SYMBOL INDEX (805 symbols across 76 files)

FILE: api_231006.py
  class GUIConfig (line 27) | class GUIConfig:
    method __init__ (line 28) | def __init__(self) -> None:
  class ConfigData (line 46) | class ConfigData(BaseModel):
  class AudioAPI (line 62) | class AudioAPI:
    method __init__ (line 63) | def __init__(self) -> None:
    method load (line 71) | def load(self):
    method set_values (line 103) | def set_values(self, values):
    method start_vc (line 126) | def start_vc(self):
    method soundinput (line 206) | def soundinput(self):
    method audio_callback (line 222) | def audio_callback(self, indata: np.ndarray, outdata: np.ndarray, fram...
    method get_devices (line 294) | def get_devices(self, update: bool = True):
    method set_devices (line 330) | def set_devices(self, input_device, output_device):
  function get_input_devices (line 358) | def get_input_devices():
  function get_output_devices (line 367) | def get_output_devices():
  function configure_audio (line 376) | def configure_audio(config_data: ConfigData):
  function start_conversion (line 395) | def start_conversion():
  function stop_conversion (line 411) | def stop_conversion():

FILE: api_240604.py
  class GUIConfig (line 28) | class GUIConfig:
    method __init__ (line 29) | def __init__(self) -> None:
  class ConfigData (line 49) | class ConfigData(BaseModel):
  class Harvest (line 68) | class Harvest(Process):
    method __init__ (line 69) | def __init__(self, inp_q, opt_q):
    method run (line 74) | def run(self):
  class AudioAPI (line 90) | class AudioAPI:
    method __init__ (line 91) | def __init__(self) -> None:
    method initialize_queues (line 102) | def initialize_queues(self):
    method load (line 110) | def load(self):
    method set_values (line 143) | def set_values(self, values):
    method start_vc (line 168) | def start_vc(self):
    method soundinput (line 279) | def soundinput(self):
    method audio_callback (line 295) | def audio_callback(self, indata: np.ndarray, outdata: np.ndarray, fram...
    method get_devices (line 420) | def get_devices(self, update: bool = True):
    method set_devices (line 456) | def set_devices(self, input_device, output_device):
  function get_input_devices (line 484) | def get_input_devices():
  function get_output_devices (line 493) | def get_output_devices():
  function configure_audio (line 502) | def configure_audio(config_data: ConfigData):
  function start_conversion (line 520) | def start_conversion():
  function stop_conversion (line 536) | def stop_conversion():

FILE: configs/config.py
  function singleton_variable (line 33) | def singleton_variable(func):
  class Config (line 44) | class Config:
    method __init__ (line 45) | def __init__(self):
    method load_config_json (line 66) | def load_config_json() -> dict:
    method arg_parse (line 77) | def arg_parse() -> tuple:
    method has_mps (line 112) | def has_mps() -> bool:
    method has_xpu (line 122) | def has_xpu() -> bool:
    method use_fp32_config (line 128) | def use_fp32_config(self):
    method device_config (line 139) | def device_config(self) -> tuple:

FILE: gui_v1.py
  function printt (line 19) | def printt(strr, *args):
  function phase_vocoder (line 26) | def phase_vocoder(a, b, fade_out, fade_in):
  class Harvest (line 50) | class Harvest(multiprocessing.Process):
    method __init__ (line 51) | def __init__(self, inp_q, opt_q):
    method run (line 56) | def run(self):
  class GUIConfig (line 114) | class GUIConfig:
    method __init__ (line 115) | def __init__(self) -> None:
  class GUI (line 137) | class GUI:
    method __init__ (line 138) | def __init__(self) -> None:
    method load (line 152) | def load(self):
    method launcher (line 223) | def launcher(self):
    method event_handler (line 534) | def event_handler(self):
    method set_values (line 655) | def set_values(self, values):
    method start_vc (line 707) | def start_vc(self):
    method start_stream (line 818) | def start_stream(self):
    method stop_stream (line 839) | def stop_stream(self):
    method audio_callback (line 848) | def audio_callback(
    method update_devices (line 1010) | def update_devices(self, hostapi_name=None):
    method set_devices (line 1045) | def set_devices(self, input_device, output_device):
    method get_device_samplerate (line 1056) | def get_device_samplerate(self):
    method get_device_channels (line 1061) | def get_device_channels(self):

FILE: i18n/i18n.py
  function load_language_list (line 6) | def load_language_list(language):
  class I18nAuto (line 12) | class I18nAuto:
    method __init__ (line 13) | def __init__(self, language=None):
    method __call__ (line 23) | def __call__(self, key):
    method __repr__ (line 26) | def __repr__(self):

FILE: i18n/scan_i18n.py
  function extract_i18n_strings (line 7) | def extract_i18n_strings(node):

FILE: infer-web.py
  function forward_dml (line 59) | def forward_dml(ctx, x, scale):
  class ToolButton (line 123) | class ToolButton(gr.Button, gr.components.FormComponent):
    method __init__ (line 126) | def __init__(self, **kwargs):
    method get_block_name (line 129) | def get_block_name(self):
  function lookup_indices (line 145) | def lookup_indices(index_root):
  function change_choices (line 161) | def change_choices():
  function clean (line 177) | def clean():
  function export_onnx (line 181) | def export_onnx(ModelPath, ExportedPath):
  function if_done (line 194) | def if_done(done, p):
  function if_done_multi (line 203) | def if_done_multi(done, ps):
  function preprocess_dataset (line 218) | def preprocess_dataset(trainset_dir, exp_dir, sr, n_p):
  function extract_f0_feature (line 258) | def extract_f0_feature(gpus, n_p, f0method, if_f0, exp_dir, version19, g...
  function get_pretrained_models (line 398) | def get_pretrained_models(path_str, f0_str, sr2):
  function change_sr2 (line 433) | def change_sr2(sr2, if_f0_3, version19):
  function change_version19 (line 439) | def change_version19(sr2, if_f0_3, version19):
  function change_f0 (line 455) | def change_f0(if_f0_3, sr2, version19):  # f0method8,pretrained_G14,pret...
  function click_train (line 465) | def click_train(
  function train_index (line 616) | def train_index(exp_dir1, version19):
  function train1key (line 715) | def train1key(
  function change_info_ (line 782) | def change_info_(ckpt_path):
  function change_f0_method (line 801) | def change_f0_method(f0method8):

FILE: infer/lib/audio.py
  function wav2 (line 10) | def wav2(i, o, format):
  function load_audio (line 33) | def load_audio(file, sr):
  function clean_path (line 56) | def clean_path(path_str):

