model(self):

FILE: jetson_voice/models/asr/ctc_decoder.py
  class CTCDecoder (line 5) | class CTCDecoder:
    method from_config (line 10) | def from_config(config, vocab, resource_path=None):
    method __init__ (line 29) | def __init__(self, config, vocab):
    method decode (line 41) | def decode(self, logits):
    method reset (line 59) | def reset(self):
    method set_timestep (line 65) | def set_timestep(self, timestep):
    method set_timestep_delta (line 71) | def set_timestep_delta(self, offset):
    method set_timestep_duration (line 77) | def set_timestep_duration(self, duration):
    method type (line 85) | def type(self):

FILE: jetson_voice/models/asr/ctc_greedy.py
  class CTCGreedyDecoder (line 13) | class CTCGreedyDecoder(CTCDecoder):
    method __init__ (line 17) | def __init__(self, config, vocab):
    method decode (line 36) | def decode(self, logits):
    method merge_chars (line 103) | def merge_chars(self, text, probs):
    method reset (line 147) | def reset(self):

FILE: jetson_voice/models/asr/ctc_utils.py
  function transcript_from_words (line 10) | def transcript_from_words(words, scores=False, times=False, end=False, a...
  function find_overlapping_word (line 36) | def find_overlapping_word(wordlist, word):
  function find_word_after (line 47) | def find_word_after(wordlist, time):
  function find_word_before (line 62) | def find_word_before(wordlist, time):
  function merge_words (line 77) | def merge_words(wordlist, words, score_threshold=-np.inf, method='overla...
  function split_words (line 141) | def split_words(wordlist, times):
  function rebase_word_times (line 162) | def rebase_word_times(wordlist):
  function find_silent_intervals (line 179) | def find_silent_intervals(logits, blank_symbol_id, min_silent_time, time...

FILE: jetson_voice/models/nlp/intent_slot.py
  class IntentSlotEngine (line 15) | class IntentSlotEngine(IntentSlotService):
    method __init__ (line 19) | def __init__(self, config, *args, **kwargs):
    method __call__ (line 41) | def __call__(self, query):
    method intent_labels (line 133) | def intent_labels(self):
    method intent_label (line 139) | def intent_label(self, index):
    method slot_labels (line 146) | def slot_labels(self):
    method slot_label (line 152) | def slot_label(self, index):

FILE: jetson_voice/models/nlp/nlp_utils.py
  function find_subtokens (line 12) | def find_subtokens(encodings, method='char_span'):

FILE: jetson_voice/models/nlp/question_answer.py
  class QuestionAnswerEngine (line 15) | class QuestionAnswerEngine(QuestionAnswerService):
    method __init__ (line 19) | def __init__(self, config, *args, **kwargs):
    method __call__ (line 41) | def __call__(self, query, top_k=1):
    method decode (line 198) | def decode(self, start: np.ndarray, end: np.ndarray, top_k: int):

FILE: jetson_voice/models/nlp/text_classification.py
  class TextClassificationEngine (line 15) | class TextClassificationEngine(TextClassificationService):
    method __init__ (line 19) | def __init__(self, config, *args, **kwargs):
    method __call__ (line 40) | def __call__(self, query):

FILE: jetson_voice/models/nlp/token_classification.py
  class TokenClassificationEngine (line 15) | class TokenClassificationEngine(TokenClassificationService):
    method __init__ (line 19) | def __init__(self, config, *args, **kwargs):
    method __call__ (line 40) | def __call__(self, query):

FILE: jetson_voice/models/tts/tts_engine.py
  class TTSEngine (line 15) | class TTSEngine(TTSService):
    method __init__ (line 21) | def __init__(self, config, *args, **kwargs):
    method __call__ (line 55) | def __call__(self, text):
    method get_symbols (line 85) | def get_symbols(self):
    method numbers_to_words (line 106) | def numbers_to_words(self, text):
    method sample_rate (line 124) | def sample_rate(self):

FILE: jetson_voice/nlp.py
  function NLP (line 7) | def NLP(resource, *args, **kwargs):
  function IntentSlot (line 21) | def IntentSlot(resource, *args, **kwargs):
  class IntentSlotService (line 34) | class IntentSlotService():
    method __init__ (line 38) | def __init__(self, config, *args, **kwargs):
    method __call__ (line 44) | def __call__(self, query):
  function QuestionAnswer (line 63) | def QuestionAnswer(resource, *args, **kwargs):
  class QuestionAnswerService (line 76) | class QuestionAnswerService():
    method __init__ (line 80) | def __init__(self, config, *args, **kwargs):
    method __call__ (line 86) | def __call__(self, query, top_k=1):
  function TextClassification (line 111) | def TextClassification(resource, *args, **kwargs):
  class TextClassificationService (line 124) | class TextClassificationService():
    method __init__ (line 128) | def __init__(self, config, *args, **kwargs):
    method __call__ (line 134) | def __call__(self, query):
  function TokenClassification (line 150) | def TokenClassification(resource, *args, **kwargs):
  class TokenClassificationService (line 163) | class TokenClassificationService():
    method __init__ (line 167) | def __init__(self, config, *args, **kwargs):
    method __call__ (line 173) | def __call__(self, query):
    method tag_string (line 192) | def tag_string(query, tags, scores=False):

FILE: jetson_voice/tts.py
  function TTS (line 7) | def TTS(resource, *args, **kwargs):
  class TTSService (line 21) | class TTSService():
    method __init__ (line 25) | def __init__(self, config, *args, **kwargs):
    method __call__ (line 31) | def __call__(self, text):
    method sample_rate (line 43) | def sample_rate(self):