FILE: infer/lib/infer_pack/attentions.py
  class Encoder (line 14) | class Encoder(nn.Module):
    method __init__ (line 15) | def __init__(
    method forward (line 62) | def forward(self, x, x_mask):
  class Decoder (line 80) | class Decoder(nn.Module):
    method __init__ (line 81) | def __init__(
    method forward (line 140) | def forward(self, x, x_mask, h, h_mask):
  class MultiHeadAttention (line 166) | class MultiHeadAttention(nn.Module):
    method __init__ (line 167) | def __init__(
    method forward (line 220) | def forward(
    method attention (line 232) | def attention(
    method _matmul_with_relative_values (line 290) | def _matmul_with_relative_values(self, x, y):
    method _matmul_with_relative_keys (line 299) | def _matmul_with_relative_keys(self, x, y):
    method _get_relative_embeddings (line 308) | def _get_relative_embeddings(self, relative_embeddings, length: int):
    method _relative_position_to_absolute_position (line 327) | def _relative_position_to_absolute_position(self, x):
    method _absolute_position_to_relative_position (line 354) | def _absolute_position_to_relative_position(self, x):
    method _attention_bias_proximal (line 376) | def _attention_bias_proximal(self, length: int):
  class FFN (line 388) | class FFN(nn.Module):
    method __init__ (line 389) | def __init__(
    method padding (line 417) | def padding(self, x: torch.Tensor, x_mask: torch.Tensor) -> torch.Tensor:
    method forward (line 424) | def forward(self, x: torch.Tensor, x_mask: torch.Tensor):
    method _causal_padding (line 435) | def _causal_padding(self, x):
    method _same_padding (line 448) | def _same_padding(self, x):

FILE: infer/lib/infer_pack/attentions_onnx.py
  class Encoder (line 22) | class Encoder(nn.Module):
    method __init__ (line 23) | def __init__(
    method forward (line 70) | def forward(self, x, x_mask):
  class Decoder (line 88) | class Decoder(nn.Module):
    method __init__ (line 89) | def __init__(
    method forward (line 148) | def forward(self, x, x_mask, h, h_mask):
  class MultiHeadAttention (line 174) | class MultiHeadAttention(nn.Module):
    method __init__ (line 175) | def __init__(
    method forward (line 228) | def forward(
    method attention (line 240) | def attention(
    method _matmul_with_relative_values (line 295) | def _matmul_with_relative_values(self, x, y):
    method _matmul_with_relative_keys (line 304) | def _matmul_with_relative_keys(self, x, y):
    method _get_relative_embeddings (line 313) | def _get_relative_embeddings(self, relative_embeddings, length):
    method _relative_position_to_absolute_position (line 330) | def _relative_position_to_absolute_position(self, x):
    method _absolute_position_to_relative_position (line 356) | def _absolute_position_to_relative_position(self, x):
    method _attention_bias_proximal (line 376) | def _attention_bias_proximal(self, length):
  class FFN (line 388) | class FFN(nn.Module):
    method __init__ (line 389) | def __init__(
    method padding (line 417) | def padding(self, x: torch.Tensor, x_mask: torch.Tensor) -> torch.Tensor:
    method forward (line 424) | def forward(self, x: torch.Tensor, x_mask: torch.Tensor):
    method _causal_padding (line 435) | def _causal_padding(self, x):
    method _same_padding (line 448) | def _same_padding(self, x):

FILE: infer/lib/infer_pack/commons.py
  function init_weights (line 10) | def init_weights(m, mean=0.0, std=0.01):
  function get_padding (line 16) | def get_padding(kernel_size, dilation=1):
  function kl_divergence (line 26) | def kl_divergence(m_p, logs_p, m_q, logs_q):
  function rand_gumbel (line 35) | def rand_gumbel(shape):
  function rand_gumbel_like (line 41) | def rand_gumbel_like(x):
  function slice_segments (line 46) | def slice_segments(x, ids_str, segment_size=4):
  function slice_segments2 (line 55) | def slice_segments2(x, ids_str, segment_size=4):
  function rand_slice_segments (line 64) | def rand_slice_segments(x, x_lengths=None, segment_size=4):
  function get_timing_signal_1d (line 74) | def get_timing_signal_1d(length, channels, min_timescale=1.0, max_timesc...
  function add_timing_signal_1d (line 90) | def add_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4):
  function cat_timing_signal_1d (line 96) | def cat_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4, axis...
  function subsequent_mask (line 102) | def subsequent_mask(length):
  function fused_add_tanh_sigmoid_multiply (line 108) | def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels):
  function convert_pad_shape (line 123) | def convert_pad_shape(pad_shape: List[List[int]]) -> List[int]:
  function shift_1d (line 127) | def shift_1d(x):
  function sequence_mask (line 132) | def sequence_mask(length: torch.Tensor, max_length: Optional[int] = None):
  function generate_path (line 139) | def generate_path(duration, mask):
  function clip_grad_value_ (line 157) | def clip_grad_value_(parameters, clip_value, norm_type=2):