FILE: jetson_voice/utils/audio.py
  function audio_db (line 15) | def audio_db(samples):
  function audio_to_float (line 27) | def audio_to_float(samples):
  function audio_to_int16 (line 37) | def audio_to_int16(samples):
  function AudioInput (line 49) | def AudioInput(wav=None, mic=None, sample_rate=16000, chunk_size=16000):
  class AudioWavStream (line 70) | class AudioWavStream:
    method __init__ (line 74) | def __init__(self, filename, sample_rate, chunk_size):
    method open (line 87) | def open(self):
    method close (line 90) | def close(self):
    method reset (line 93) | def reset(self):
    method next (line 96) | def next(self):
    method __next__ (line 108) | def __next__(self):
    method __iter__ (line 116) | def __iter__(self):
  class AudioMicStream (line 121) | class AudioMicStream:
    method __init__ (line 125) | def __init__(self, device, sample_rate, chunk_size):
    method __del__ (line 140) | def __del__(self):
    method open (line 144) | def open(self):
    method close (line 183) | def close(self):
    method reset (line 189) | def reset(self):
    method next (line 193) | def next(self):
    method __next__ (line 208) | def __next__(self):
    method __iter__ (line 216) | def __iter__(self):
  class AudioOutput (line 221) | class AudioOutput:
    method __init__ (line 225) | def __init__(self, device, sample_rate, chunk_size=4096):
    method __del__ (line 245) | def __del__(self):
    method open (line 252) | def open(self):
    method close (line 272) | def close(self):
    method write (line 278) | def write(self, samples):
  function _get_audio_devices (line 299) | def _get_audio_devices(audio_interface=None):
  function find_audio_device (line 324) | def find_audio_device(device, audio_interface=None):
  function list_audio_inputs (line 353) | def list_audio_inputs():
  function list_audio_outputs (line 372) | def list_audio_outputs():
  function list_audio_devices (line 391) | def list_audio_devices():

FILE: jetson_voice/utils/config.py
  class ConfigDict (line 36) | class ConfigDict(dict):
    method __init__ (line 41) | def __init__(self, *args, path=None, watch=None, **kwargs):
    method load (line 70) | def load(self, path, clear=False):
    method __getattr__ (line 87) | def __getattr__(self, attr):
    method __setattr__ (line 93) | def __setattr__(self, attr, value):
    method __setitem__ (line 99) | def __setitem__(self, key, value):
    method __watch__ (line 107) | def __watch__(self, key, value):
    method __str__ (line 119) | def __str__(self):
    method setdefault (line 125) | def setdefault(self, key, default=None):
    method update (line 136) | def update(self, *args, **kwargs):
  function _set_log_level (line 148) | def _set_log_level(key, value):
  class ConfigArgParser (line 179) | class ConfigArgParser(argparse.ArgumentParser):
    method __init__ (line 183) | def __init__(self, *args, **kwargs):
    method parse_args (line 200) | def parse_args(self, *args, **kwargs):

FILE: jetson_voice/utils/resource.py
  function find_resource (line 17) | def find_resource(path):
  function load_resource (line 38) | def load_resource(resource, factory_map, *args, **kwargs):
  function load_model (line 88) | def load_model(config, dynamic_shapes=None):
  function load_models_manifest (line 120) | def load_models_manifest(path=None):
  function find_model_manifest (line 139) | def find_model_manifest(name):
  function download_model (line 162) | def download_model(name, max_attempts=10, retry_time=5):
  function get_model_config_path (line 220) | def get_model_config_path(name=None, manifest=None):
  function list_models (line 239) | def list_models():

FILE: jetson_voice/utils/softmax.py
  function softmax (line 7) | def softmax(x, theta=1.0, axis=None):
  function normalize_logits (line 51) | def normalize_logits(logits):

FILE: patches/nemo/1.0.0rc1/exportable.original.py
  class ExportFormat (line 39) | class ExportFormat(Enum):
  class Exportable (line 52) | class Exportable(ABC):
    method get_format (line 59) | def get_format(filename: str):
    method input_module (line 67) | def input_module(self):
    method output_module (line 71) | def output_module(self):
    method get_input_names (line 74) | def get_input_names(self, input_example):
    method get_output_names (line 88) | def get_output_names(self, output_example):
    method get_input_dynamic_axes (line 102) | def get_input_dynamic_axes(self, input_names):
    method get_output_dynamic_axes (line 111) | def get_output_dynamic_axes(self, output_names):
    method export (line 120) | def export(
    method disabled_deployment_input_names (line 256) | def disabled_deployment_input_names(self):
    method disabled_deployment_output_names (line 261) | def disabled_deployment_output_names(self):
    method supported_export_formats (line 266) | def supported_export_formats(self):
    method _extract_dynamic_axes (line 271) | def _extract_dynamic_axes(name: str, ntype: NeuralType):
    method _prepare_for_export (line 294) | def _prepare_for_export(self, replace_1D_2D=False):

FILE: patches/nemo/1.0.0rc1/exportable.py
  class ExportFormat (line 39) | class ExportFormat(Enum):
  class Exportable (line 52) | class Exportable(ABC):
    method get_format (line 59) | def get_format(filename: str):
    method input_module (line 67) | def input_module(self):
    method output_module (line 71) | def output_module(self):
    method get_input_names (line 74) | def get_input_names(self, input_example):
    method get_output_names (line 88) | def get_output_names(self, output_example):
    method get_input_dynamic_axes (line 102) | def get_input_dynamic_axes(self, input_names):
    method get_output_dynamic_axes (line 111) | def get_output_dynamic_axes(self, output_names):
    method export (line 120) | def export(
    method disabled_deployment_input_names (line 274) | def disabled_deployment_input_names(self):
    method disabled_deployment_output_names (line 279) | def disabled_deployment_output_names(self):
    method supported_export_formats (line 284) | def supported_export_formats(self):
    method _extract_dynamic_axes (line 289) | def _extract_dynamic_axes(name: str, ntype: NeuralType):
    method _prepare_for_export (line 312) | def _prepare_for_export(self, replace_1D_2D=False):