FILE: infer/lib/infer_pack/models.py
  class TextEncoder (line 19) | class TextEncoder(nn.Module):
    method __init__ (line 20) | def __init__(
    method forward (line 54) | def forward(
  class ResidualCouplingBlock (line 82) | class ResidualCouplingBlock(nn.Module):
    method __init__ (line 83) | def __init__(
    method forward (line 117) | def forward(
    method remove_weight_norm (line 132) | def remove_weight_norm(self):
    method __prepare_scriptable__ (line 136) | def __prepare_scriptable__(self):
  class PosteriorEncoder (line 148) | class PosteriorEncoder(nn.Module):
    method __init__ (line 149) | def __init__(
    method forward (line 178) | def forward(
    method remove_weight_norm (line 191) | def remove_weight_norm(self):
    method __prepare_scriptable__ (line 194) | def __prepare_scriptable__(self):
  class Generator (line 204) | class Generator(torch.nn.Module):
    method __init__ (line 205) | def __init__(
    method forward (line 252) | def forward(
    method __prepare_scriptable__ (line 283) | def __prepare_scriptable__(self):
    method remove_weight_norm (line 305) | def remove_weight_norm(self):
  class SineGen (line 312) | class SineGen(torch.nn.Module):
    method __init__ (line 328) | def __init__(
    method _f02uv (line 345) | def _f02uv(self, f0):
    method _f02sine (line 353) | def _f02sine(self, f0, upp):
    method forward (line 371) | def forward(self, f0: torch.Tensor, upp: int):
  class SourceModuleHnNSF (line 391) | class SourceModuleHnNSF(torch.nn.Module):
    method __init__ (line 409) | def __init__(
    method forward (line 433) | def forward(self, x: torch.Tensor, upp: int = 1):
  class GeneratorNSF (line 448) | class GeneratorNSF(torch.nn.Module):
    method __init__ (line 449) | def __init__(
    method forward (line 522) | def forward(
    method remove_weight_norm (line 567) | def remove_weight_norm(self):
    method __prepare_scriptable__ (line 573) | def __prepare_scriptable__(self):
  class SynthesizerTrnMs256NSFsid (line 602) | class SynthesizerTrnMs256NSFsid(nn.Module):
    method __init__ (line 603) | def __init__(
    method remove_weight_norm (line 688) | def remove_weight_norm(self):
    method __prepare_scriptable__ (line 694) | def __prepare_scriptable__(self):
    method forward (line 721) | def forward(
    method infer (line 746) | def infer(
  class SynthesizerTrnMs768NSFsid (line 779) | class SynthesizerTrnMs768NSFsid(SynthesizerTrnMs256NSFsid):
    method __init__ (line 780) | def __init__(
  class SynthesizerTrnMs256NSFsid_nono (line 836) | class SynthesizerTrnMs256NSFsid_nono(nn.Module):
    method __init__ (line 837) | def __init__(
    method remove_weight_norm (line 919) | def remove_weight_norm(self):
    method __prepare_scriptable__ (line 925) | def __prepare_scriptable__(self):
    method forward (line 952) | def forward(self, phone, phone_lengths, y, y_lengths, ds):  # 这里ds是id，...
    method infer (line 964) | def infer(
  class SynthesizerTrnMs768NSFsid_nono (line 994) | class SynthesizerTrnMs768NSFsid_nono(SynthesizerTrnMs256NSFsid_nono):
    method __init__ (line 995) | def __init__(
  class MultiPeriodDiscriminator (line 1052) | class MultiPeriodDiscriminator(torch.nn.Module):
    method __init__ (line 1053) | def __init__(self, use_spectral_norm=False):
    method forward (line 1064) | def forward(self, y, y_hat):
  class MultiPeriodDiscriminatorV2 (line 1082) | class MultiPeriodDiscriminatorV2(torch.nn.Module):
    method __init__ (line 1083) | def __init__(self, use_spectral_norm=False):
    method forward (line 1094) | def forward(self, y, y_hat):
  class DiscriminatorS (line 1112) | class DiscriminatorS(torch.nn.Module):
    method __init__ (line 1113) | def __init__(self, use_spectral_norm=False):
    method forward (line 1128) | def forward(self, x):
  class DiscriminatorP (line 1142) | class DiscriminatorP(torch.nn.Module):
    method __init__ (line 1143) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=...
    method forward (line 1199) | def forward(self, x):

FILE: infer/lib/infer_pack/models_onnx.py
  class TextEncoder256 (line 27) | class TextEncoder256(nn.Module):
    method __init__ (line 28) | def __init__(
    method forward (line 56) | def forward(self, phone, pitch, lengths):
  class TextEncoder768 (line 74) | class TextEncoder768(nn.Module):
    method __init__ (line 75) | def __init__(
    method forward (line 103) | def forward(self, phone, pitch, lengths):
  class ResidualCouplingBlock (line 121) | class ResidualCouplingBlock(nn.Module):
    method __init__ (line 122) | def __init__(
    method forward (line 156) | def forward(self, x, x_mask, g=None, reverse=False):
    method remove_weight_norm (line 165) | def remove_weight_norm(self):
  class PosteriorEncoder (line 170) | class PosteriorEncoder(nn.Module):
    method __init__ (line 171) | def __init__(
    method forward (line 200) | def forward(self, x, x_lengths, g=None):
    method remove_weight_norm (line 211) | def remove_weight_norm(self):
  class Generator (line 215) | class Generator(torch.nn.Module):
    method __init__ (line 216) | def __init__(
    method forward (line 263) | def forward(self, x, g=None):
    method remove_weight_norm (line 284) | def remove_weight_norm(self):
  class SineGen (line 291) | class SineGen(torch.nn.Module):
    method __init__ (line 307) | def __init__(
    method _f02uv (line 324) | def _f02uv(self, f0):
    method _f02sine (line 332) | def _f02sine(self, f0, upp):
    method forward (line 350) | def forward(self, f0: torch.Tensor, upp: int):
  class SourceModuleHnNSF (line 370) | class SourceModuleHnNSF(torch.nn.Module):
    method __init__ (line 388) | def __init__(
    method forward (line 411) | def forward(self, x, upp=None):
  class GeneratorNSF (line 419) | class GeneratorNSF(torch.nn.Module):
    method __init__ (line 420) | def __init__(
    method forward (line 491) | def forward(self, x, f0, g=None):
    method remove_weight_norm (line 515) | def remove_weight_norm(self):
  class SynthesizerTrnMsNSFsidM (line 529) | class SynthesizerTrnMsNSFsidM(nn.Module):
    method __init__ (line 530) | def __init__(
    method remove_weight_norm (line 624) | def remove_weight_norm(self):
    method construct_spkmixmap (line 629) | def construct_spkmixmap(self, n_speaker):
    method forward (line 635) | def forward(self, phone, phone_lengths, pitch, nsff0, g, rnd, max_len=...
  class MultiPeriodDiscriminator (line 652) | class MultiPeriodDiscriminator(torch.nn.Module):
    method __init__ (line 653) | def __init__(self, use_spectral_norm=False):
    method forward (line 664) | def forward(self, y, y_hat):
  class MultiPeriodDiscriminatorV2 (line 682) | class MultiPeriodDiscriminatorV2(torch.nn.Module):
    method __init__ (line 683) | def __init__(self, use_spectral_norm=False):
    method forward (line 694) | def forward(self, y, y_hat):
  class DiscriminatorS (line 712) | class DiscriminatorS(torch.nn.Module):
    method __init__ (line 713) | def __init__(self, use_spectral_norm=False):
    method forward (line 728) | def forward(self, x):
  class DiscriminatorP (line 742) | class DiscriminatorP(torch.nn.Module):
    method __init__ (line 743) | def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=...
    method forward (line 799) | def forward(self, x):