FILE: patches/nemo/1.0.0rc1/nlp/distilbert.original.py
  class DistilBertEncoder (line 25) | class DistilBertEncoder(DistilBertModel, BertModule):
    method forward (line 31) | def forward(self, input_ids, attention_mask, token_type_ids=None):

FILE: patches/nemo/1.0.0rc1/nlp/distilbert.py
  class DistilBertEncoder (line 27) | class DistilBertEncoder(DistilBertModel, BertModule):
    method input_types (line 33) | def input_types(self) -> Optional[Dict[str, NeuralType]]:
    method forward (line 55) | def forward(self, input_ids, attention_mask, token_type_ids=None):

FILE: patches/nemo/1.0.0rc1/nlp/huggingface_utils.py
  function get_huggingface_lm_model (line 77) | def get_huggingface_lm_model(
  function get_huggingface_pretrained_lm_models_list (line 118) | def get_huggingface_pretrained_lm_models_list(include_external: bool = F...

FILE: patches/nemo/1.0.0rc1/nlp/mobilebert.py
  class MobileBertEncoder (line 25) | class MobileBertEncoder(MobileBertModel, BertModule):
    method forward (line 31) | def forward(self, input_ids, attention_mask, token_type_ids):

FILE: patches/nemo/1.0.0rc1/setup.original.py
  function is_build_action (line 31) | def is_build_action():
  function req_file (line 80) | def req_file(filename, folder="requirements"):
  class StyleCommand (line 153) | class StyleCommand(distutils_cmd.Command):
    method __call_checker (line 168) | def __call_checker(self, base_command, scope, check):
    method _isort (line 184) | def _isort(self, scope, check):
    method _black (line 187) | def _black(self, scope, check):
    method _pass (line 190) | def _pass(self):
    method _fail (line 193) | def _fail(self):
    method initialize_options (line 197) | def initialize_options(self):
    method run (line 201) | def run(self):
    method finalize_options (line 212) | def finalize_options(self):

FILE: patches/nemo/1.0.0rc1/setup.py
  function is_build_action (line 31) | def is_build_action():
  function req_file (line 80) | def req_file(filename, folder="requirements"):
  class StyleCommand (line 153) | class StyleCommand(distutils_cmd.Command):
    method __call_checker (line 168) | def __call_checker(self, base_command, scope, check):
    method _isort (line 184) | def _isort(self, scope, check):
    method _black (line 187) | def _black(self, scope, check):
    method _pass (line 190) | def _pass(self):
    method _fail (line 193) | def _fail(self):
    method initialize_options (line 197) | def initialize_options(self):
    method run (line 201) | def run(self):
    method finalize_options (line 212) | def finalize_options(self):

FILE: patches/pytorch/1.6.0/functional.original.py
  function broadcast_tensors (line 36) | def broadcast_tensors(*tensors):
  function split (line 68) | def split(tensor, split_size_or_sections, dim=0):
  function _indices_product (line 118) | def _indices_product(indices):
  function _index_tensor_with_indices_list (line 130) | def _index_tensor_with_indices_list(tensor, indices):
  function lu_unpack (line 137) | def lu_unpack(LU_data, LU_pivots, unpack_data=True, unpack_pivots=True):
  function einsum (line 243) | def einsum(equation, *operands):
  function meshgrid (line 330) | def meshgrid(*tensors):
  function stft (line 368) | def stft(input, n_fft, hop_length=None, win_length=None, window=None,
  function istft (line 468) | def istft(input, n_fft, hop_length=None, win_length=None, window=None,
  function _unique_impl (line 533) | def _unique_impl(input, sorted=True, return_inverse=False, return_counts...
  function _unique_consecutive_impl (line 617) | def _unique_consecutive_impl(input, return_inverse=False, return_counts=...
  function _return_counts (line 678) | def _return_counts(input, sorted=True, return_inverse=False, return_coun...
  function _return_output (line 688) | def _return_output(input, sorted=True, return_inverse=False, return_coun...
  function _return_inverse (line 698) | def _return_inverse(input, sorted=True, return_inverse=False, return_cou...
  function _consecutive_return_counts (line 740) | def _consecutive_return_counts(input, return_inverse=False, return_count...
  function _consecutive_return_output (line 750) | def _consecutive_return_output(input, return_inverse=False, return_count...
  function _consecutive_return_inverse (line 760) | def _consecutive_return_inverse(input, return_inverse=False, return_coun...
  function tensordot (line 802) | def tensordot(a, b, dims=2):
  function cartesian_prod (line 861) | def cartesian_prod(*tensors):
  function block_diag (line 894) | def block_diag(*tensors):
  function cdist (line 929) | def cdist(x1, x2, p=2., compute_mode='use_mm_for_euclid_dist_if_necessar...
  function norm (line 986) | def norm(input, p="fro", dim=None, keepdim=False, out=None, dtype=None):...
  function norm (line 991) | def norm(input, p="fro", dim=None, keepdim=False, out=None, dtype=None):...
  function norm (line 996) | def norm(input, p="fro", dim=None, keepdim=False, out=None, dtype=None):...
  function norm (line 1001) | def norm(input, p="fro", dim=None, keepdim=False, out=None, dtype=None):...
  function norm (line 1005) | def norm(input, p="fro", dim=None, keepdim=False, out=None, dtype=None):...
  function chain_matmul (line 1132) | def chain_matmul(*matrices):
  function _lu_impl (line 1167) | def _lu_impl(A, pivot=True, get_infos=False, out=None):
  function _check_list_size (line 1241) | def _check_list_size(out_len, get_infos, out):
  function _lu_with_infos (line 1251) | def _lu_with_infos(A, pivot=True, get_infos=False, out=None):
  function _lu_no_infos (line 1266) | def _lu_no_infos(A, pivot=True, get_infos=False, out=None):
  function align_tensors (line 1294) | def align_tensors(*tensors):

FILE: patches/pytorch/1.6.0/functional.py
  function broadcast_tensors (line 39) | def broadcast_tensors(*tensors):
  function split (line 71) | def split(tensor, split_size_or_sections, dim=0):
  function _indices_product (line 121) | def _indices_product(indices):
  function _index_tensor_with_indices_list (line 133) | def _index_tensor_with_indices_list(tensor, indices):
  function lu_unpack (line 140) | def lu_unpack(LU_data, LU_pivots, unpack_data=True, unpack_pivots=True):
  function einsum (line 246) | def einsum(equation, *operands):
  function meshgrid (line 333) | def meshgrid(*tensors):
  function stft (line 371) | def stft(input, n_fft, hop_length=None, win_length=None, window=None,
  function istft (line 481) | def istft(input, n_fft, hop_length=None, win_length=None, window=None,
  function _unique_impl (line 546) | def _unique_impl(input, sorted=True, return_inverse=False, return_counts...
  function _unique_consecutive_impl (line 630) | def _unique_consecutive_impl(input, return_inverse=False, return_counts=...
  function _return_counts (line 691) | def _return_counts(input, sorted=True, return_inverse=False, return_coun...
  function _return_output (line 701) | def _return_output(input, sorted=True, return_inverse=False, return_coun...
  function _return_inverse (line 711) | def _return_inverse(input, sorted=True, return_inverse=False, return_cou...
  function _consecutive_return_counts (line 753) | def _consecutive_return_counts(input, return_inverse=False, return_count...
  function _consecutive_return_output (line 763) | def _consecutive_return_output(input, return_inverse=False, return_count...
  function _consecutive_return_inverse (line 773) | def _consecutive_return_inverse(input, return_inverse=False, return_coun...
  function tensordot (line 815) | def tensordot(a, b, dims=2):
  function cartesian_prod (line 874) | def cartesian_prod(*tensors):
  function block_diag (line 907) | def block_diag(*tensors):
  function cdist (line 942) | def cdist(x1, x2, p=2., compute_mode='use_mm_for_euclid_dist_if_necessar...
  function norm (line 999) | def norm(input, p="fro", dim=None, keepdim=False, out=None, dtype=None):...
  function norm (line 1004) | def norm(input, p="fro", dim=None, keepdim=False, out=None, dtype=None):...
  function norm (line 1009) | def norm(input, p="fro", dim=None, keepdim=False, out=None, dtype=None):...
  function norm (line 1014) | def norm(input, p="fro", dim=None, keepdim=False, out=None, dtype=None):...
  function norm (line 1018) | def norm(input, p="fro", dim=None, keepdim=False, out=None, dtype=None):...
  function chain_matmul (line 1145) | def chain_matmul(*matrices):
  function _lu_impl (line 1180) | def _lu_impl(A, pivot=True, get_infos=False, out=None):
  function _check_list_size (line 1254) | def _check_list_size(out_len, get_infos, out):
  function _lu_with_infos (line 1264) | def _lu_with_infos(A, pivot=True, get_infos=False, out=None):
  function _lu_no_infos (line 1279) | def _lu_no_infos(A, pivot=True, get_infos=False, out=None):
  function align_tensors (line 1307) | def align_tensors(*tensors):