FILE: infer/lib/infer_pack/modules.py
  class LayerNorm (line 20) | class LayerNorm(nn.Module):
    method __init__ (line 21) | def __init__(self, channels, eps=1e-5):
    method forward (line 29) | def forward(self, x):
  class ConvReluNorm (line 35) | class ConvReluNorm(nn.Module):
    method __init__ (line 36) | def __init__(
    method forward (line 77) | def forward(self, x, x_mask):
  class DDSConv (line 87) | class DDSConv(nn.Module):
    method __init__ (line 92) | def __init__(self, channels, kernel_size, n_layers, p_dropout=0.0):
    method forward (line 121) | def forward(self, x, x_mask, g: Optional[torch.Tensor] = None):
  class WN (line 136) | class WN(torch.nn.Module):
    method __init__ (line 137) | def __init__(
    method forward (line 188) | def forward(
    method remove_weight_norm (line 219) | def remove_weight_norm(self):
    method __prepare_scriptable__ (line 227) | def __prepare_scriptable__(self):
  class ResBlock1 (line 252) | class ResBlock1(torch.nn.Module):
    method __init__ (line 253) | def __init__(self, channels, kernel_size=3, dilation=(1, 3, 5)):
    method forward (line 328) | def forward(self, x: torch.Tensor, x_mask: Optional[torch.Tensor] = No...
    method remove_weight_norm (line 343) | def remove_weight_norm(self):
    method __prepare_scriptable__ (line 349) | def __prepare_scriptable__(self):
  class ResBlock2 (line 367) | class ResBlock2(torch.nn.Module):
    method __init__ (line 368) | def __init__(self, channels, kernel_size=3, dilation=(1, 3)):
    method forward (line 397) | def forward(self, x, x_mask: Optional[torch.Tensor] = None):
    method remove_weight_norm (line 408) | def remove_weight_norm(self):
    method __prepare_scriptable__ (line 412) | def __prepare_scriptable__(self):
  class Log (line 423) | class Log(nn.Module):
    method forward (line 424) | def forward(
  class Flip (line 440) | class Flip(nn.Module):
    method forward (line 444) | def forward(
  class ElementwiseAffine (line 459) | class ElementwiseAffine(nn.Module):
    method __init__ (line 460) | def __init__(self, channels):
    method forward (line 466) | def forward(self, x, x_mask, reverse=False, **kwargs):
  class ResidualCouplingLayer (line 477) | class ResidualCouplingLayer(nn.Module):
    method __init__ (line 478) | def __init__(
    method forward (line 512) | def forward(
    method remove_weight_norm (line 539) | def remove_weight_norm(self):
    method __prepare_scriptable__ (line 542) | def __prepare_scriptable__(self):
  class ConvFlow (line 552) | class ConvFlow(nn.Module):
    method __init__ (line 553) | def __init__(
    method forward (line 579) | def forward(

FILE: infer/lib/infer_pack/modules/F0Predictor/DioF0Predictor.py
  class DioF0Predictor (line 7) | class DioF0Predictor(F0Predictor):
    method __init__ (line 8) | def __init__(self, hop_length=512, f0_min=50, f0_max=1100, sampling_ra...
    method interpolate_f0 (line 14) | def interpolate_f0(self, f0):
    method resize_f0 (line 52) | def resize_f0(self, x, target_len):
    method compute_f0 (line 63) | def compute_f0(self, wav, p_len=None):
    method compute_f0_uv (line 78) | def compute_f0_uv(self, wav, p_len=None):

FILE: infer/lib/infer_pack/modules/F0Predictor/F0Predictor.py
  class F0Predictor (line 1) | class F0Predictor(object):
    method compute_f0 (line 2) | def compute_f0(self, wav, p_len):
    method compute_f0_uv (line 10) | def compute_f0_uv(self, wav, p_len):

FILE: infer/lib/infer_pack/modules/F0Predictor/HarvestF0Predictor.py
  class HarvestF0Predictor (line 7) | class HarvestF0Predictor(F0Predictor):
    method __init__ (line 8) | def __init__(self, hop_length=512, f0_min=50, f0_max=1100, sampling_ra...
    method interpolate_f0 (line 14) | def interpolate_f0(self, f0):
    method resize_f0 (line 52) | def resize_f0(self, x, target_len):
    method compute_f0 (line 63) | def compute_f0(self, wav, p_len=None):
    method compute_f0_uv (line 76) | def compute_f0_uv(self, wav, p_len=None):

FILE: infer/lib/infer_pack/modules/F0Predictor/PMF0Predictor.py
  class PMF0Predictor (line 7) | class PMF0Predictor(F0Predictor):
    method __init__ (line 8) | def __init__(self, hop_length=512, f0_min=50, f0_max=1100, sampling_ra...
    method interpolate_f0 (line 14) | def interpolate_f0(self, f0):
    method compute_f0 (line 52) | def compute_f0(self, wav, p_len=None):
    method compute_f0_uv (line 76) | def compute_f0_uv(self, wav, p_len=None):

FILE: infer/lib/infer_pack/onnx_inference.py
  class ContentVec (line 11) | class ContentVec:
    method __init__ (line 12) | def __init__(self, vec_path="pretrained/vec-768-layer-12.onnx", device...
    method __call__ (line 24) | def __call__(self, wav):
    method forward (line 27) | def forward(self, wav):
  function get_f0_predictor (line 38) | def get_f0_predictor(f0_predictor, hop_length, sampling_rate, **kargs):
  class OnnxRVC (line 64) | class OnnxRVC:
    method __init__ (line 65) | def __init__(
    method forward (line 87) | def forward(self, hubert, hubert_length, pitch, pitchf, ds, rnd):
    method inference (line 98) | def inference(

FILE: infer/lib/infer_pack/transforms.py
  function piecewise_rational_quadratic_transform (line 10) | def piecewise_rational_quadratic_transform(
  function searchsorted (line 43) | def searchsorted(bin_locations, inputs, eps=1e-6):
  function unconstrained_rational_quadratic_spline (line 48) | def unconstrained_rational_quadratic_spline(
  function rational_quadratic_spline (line 98) | def rational_quadratic_spline(

FILE: infer/lib/jit/__init__.py
  function load_inputs (line 9) | def load_inputs(path, device, is_half=False):
  function benchmark (line 20) | def benchmark(
  function jit_warm_up (line 33) | def jit_warm_up(model, inputs_path, device=torch.device("cpu"), epoch=5,...
  function to_jit_model (line 37) | def to_jit_model(
  function export (line 76) | def export(
  function load (line 102) | def load(path: str):
  function save (line 107) | def save(ckpt: dict, save_path: str):
  function rmvpe_jit_export (line 112) | def rmvpe_jit_export(
  function synthesizer_jit_export (line 137) | def synthesizer_jit_export(

FILE: infer/lib/jit/get_hubert.py
  function pad_to_multiple (line 14) | def pad_to_multiple(x, multiple, dim=-1, value=0):
  function extract_features (line 28) | def extract_features(
  function compute_mask_indices (line 95) | def compute_mask_indices(
  function apply_mask (line 227) | def apply_mask(self, x, padding_mask, target_list):
  function get_hubert_model (line 266) | def get_hubert_model(

FILE: infer/lib/jit/get_rmvpe.py
  function get_rmvpe (line 4) | def get_rmvpe(model_path="assets/rmvpe/rmvpe.pt", device=torch.device("c...

FILE: infer/lib/jit/get_synthesizer.py
  function get_synthesizer (line 4) | def get_synthesizer(pth_path, device=torch.device("cpu")):

FILE: infer/lib/rmvpe.py
  class STFT (line 29) | class STFT(torch.nn.Module):
    method __init__ (line 30) | def __init__(
    method transform (line 78) | def transform(self, input_data, return_phase=False):
    method inverse (line 109) | def inverse(self, magnitude, phase):
    method forward (line 144) | def forward(self, input_data):
  class BiGRU (line 162) | class BiGRU(nn.Module):
    method __init__ (line 163) | def __init__(self, input_features, hidden_features, num_layers):
    method forward (line 173) | def forward(self, x):
  class ConvBlockRes (line 177) | class ConvBlockRes(nn.Module):
    method __init__ (line 178) | def __init__(self, in_channels, out_channels, momentum=0.01):
    method forward (line 206) | def forward(self, x: torch.Tensor):
  class Encoder (line 213) | class Encoder(nn.Module):
    method __init__ (line 214) | def __init__(
    method forward (line 242) | def forward(self, x: torch.Tensor):
  class ResEncoderBlock (line 251) | class ResEncoderBlock(nn.Module):
    method __init__ (line 252) | def __init__(
    method forward (line 265) | def forward(self, x):
  class Intermediate (line 274) | class Intermediate(nn.Module):  #
    method __init__ (line 275) | def __init__(self, in_channels, out_channels, n_inters, n_blocks, mome...
    method forward (line 287) | def forward(self, x):
  class ResDecoderBlock (line 293) | class ResDecoderBlock(nn.Module):
    method __init__ (line 294) | def __init__(self, in_channels, out_channels, stride, n_blocks=1, mome...
    method forward (line 316) | def forward(self, x, concat_tensor):
  class Decoder (line 324) | class Decoder(nn.Module):
    method __init__ (line 325) | def __init__(self, in_channels, n_decoders, stride, n_blocks, momentum...
    method forward (line 336) | def forward(self, x: torch.Tensor, concat_tensors: List[torch.Tensor]):
  class DeepUnet (line 342) | class DeepUnet(nn.Module):
    method __init__ (line 343) | def __init__(
    method forward (line 366) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class E2E (line 373) | class E2E(nn.Module):
    method __init__ (line 374) | def __init__(
    method forward (line 406) | def forward(self, mel):
  class MelSpectrogram (line 418) | class MelSpectrogram(torch.nn.Module):
    method __init__ (line 419) | def __init__(
    method forward (line 452) | def forward(self, audio, keyshift=0, speed=1, center=True):
  class RMVPE (line 495) | class RMVPE:
    method __init__ (line 496) | def __init__(self, model_path: str, is_half, device=None, use_jit=False):
    method mel2hidden (line 569) | def mel2hidden(self, mel):
    method decode (line 587) | def decode(self, hidden, thred=0.03):
    method infer_from_audio (line 594) | def infer_from_audio(self, audio, thred=0.03):
    method to_local_average_cents (line 622) | def to_local_average_cents(self, salience, thred=0.05):

FILE: infer/lib/rtrvc.py
  function printt (line 31) | def printt(strr, *args):
  class RVC (line 40) | class RVC:
    method __init__ (line 41) | def __init__(
    method change_key (line 192) | def change_key(self, new_key):
    method change_formant (line 195) | def change_formant(self, new_formant):
    method change_index_rate (line 198) | def change_index_rate(self, new_index_rate):
    method get_f0_post (line 205) | def get_f0_post(self, f0):
    method get_f0 (line 218) | def get_f0(self, x, f0_up_key, n_cpu, method="harvest"):
    method get_f0_crepe (line 289) | def get_f0_crepe(self, x, f0_up_key):
    method get_f0_rmvpe (line 313) | def get_f0_rmvpe(self, x, f0_up_key):
    method get_f0_fcpe (line 328) | def get_f0_fcpe(self, x, f0_up_key):
    method infer (line 347) | def infer(

FILE: infer/lib/slicer2.py
  function get_rms (line 5) | def get_rms(
  class Slicer (line 38) | class Slicer:
    method __init__ (line 39) | def __init__(
    method _apply_slice (line 64) | def _apply_slice(self, waveform, begin, end):
    method slice (line 75) | def slice(self, waveform):
  function main (line 182) | def main():

FILE: infer/lib/train/data_utils.py
  class TextAudioLoaderMultiNSFsid (line 15) | class TextAudioLoaderMultiNSFsid(torch.utils.data.Dataset):
    method __init__ (line 22) | def __init__(self, audiopaths_and_text, hparams):
    method _filter (line 34) | def _filter(self):
    method get_sid (line 50) | def get_sid(self, sid):
    method get_audio_text_pair (line 54) | def get_audio_text_pair(self, audiopath_and_text):
    method get_labels (line 83) | def get_labels(self, phone, pitch, pitchf):
    method get_audio (line 98) | def get_audio(self, filename):
    method __getitem__ (line 140) | def __getitem__(self, index):
    method __len__ (line 143) | def __len__(self):
  class TextAudioCollateMultiNSFsid (line 147) | class TextAudioCollateMultiNSFsid:
    method __init__ (line 150) | def __init__(self, return_ids=False):
    method __call__ (line 153) | def __call__(self, batch):
  class TextAudioLoader (line 223) | class TextAudioLoader(torch.utils.data.Dataset):
    method __init__ (line 230) | def __init__(self, audiopaths_and_text, hparams):
    method _filter (line 242) | def _filter(self):
    method get_sid (line 258) | def get_sid(self, sid):
    method get_audio_text_pair (line 262) | def get_audio_text_pair(self, audiopath_and_text):
    method get_labels (line 282) | def get_labels(self, phone):
    method get_audio (line 290) | def get_audio(self, filename):
    method __getitem__ (line 332) | def __getitem__(self, index):
    method __len__ (line 335) | def __len__(self):
  class TextAudioCollate (line 339) | class TextAudioCollate:
    method __init__ (line 342) | def __init__(self, return_ids=False):
    method __call__ (line 345) | def __call__(self, batch):
  class DistributedBucketSampler (line 401) | class DistributedBucketSampler(torch.utils.data.distributed.DistributedS...
    method __init__ (line 411) | def __init__(
    method _create_buckets (line 429) | def _create_buckets(self):
    method __iter__ (line 452) | def __iter__(self):
    method _bisect (line 501) | def _bisect(self, x, lo=0, hi=None):
    method __len__ (line 516) | def __len__(self):