FILE: patches/pytorch/1.7.0/functional.original.py
  function broadcast_tensors (line 42) | def broadcast_tensors(*tensors):
  function split (line 74) | def split(tensor, split_size_or_sections, dim=0):
  function _indices_product (line 131) | def _indices_product(indices: _Indices) -> List[List[int]]:
  function _index_tensor_with_indices_list (line 143) | def _index_tensor_with_indices_list(tensor, indices):
  function lu_unpack (line 151) | def lu_unpack(LU_data, LU_pivots, unpack_data=True, unpack_pivots=True):
  function einsum (line 261) | def einsum(equation, *operands):
  function meshgrid (line 349) | def meshgrid(*tensors: Union[Tensor, List[Tensor]]) -> Tuple[Tensor, ...]:
  function meshgrid (line 352) | def meshgrid(*tensors):
  function _meshgrid (line 356) | def _meshgrid(*tensors):
  function stft (line 394) | def stft(input: Tensor, n_fft: int, hop_length: Optional[int] = None,
  function istft (line 518) | def istft(input: Tensor, n_fft: int, hop_length: Optional[int] = None,
  function _unique_impl (line 602) | def _unique_impl(input: Tensor, sorted: bool = True,
  function _unique_consecutive_impl (line 687) | def _unique_consecutive_impl(input: Tensor, return_inverse: bool = False,
  function _return_counts (line 749) | def _return_counts(input, sorted=True, return_inverse=False, return_coun...
  function _return_output (line 760) | def _return_output(input, sorted=True, return_inverse=False, return_coun...
  function _return_inverse (line 771) | def _return_inverse(input, sorted=True, return_inverse=False, return_cou...
  function _consecutive_return_counts (line 814) | def _consecutive_return_counts(input, return_inverse=False, return_count...
  function _consecutive_return_output (line 825) | def _consecutive_return_output(input, return_inverse=False, return_count...
  function _consecutive_return_inverse (line 836) | def _consecutive_return_inverse(input, return_inverse=False, return_coun...
  function tensordot (line 879) | def tensordot(a, b, dims=2):
  function cartesian_prod (line 938) | def cartesian_prod(*tensors):
  function block_diag (line 971) | def block_diag(*tensors):
  function cdist (line 1006) | def cdist(x1, x2, p=2., compute_mode='use_mm_for_euclid_dist_if_necessar...
  function atleast_1d (line 1061) | def atleast_1d(*tensors):
  function atleast_2d (line 1095) | def atleast_2d(*tensors):
  function atleast_3d (line 1130) | def atleast_3d(*tensors):
  function norm (line 1191) | def norm(input, p="fro", dim=None, keepdim=False, out=None, dtype=None):...
  function norm (line 1196) | def norm(input, p="fro", dim=None, keepdim=False, out=None, dtype=None):...
  function norm (line 1201) | def norm(input, p="fro", dim=None, keepdim=False, out=None, dtype=None):...
  function norm (line 1206) | def norm(input, p="fro", dim=None, keepdim=False, out=None, dtype=None):...
  function norm (line 1211) | def norm(input, p="fro", dim=None, keepdim=False, out=None, dtype=None):...
  function chain_matmul (line 1346) | def chain_matmul(*matrices):
  function _lu_impl (line 1381) | def _lu_impl(A, pivot=True, get_infos=False, out=None):
  function _check_list_size (line 1461) | def _check_list_size(out_len: int, get_infos: bool, out: _ListOrSeq) -> ...
  function _lu_with_infos (line 1468) | def _lu_with_infos(A, pivot=True, get_infos=False, out=None):
  function _lu_no_infos (line 1483) | def _lu_no_infos(A, pivot=True, get_infos=False, out=None):
  function align_tensors (line 1511) | def align_tensors(*tensors):

FILE: patches/pytorch/1.7.0/functional.py
  function broadcast_tensors (line 45) | def broadcast_tensors(*tensors):
  function split (line 77) | def split(tensor, split_size_or_sections, dim=0):
  function _indices_product (line 134) | def _indices_product(indices: _Indices) -> List[List[int]]:
  function _index_tensor_with_indices_list (line 146) | def _index_tensor_with_indices_list(tensor, indices):
  function lu_unpack (line 154) | def lu_unpack(LU_data, LU_pivots, unpack_data=True, unpack_pivots=True):
  function einsum (line 264) | def einsum(equation, *operands):
  function meshgrid (line 352) | def meshgrid(*tensors: Union[Tensor, List[Tensor]]) -> Tuple[Tensor, ...]:
  function meshgrid (line 355) | def meshgrid(*tensors):
  function _meshgrid (line 359) | def _meshgrid(*tensors):
  function stft (line 397) | def stft(input: Tensor, n_fft: int, hop_length: Optional[int] = None,
  function istft (line 530) | def istft(input: Tensor, n_fft: int, hop_length: Optional[int] = None,
  function _unique_impl (line 614) | def _unique_impl(input: Tensor, sorted: bool = True,
  function _unique_consecutive_impl (line 699) | def _unique_consecutive_impl(input: Tensor, return_inverse: bool = False,
  function _return_counts (line 761) | def _return_counts(input, sorted=True, return_inverse=False, return_coun...
  function _return_output (line 772) | def _return_output(input, sorted=True, return_inverse=False, return_coun...
  function _return_inverse (line 783) | def _return_inverse(input, sorted=True, return_inverse=False, return_cou...
  function _consecutive_return_counts (line 826) | def _consecutive_return_counts(input, return_inverse=False, return_count...
  function _consecutive_return_output (line 837) | def _consecutive_return_output(input, return_inverse=False, return_count...
  function _consecutive_return_inverse (line 848) | def _consecutive_return_inverse(input, return_inverse=False, return_coun...
  function tensordot (line 891) | def tensordot(a, b, dims=2):
  function cartesian_prod (line 950) | def cartesian_prod(*tensors):
  function block_diag (line 983) | def block_diag(*tensors):
  function cdist (line 1018) | def cdist(x1, x2, p=2., compute_mode='use_mm_for_euclid_dist_if_necessar...
  function atleast_1d (line 1073) | def atleast_1d(*tensors):
  function atleast_2d (line 1107) | def atleast_2d(*tensors):
  function atleast_3d (line 1142) | def atleast_3d(*tensors):
  function norm (line 1203) | def norm(input, p="fro", dim=None, keepdim=False, out=None, dtype=None):...
  function norm (line 1208) | def norm(input, p="fro", dim=None, keepdim=False, out=None, dtype=None):...
  function norm (line 1213) | def norm(input, p="fro", dim=None, keepdim=False, out=None, dtype=None):...
  function norm (line 1218) | def norm(input, p="fro", dim=None, keepdim=False, out=None, dtype=None):...
  function norm (line 1223) | def norm(input, p="fro", dim=None, keepdim=False, out=None, dtype=None):...
  function chain_matmul (line 1358) | def chain_matmul(*matrices):
  function _lu_impl (line 1393) | def _lu_impl(A, pivot=True, get_infos=False, out=None):
  function _check_list_size (line 1473) | def _check_list_size(out_len: int, get_infos: bool, out: _ListOrSeq) -> ...
  function _lu_with_infos (line 1480) | def _lu_with_infos(A, pivot=True, get_infos=False, out=None):
  function _lu_no_infos (line 1495) | def _lu_no_infos(A, pivot=True, get_infos=False, out=None):
  function align_tensors (line 1523) | def align_tensors(*tensors):