FILE: infer/lib/train/losses.py
  function feature_loss (line 4) | def feature_loss(fmap_r, fmap_g):
  function discriminator_loss (line 15) | def discriminator_loss(disc_real_outputs, disc_generated_outputs):
  function generator_loss (line 31) | def generator_loss(disc_outputs):
  function kl_loss (line 43) | def kl_loss(z_p, logs_q, m_p, logs_p, z_mask):

FILE: infer/lib/train/mel_processing.py
  function dynamic_range_compression_torch (line 11) | def dynamic_range_compression_torch(x, C=1, clip_val=1e-5):
  function dynamic_range_decompression_torch (line 20) | def dynamic_range_decompression_torch(x, C=1):
  function spectral_normalize_torch (line 29) | def spectral_normalize_torch(magnitudes):
  function spectral_de_normalize_torch (line 33) | def spectral_de_normalize_torch(magnitudes):
  function spectrogram_torch (line 42) | def spectrogram_torch(y, n_fft, sampling_rate, hop_size, win_size, cente...
  function spec_to_mel_torch (line 92) | def spec_to_mel_torch(spec, n_fft, num_mels, sampling_rate, fmin, fmax):
  function mel_spectrogram_torch (line 111) | def mel_spectrogram_torch(

FILE: infer/lib/train/process_ckpt.py
  function savee (line 13) | def savee(ckpt, sr, if_f0, name, epoch, version, hps):
  function show_info (line 51) | def show_info(path):
  function extract_small_model (line 64) | def extract_small_model(path, name, sr, if_f0, info, version):
  function change_info (line 194) | def change_info(path, info, name):
  function merge (line 206) | def merge(path1, path2, alpha1, sr, f0, info, name, version):

FILE: infer/lib/train/utils.py
  function load_checkpoint_d (line 20) | def load_checkpoint_d(checkpoint_path, combd, sbd, optimizer=None, load_...
  function load_checkpoint (line 100) | def load_checkpoint(checkpoint_path, model, optimizer=None, load_opt=1):
  function save_checkpoint (line 144) | def save_checkpoint(model, optimizer, learning_rate, iteration, checkpoi...
  function save_checkpoint_d (line 165) | def save_checkpoint_d(combd, sbd, optimizer, learning_rate, iteration, c...
  function summarize (line 191) | def summarize(
  function latest_checkpoint_path (line 210) | def latest_checkpoint_path(dir_path, regex="G_*.pth"):
  function plot_spectrogram_to_numpy (line 218) | def plot_spectrogram_to_numpy(spectrogram):
  function plot_alignment_to_numpy (line 244) | def plot_alignment_to_numpy(alignment, info=None):
  function load_wav_to_torch (line 275) | def load_wav_to_torch(full_path):
  function load_filepaths_and_text (line 280) | def load_filepaths_and_text(filename, split="|"):
  function get_hparams (line 291) | def get_hparams(init=True):
  function get_hparams_from_dir (line 394) | def get_hparams_from_dir(model_dir):
  function get_hparams_from_file (line 405) | def get_hparams_from_file(config_path):
  function check_git_hash (line 414) | def check_git_hash(model_dir):
  function get_logger (line 439) | def get_logger(model_dir, filename="train.log"):
  class HParams (line 454) | class HParams:
    method __init__ (line 455) | def __init__(self, **kwargs):
    method keys (line 461) | def keys(self):
    method items (line 464) | def items(self):
    method values (line 467) | def values(self):
    method __len__ (line 470) | def __len__(self):
    method __getitem__ (line 473) | def __getitem__(self, key):
    method __setitem__ (line 476) | def __setitem__(self, key, value):
    method __contains__ (line 479) | def __contains__(self, key):
    method __repr__ (line 482) | def __repr__(self):

FILE: infer/lib/uvr5_pack/lib_v5/dataset.py
  class VocalRemoverValidationSet (line 12) | class VocalRemoverValidationSet(torch.utils.data.Dataset):
    method __init__ (line 13) | def __init__(self, patch_list):
    method __len__ (line 16) | def __len__(self):
    method __getitem__ (line 19) | def __getitem__(self, idx):
  function make_pair (line 31) | def make_pair(mix_dir, inst_dir):
  function train_val_split (line 54) | def train_val_split(dataset_dir, split_mode, val_rate, val_filelist):
  function augment (line 90) | def augment(X, y, reduction_rate, reduction_mask, mixup_rate, mixup_alpha):
  function make_padding (line 118) | def make_padding(width, cropsize, offset):
  function make_training_set (line 128) | def make_training_set(filelist, cropsize, patches, sr, hop_length, n_fft...
  function make_validation_set (line 153) | def make_validation_set(filelist, cropsize, sr, hop_length, n_fft, offset):

FILE: infer/lib/uvr5_pack/lib_v5/layers.py
  class Conv2DBNActiv (line 8) | class Conv2DBNActiv(nn.Module):
    method __init__ (line 9) | def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, ac...
    method __call__ (line 25) | def __call__(self, x):
  class SeperableConv2DBNActiv (line 29) | class SeperableConv2DBNActiv(nn.Module):
    method __init__ (line 30) | def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, ac...
    method __call__ (line 48) | def __call__(self, x):
  class Encoder (line 52) | class Encoder(nn.Module):
    method __init__ (line 53) | def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.Leaky...
    method __call__ (line 58) | def __call__(self, x):
  class Decoder (line 65) | class Decoder(nn.Module):
    method __init__ (line 66) | def __init__(
    method __call__ (line 73) | def __call__(self, x, skip=None):
  class ASPPModule (line 86) | class ASPPModule(nn.Module):
    method __init__ (line 87) | def __init__(self, nin, nout, dilations=(4, 8, 16), activ=nn.ReLU):
    method forward (line 107) | def forward(self, x):