FILE: patches/transformers/4.5.0/convert_graph_to_onnx.original.py
  class OnnxConverterArgumentParser (line 45) | class OnnxConverterArgumentParser(ArgumentParser):
    method __init__ (line 50) | def __init__(self):
  function generate_identified_filename (line 91) | def generate_identified_filename(filename: Path, identifier: str) -> Path:
  function check_onnxruntime_requirements (line 104) | def check_onnxruntime_requirements(minimum_version: Version):
  function ensure_valid_input (line 133) | def ensure_valid_input(model, tokens, input_names):
  function infer_shapes (line 161) | def infer_shapes(nlp: Pipeline, framework: str) -> Tuple[List[str], List...
  function load_graph_from_args (line 225) | def load_graph_from_args(
  function convert_pytorch (line 256) | def convert_pytorch(nlp: Pipeline, opset: int, output: Path, use_externa...
  function convert_tensorflow (line 295) | def convert_tensorflow(nlp: Pipeline, opset: int, output: Path):
  function convert (line 332) | def convert(
  function optimize (line 376) | def optimize(onnx_model_path: Path) -> Path:
  function quantize (line 401) | def quantize(onnx_model_path: Path) -> Path:
  function verify (line 438) | def verify(path: Path):

FILE: patches/transformers/4.5.0/convert_graph_to_onnx.py
  class OnnxConverterArgumentParser (line 48) | class OnnxConverterArgumentParser(ArgumentParser):
    method __init__ (line 53) | def __init__(self):
  function generate_identified_filename (line 99) | def generate_identified_filename(filename: Path, identifier: str) -> Path:
  function check_onnxruntime_requirements (line 112) | def check_onnxruntime_requirements(minimum_version: Version):
  function ensure_valid_input (line 141) | def ensure_valid_input(model, tokens, input_names):
  function infer_shapes (line 169) | def infer_shapes(nlp: Pipeline, framework: str) -> Tuple[List[str], List...
  function load_graph_from_args (line 233) | def load_graph_from_args(
  function convert_pytorch (line 264) | def convert_pytorch(nlp: Pipeline, opset: int, output: Path, use_externa...
  function convert_tensorflow (line 311) | def convert_tensorflow(nlp: Pipeline, opset: int, output: Path):
  function convert (line 348) | def convert(
  function optimize (line 409) | def optimize(onnx_model_path: Path) -> Path:
  function quantize (line 434) | def quantize(onnx_model_path: Path) -> Path:
  function verify (line 471) | def verify(path: Path):

FILE: patches/transformers/4.5.0/modeling_distilbert.py
  function create_sinusoidal_embeddings (line 74) | def create_sinusoidal_embeddings(n_pos, dim, out):
  class Embeddings (line 82) | class Embeddings(nn.Module):
    method __init__ (line 83) | def __init__(self, config):
    method forward (line 95) | def forward(self, input_ids):
  class MultiHeadSelfAttention (line 116) | class MultiHeadSelfAttention(nn.Module):
    method __init__ (line 117) | def __init__(self, config):
    method prune_heads (line 133) | def prune_heads(self, heads):
    method forward (line 148) | def forward(self, query, key, value, mask, head_mask=None, output_atte...
  class FFN (line 203) | class FFN(nn.Module):
    method __init__ (line 204) | def __init__(self, config):
    method forward (line 214) | def forward(self, input):
    method ff_chunk (line 217) | def ff_chunk(self, input):
  class TransformerBlock (line 225) | class TransformerBlock(nn.Module):
    method __init__ (line 226) | def __init__(self, config):
    method forward (line 237) | def forward(self, x, attn_mask=None, head_mask=None, output_attentions...
  class Transformer (line 273) | class Transformer(nn.Module):
    method __init__ (line 274) | def __init__(self, config):
    method forward (line 281) | def forward(
  class DistilBertPreTrainedModel (line 330) | class DistilBertPreTrainedModel(PreTrainedModel):
    method _init_weights (line 340) | def _init_weights(self, module):
  class DistilBertModel (line 416) | class DistilBertModel(DistilBertPreTrainedModel):
    method __init__ (line 417) | def __init__(self, config):
    method get_input_embeddings (line 425) | def get_input_embeddings(self):
    method set_input_embeddings (line 428) | def set_input_embeddings(self, new_embeddings):
    method _prune_heads (line 431) | def _prune_heads(self, heads_to_prune):
    method forward (line 446) | def forward(
  class DistilBertForMaskedLM (line 495) | class DistilBertForMaskedLM(DistilBertPreTrainedModel):
    method __init__ (line 496) | def __init__(self, config):
    method get_output_embeddings (line 508) | def get_output_embeddings(self):
    method set_output_embeddings (line 511) | def set_output_embeddings(self, new_embeddings):
    method forward (line 521) | def forward(
  class DistilBertForSequenceClassification (line 578) | class DistilBertForSequenceClassification(DistilBertPreTrainedModel):
    method __init__ (line 579) | def __init__(self, config):
    method forward (line 597) | def forward(
  class DistilBertForQuestionAnswering (line 660) | class DistilBertForQuestionAnswering(DistilBertPreTrainedModel):
    method __init__ (line 661) | def __init__(self, config):
    method forward (line 678) | def forward(
  class DistilBertForTokenClassification (line 756) | class DistilBertForTokenClassification(DistilBertPreTrainedModel):
    method __init__ (line 757) | def __init__(self, config):
    method forward (line 774) | def forward(
  class DistilBertForMultipleChoice (line 840) | class DistilBertForMultipleChoice(DistilBertPreTrainedModel):
    method __init__ (line 841) | def __init__(self, config):
    method forward (line 855) | def forward(