FILE: infer/lib/uvr5_pack/lib_v5/layers_123812KB .py
  class Conv2DBNActiv (line 8) | class Conv2DBNActiv(nn.Module):
    method __init__ (line 9) | def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, ac...
    method __call__ (line 25) | def __call__(self, x):
  class SeperableConv2DBNActiv (line 29) | class SeperableConv2DBNActiv(nn.Module):
    method __init__ (line 30) | def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, ac...
    method __call__ (line 48) | def __call__(self, x):
  class Encoder (line 52) | class Encoder(nn.Module):
    method __init__ (line 53) | def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.Leaky...
    method __call__ (line 58) | def __call__(self, x):
  class Decoder (line 65) | class Decoder(nn.Module):
    method __init__ (line 66) | def __init__(
    method __call__ (line 73) | def __call__(self, x, skip=None):
  class ASPPModule (line 86) | class ASPPModule(nn.Module):
    method __init__ (line 87) | def __init__(self, nin, nout, dilations=(4, 8, 16), activ=nn.ReLU):
    method forward (line 107) | def forward(self, x):

FILE: infer/lib/uvr5_pack/lib_v5/layers_123821KB.py
  class Conv2DBNActiv (line 8) | class Conv2DBNActiv(nn.Module):
    method __init__ (line 9) | def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, ac...
    method __call__ (line 25) | def __call__(self, x):
  class SeperableConv2DBNActiv (line 29) | class SeperableConv2DBNActiv(nn.Module):
    method __init__ (line 30) | def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, ac...
    method __call__ (line 48) | def __call__(self, x):
  class Encoder (line 52) | class Encoder(nn.Module):
    method __init__ (line 53) | def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.Leaky...
    method __call__ (line 58) | def __call__(self, x):
  class Decoder (line 65) | class Decoder(nn.Module):
    method __init__ (line 66) | def __init__(
    method __call__ (line 73) | def __call__(self, x, skip=None):
  class ASPPModule (line 86) | class ASPPModule(nn.Module):
    method __init__ (line 87) | def __init__(self, nin, nout, dilations=(4, 8, 16), activ=nn.ReLU):
    method forward (line 107) | def forward(self, x):

FILE: infer/lib/uvr5_pack/lib_v5/layers_33966KB.py
  class Conv2DBNActiv (line 8) | class Conv2DBNActiv(nn.Module):
    method __init__ (line 9) | def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, ac...
    method __call__ (line 25) | def __call__(self, x):
  class SeperableConv2DBNActiv (line 29) | class SeperableConv2DBNActiv(nn.Module):
    method __init__ (line 30) | def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, ac...
    method __call__ (line 48) | def __call__(self, x):
  class Encoder (line 52) | class Encoder(nn.Module):
    method __init__ (line 53) | def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.Leaky...
    method __call__ (line 58) | def __call__(self, x):
  class Decoder (line 65) | class Decoder(nn.Module):
    method __init__ (line 66) | def __init__(
    method __call__ (line 73) | def __call__(self, x, skip=None):
  class ASPPModule (line 86) | class ASPPModule(nn.Module):
    method __init__ (line 87) | def __init__(self, nin, nout, dilations=(4, 8, 16, 32, 64), activ=nn.R...
    method forward (line 113) | def forward(self, x):

FILE: infer/lib/uvr5_pack/lib_v5/layers_537227KB.py
  class Conv2DBNActiv (line 8) | class Conv2DBNActiv(nn.Module):
    method __init__ (line 9) | def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, ac...
    method __call__ (line 25) | def __call__(self, x):
  class SeperableConv2DBNActiv (line 29) | class SeperableConv2DBNActiv(nn.Module):
    method __init__ (line 30) | def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, ac...
    method __call__ (line 48) | def __call__(self, x):
  class Encoder (line 52) | class Encoder(nn.Module):
    method __init__ (line 53) | def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.Leaky...
    method __call__ (line 58) | def __call__(self, x):
  class Decoder (line 65) | class Decoder(nn.Module):
    method __init__ (line 66) | def __init__(
    method __call__ (line 73) | def __call__(self, x, skip=None):
  class ASPPModule (line 86) | class ASPPModule(nn.Module):
    method __init__ (line 87) | def __init__(self, nin, nout, dilations=(4, 8, 16, 32, 64), activ=nn.R...
    method forward (line 113) | def forward(self, x):

FILE: infer/lib/uvr5_pack/lib_v5/layers_537238KB.py
  class Conv2DBNActiv (line 8) | class Conv2DBNActiv(nn.Module):
    method __init__ (line 9) | def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, ac...
    method __call__ (line 25) | def __call__(self, x):
  class SeperableConv2DBNActiv (line 29) | class SeperableConv2DBNActiv(nn.Module):
    method __init__ (line 30) | def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, ac...
    method __call__ (line 48) | def __call__(self, x):
  class Encoder (line 52) | class Encoder(nn.Module):
    method __init__ (line 53) | def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.Leaky...
    method __call__ (line 58) | def __call__(self, x):
  class Decoder (line 65) | class Decoder(nn.Module):
    method __init__ (line 66) | def __init__(
    method __call__ (line 73) | def __call__(self, x, skip=None):
  class ASPPModule (line 86) | class ASPPModule(nn.Module):
    method __init__ (line 87) | def __init__(self, nin, nout, dilations=(4, 8, 16, 32, 64), activ=nn.R...
    method forward (line 113) | def forward(self, x):

FILE: infer/lib/uvr5_pack/lib_v5/layers_new.py
  class Conv2DBNActiv (line 8) | class Conv2DBNActiv(nn.Module):
    method __init__ (line 9) | def __init__(self, nin, nout, ksize=3, stride=1, pad=1, dilation=1, ac...
    method __call__ (line 25) | def __call__(self, x):
  class Encoder (line 29) | class Encoder(nn.Module):
    method __init__ (line 30) | def __init__(self, nin, nout, ksize=3, stride=1, pad=1, activ=nn.Leaky...
    method __call__ (line 35) | def __call__(self, x):
  class Decoder (line 42) | class Decoder(nn.Module):
    method __init__ (line 43) | def __init__(
    method __call__ (line 51) | def __call__(self, x, skip=None):
  class ASPPModule (line 67) | class ASPPModule(nn.Module):
    method __init__ (line 68) | def __init__(self, nin, nout, dilations=(4, 8, 12), activ=nn.ReLU, dro...
    method forward (line 87) | def forward(self, x):
  class LSTMModule (line 105) | class LSTMModule(nn.Module):
    method __init__ (line 106) | def __init__(self, nin_conv, nin_lstm, nout_lstm):
    method forward (line 116) | def forward(self, x):