FILE: patches/transformers/4.5.1/convert_graph_to_onnx.original.py
  class OnnxConverterArgumentParser (line 45) | class OnnxConverterArgumentParser(ArgumentParser):
    method __init__ (line 50) | def __init__(self):
  function generate_identified_filename (line 91) | def generate_identified_filename(filename: Path, identifier: str) -> Path:
  function check_onnxruntime_requirements (line 104) | def check_onnxruntime_requirements(minimum_version: Version):
  function ensure_valid_input (line 133) | def ensure_valid_input(model, tokens, input_names):
  function infer_shapes (line 161) | def infer_shapes(nlp: Pipeline, framework: str) -> Tuple[List[str], List...
  function load_graph_from_args (line 225) | def load_graph_from_args(
  function convert_pytorch (line 256) | def convert_pytorch(nlp: Pipeline, opset: int, output: Path, use_externa...
  function convert_tensorflow (line 295) | def convert_tensorflow(nlp: Pipeline, opset: int, output: Path):
  function convert (line 332) | def convert(
  function optimize (line 376) | def optimize(onnx_model_path: Path) -> Path:
  function quantize (line 401) | def quantize(onnx_model_path: Path) -> Path:
  function verify (line 438) | def verify(path: Path):

FILE: patches/transformers/4.5.1/convert_graph_to_onnx.py
  class OnnxConverterArgumentParser (line 48) | class OnnxConverterArgumentParser(ArgumentParser):
    method __init__ (line 53) | def __init__(self):
  function generate_identified_filename (line 99) | def generate_identified_filename(filename: Path, identifier: str) -> Path:
  function check_onnxruntime_requirements (line 112) | def check_onnxruntime_requirements(minimum_version: Version):
  function ensure_valid_input (line 141) | def ensure_valid_input(model, tokens, input_names):
  function infer_shapes (line 169) | def infer_shapes(nlp: Pipeline, framework: str) -> Tuple[List[str], List...
  function load_graph_from_args (line 233) | def load_graph_from_args(
  function convert_pytorch (line 264) | def convert_pytorch(nlp: Pipeline, opset: int, output: Path, use_externa...
  function convert_tensorflow (line 311) | def convert_tensorflow(nlp: Pipeline, opset: int, output: Path):
  function convert (line 348) | def convert(
  function optimize (line 409) | def optimize(onnx_model_path: Path) -> Path:
  function quantize (line 434) | def quantize(onnx_model_path: Path) -> Path:
  function verify (line 471) | def verify(path: Path):

FILE: patches/transformers/4.5.1/modeling_distilbert.original.py
  function create_sinusoidal_embeddings (line 74) | def create_sinusoidal_embeddings(n_pos, dim, out):
  class Embeddings (line 82) | class Embeddings(nn.Module):
    method __init__ (line 83) | def __init__(self, config):
    method forward (line 95) | def forward(self, input_ids):
  class MultiHeadSelfAttention (line 116) | class MultiHeadSelfAttention(nn.Module):
    method __init__ (line 117) | def __init__(self, config):
    method prune_heads (line 133) | def prune_heads(self, heads):
    method forward (line 148) | def forward(self, query, key, value, mask, head_mask=None, output_atte...
  class FFN (line 203) | class FFN(nn.Module):
    method __init__ (line 204) | def __init__(self, config):
    method forward (line 214) | def forward(self, input):
    method ff_chunk (line 217) | def ff_chunk(self, input):
  class TransformerBlock (line 225) | class TransformerBlock(nn.Module):
    method __init__ (line 226) | def __init__(self, config):
    method forward (line 237) | def forward(self, x, attn_mask=None, head_mask=None, output_attentions...
  class Transformer (line 273) | class Transformer(nn.Module):
    method __init__ (line 274) | def __init__(self, config):
    method forward (line 281) | def forward(
  class DistilBertPreTrainedModel (line 330) | class DistilBertPreTrainedModel(PreTrainedModel):
    method _init_weights (line 340) | def _init_weights(self, module):
  class DistilBertModel (line 416) | class DistilBertModel(DistilBertPreTrainedModel):
    method __init__ (line 417) | def __init__(self, config):
    method get_input_embeddings (line 425) | def get_input_embeddings(self):
    method set_input_embeddings (line 428) | def set_input_embeddings(self, new_embeddings):
    method _prune_heads (line 431) | def _prune_heads(self, heads_to_prune):
    method forward (line 446) | def forward(
  class DistilBertForMaskedLM (line 495) | class DistilBertForMaskedLM(DistilBertPreTrainedModel):
    method __init__ (line 496) | def __init__(self, config):
    method get_output_embeddings (line 508) | def get_output_embeddings(self):
    method set_output_embeddings (line 511) | def set_output_embeddings(self, new_embeddings):
    method forward (line 521) | def forward(
  class DistilBertForSequenceClassification (line 578) | class DistilBertForSequenceClassification(DistilBertPreTrainedModel):
    method __init__ (line 579) | def __init__(self, config):
    method forward (line 597) | def forward(
  class DistilBertForQuestionAnswering (line 660) | class DistilBertForQuestionAnswering(DistilBertPreTrainedModel):
    method __init__ (line 661) | def __init__(self, config):
    method forward (line 678) | def forward(
  class DistilBertForTokenClassification (line 756) | class DistilBertForTokenClassification(DistilBertPreTrainedModel):
    method __init__ (line 757) | def __init__(self, config):
    method forward (line 774) | def forward(
  class DistilBertForMultipleChoice (line 840) | class DistilBertForMultipleChoice(DistilBertPreTrainedModel):
    method __init__ (line 841) | def __init__(self, config):
    method forward (line 855) | def forward(

FILE: patches/transformers/4.5.1/modeling_distilbert.py
  function create_sinusoidal_embeddings (line 74) | def create_sinusoidal_embeddings(n_pos, dim, out):
  class Embeddings (line 82) | class Embeddings(nn.Module):
    method __init__ (line 83) | def __init__(self, config):
    method forward (line 95) | def forward(self, input_ids):
  class MultiHeadSelfAttention (line 116) | class MultiHeadSelfAttention(nn.Module):
    method __init__ (line 117) | def __init__(self, config):
    method prune_heads (line 133) | def prune_heads(self, heads):
    method forward (line 148) | def forward(self, query, key, value, mask, head_mask=None, output_atte...
  class FFN (line 203) | class FFN(nn.Module):
    method __init__ (line 204) | def __init__(self, config):
    method forward (line 214) | def forward(self, input):
    method ff_chunk (line 217) | def ff_chunk(self, input):
  class TransformerBlock (line 225) | class TransformerBlock(nn.Module):
    method __init__ (line 226) | def __init__(self, config):
    method forward (line 237) | def forward(self, x, attn_mask=None, head_mask=None, output_attentions...
  class Transformer (line 273) | class Transformer(nn.Module):
    method __init__ (line 274) | def __init__(self, config):
    method forward (line 281) | def forward(
  class DistilBertPreTrainedModel (line 330) | class DistilBertPreTrainedModel(PreTrainedModel):
    method _init_weights (line 340) | def _init_weights(self, module):
  class DistilBertModel (line 416) | class DistilBertModel(DistilBertPreTrainedModel):
    method __init__ (line 417) | def __init__(self, config):
    method get_input_embeddings (line 425) | def get_input_embeddings(self):
    method set_input_embeddings (line 428) | def set_input_embeddings(self, new_embeddings):
    method _prune_heads (line 431) | def _prune_heads(self, heads_to_prune):
    method forward (line 446) | def forward(
  class DistilBertForMaskedLM (line 495) | class DistilBertForMaskedLM(DistilBertPreTrainedModel):
    method __init__ (line 496) | def __init__(self, config):
    method get_output_embeddings (line 508) | def get_output_embeddings(self):
    method set_output_embeddings (line 511) | def set_output_embeddings(self, new_embeddings):
    method forward (line 521) | def forward(
  class DistilBertForSequenceClassification (line 578) | class DistilBertForSequenceClassification(DistilBertPreTrainedModel):
    method __init__ (line 579) | def __init__(self, config):
    method forward (line 597) | def forward(
  class DistilBertForQuestionAnswering (line 660) | class DistilBertForQuestionAnswering(DistilBertPreTrainedModel):
    method __init__ (line 661) | def __init__(self, config):
    method forward (line 678) | def forward(
  class DistilBertForTokenClassification (line 756) | class DistilBertForTokenClassification(DistilBertPreTrainedModel):
    method __init__ (line 757) | def __init__(self, config):
    method forward (line 774) | def forward(
  class DistilBertForMultipleChoice (line 840) | class DistilBertForMultipleChoice(DistilBertPreTrainedModel):
    method __init__ (line 841) | def __init__(self, config):
    method forward (line 855) | def forward(

FILE: ros/jetson_voice_ros/asr.py
  class ASRNode (line 13) | class ASRNode(Node):
    method __init__ (line 14) | def __init__(self):
    method audio_listener (line 34) | def audio_listener(self, msg):
  function main (line 60) | def main(args=None):

FILE: ros/jetson_voice_ros/audio_input.py
  class AudioInputNode (line 12) | class AudioInputNode(Node):
    method __init__ (line 13) | def __init__(self):
    method publish_audio (line 58) | def publish_audio(self):
  function main (line 99) | def main(args=None):

FILE: ros/jetson_voice_ros/audio_output.py
  class AudioOutputNode (line 14) | class AudioOutputNode(Node):
    method __init__ (line 15) | def __init__(self):
    method audio_listener (line 47) | def audio_listener(self, msg):
  function main (line 65) | def main(args=None):

FILE: ros/jetson_voice_ros/nlp_intent_slot.py
  class NLPIntentSlotNode (line 12) | class NLPIntentSlotNode(Node):
    method __init__ (line 13) | def __init__(self):
    method query_listener (line 29) | def query_listener(self, msg):
  function main (line 70) | def main(args=None):

FILE: ros/jetson_voice_ros/nlp_question_answer.py
  class NLPQuestionAnswerNode (line 12) | class NLPQuestionAnswerNode(Node):
    method __init__ (line 13) | def __init__(self):
    method query_listener (line 29) | def query_listener(self, msg):
  function main (line 58) | def main(args=None):

FILE: ros/jetson_voice_ros/tts.py
  class TTSNode (line 14) | class TTSNode(Node):
    method __init__ (line 15) | def __init__(self):
    method text_listener (line 31) | def text_listener(self, msg):
  function main (line 57) | def main(args=None):

FILE: ros/launch/asr.launch.py
  function generate_launch_description (line 13) | def generate_launch_description():

FILE: ros/launch/audio_playback.launch.py
  function generate_launch_description (line 13) | def generate_launch_description():

FILE: ros/launch/tts.launch.py
  function generate_launch_description (line 13) | def generate_launch_description():

FILE: scripts/record_mic.py
  function signal_handler (line 30) | def signal_handler(sig, frame):

FILE: tests/run_tests.py
  function run_test (line 32) | def run_test(module, model, config, args=None, log_dir=None):
  function filter_test (line 62) | def filter_test(test):