FILE: infer/lib/uvr5_pack/lib_v5/model_param_init.py
  function int_keys (line 36) | def int_keys(d):
  class ModelParameters (line 45) | class ModelParameters(object):
    method __init__ (line 46) | def __init__(self, config_path=""):

FILE: infer/lib/uvr5_pack/lib_v5/nets.py
  class BaseASPPNet (line 9) | class BaseASPPNet(nn.Module):
    method __init__ (line 10) | def __init__(self, nin, ch, dilations=(4, 8, 16)):
    method __call__ (line 24) | def __call__(self, x):
  class CascadedASPPNet (line 40) | class CascadedASPPNet(nn.Module):
    method __init__ (line 41) | def __init__(self, n_fft):
    method forward (line 61) | def forward(self, x, aggressiveness=None):
    method predict (line 116) | def predict(self, x_mag, aggressiveness=None):

FILE: infer/lib/uvr5_pack/lib_v5/nets_123812KB.py
  class BaseASPPNet (line 8) | class BaseASPPNet(nn.Module):
    method __init__ (line 9) | def __init__(self, nin, ch, dilations=(4, 8, 16)):
    method __call__ (line 23) | def __call__(self, x):
  class CascadedASPPNet (line 39) | class CascadedASPPNet(nn.Module):
    method __init__ (line 40) | def __init__(self, n_fft):
    method forward (line 60) | def forward(self, x, aggressiveness=None):
    method predict (line 115) | def predict(self, x_mag, aggressiveness=None):

FILE: infer/lib/uvr5_pack/lib_v5/nets_123821KB.py
  class BaseASPPNet (line 8) | class BaseASPPNet(nn.Module):
    method __init__ (line 9) | def __init__(self, nin, ch, dilations=(4, 8, 16)):
    method __call__ (line 23) | def __call__(self, x):
  class CascadedASPPNet (line 39) | class CascadedASPPNet(nn.Module):
    method __init__ (line 40) | def __init__(self, n_fft):
    method forward (line 60) | def forward(self, x, aggressiveness=None):
    method predict (line 115) | def predict(self, x_mag, aggressiveness=None):

FILE: infer/lib/uvr5_pack/lib_v5/nets_33966KB.py
  class BaseASPPNet (line 8) | class BaseASPPNet(nn.Module):
    method __init__ (line 9) | def __init__(self, nin, ch, dilations=(4, 8, 16, 32)):
    method __call__ (line 23) | def __call__(self, x):
  class CascadedASPPNet (line 39) | class CascadedASPPNet(nn.Module):
    method __init__ (line 40) | def __init__(self, n_fft):
    method forward (line 60) | def forward(self, x, aggressiveness=None):
    method predict (line 115) | def predict(self, x_mag, aggressiveness=None):

FILE: infer/lib/uvr5_pack/lib_v5/nets_537227KB.py
  class BaseASPPNet (line 9) | class BaseASPPNet(nn.Module):
    method __init__ (line 10) | def __init__(self, nin, ch, dilations=(4, 8, 16)):
    method __call__ (line 24) | def __call__(self, x):
  class CascadedASPPNet (line 40) | class CascadedASPPNet(nn.Module):
    method __init__ (line 41) | def __init__(self, n_fft):
    method forward (line 61) | def forward(self, x, aggressiveness=None):
    method predict (line 116) | def predict(self, x_mag, aggressiveness=None):

FILE: infer/lib/uvr5_pack/lib_v5/nets_537238KB.py
  class BaseASPPNet (line 9) | class BaseASPPNet(nn.Module):
    method __init__ (line 10) | def __init__(self, nin, ch, dilations=(4, 8, 16)):
    method __call__ (line 24) | def __call__(self, x):
  class CascadedASPPNet (line 40) | class CascadedASPPNet(nn.Module):
    method __init__ (line 41) | def __init__(self, n_fft):
    method forward (line 61) | def forward(self, x, aggressiveness=None):
    method predict (line 116) | def predict(self, x_mag, aggressiveness=None):

FILE: infer/lib/uvr5_pack/lib_v5/nets_61968KB.py
  class BaseASPPNet (line 8) | class BaseASPPNet(nn.Module):
    method __init__ (line 9) | def __init__(self, nin, ch, dilations=(4, 8, 16)):
    method __call__ (line 23) | def __call__(self, x):
  class CascadedASPPNet (line 39) | class CascadedASPPNet(nn.Module):
    method __init__ (line 40) | def __init__(self, n_fft):
    method forward (line 60) | def forward(self, x, aggressiveness=None):
    method predict (line 115) | def predict(self, x_mag, aggressiveness=None):

FILE: infer/lib/uvr5_pack/lib_v5/nets_new.py
  class BaseNet (line 8) | class BaseNet(nn.Module):
    method __init__ (line 9) | def __init__(
    method __call__ (line 27) | def __call__(self, x):
  class CascadedNet (line 45) | class CascadedNet(nn.Module):
    method __init__ (line 46) | def __init__(self, n_fft, nout=32, nout_lstm=128):
    method forward (line 78) | def forward(self, x):
    method predict_mask (line 116) | def predict_mask(self, x):
    method predict (line 125) | def predict(self, x, aggressiveness=None):

FILE: infer/lib/uvr5_pack/lib_v5/spec_utils.py
  function crop_center (line 12) | def crop_center(h1, h2):
  function wave_to_spectrogram (line 30) | def wave_to_spectrogram(
  function wave_to_spectrogram_mt (line 54) | def wave_to_spectrogram_mt(
  function combine_spectrograms (line 89) | def combine_spectrograms(specs, mp):
  function spectrogram_to_image (line 127) | def spectrogram_to_image(spec, mode="magnitude"):
  function reduce_vocal_aggressively (line 151) | def reduce_vocal_aggressively(X, y, softmask):
  function mask_silence (line 162) | def mask_silence(mag, ref, thres=0.2, min_range=64, fade_size=32):
  function align_wave_head_and_tail (line 200) | def align_wave_head_and_tail(a, b):
  function cache_or_load (line 206) | def cache_or_load(mix_path, inst_path, mp):
  function spectrogram_to_wave (line 295) | def spectrogram_to_wave(spec, hop_length, mid_side, mid_side_b2, reverse):
  function spectrogram_to_wave_mt (line 319) | def spectrogram_to_wave_mt(spec, hop_length, mid_side, reverse, mid_side...
  function cmb_spectrogram_to_wave (line 353) | def cmb_spectrogram_to_wave(spec_m, mp, extra_bins_h=None, extra_bins=No...
  function fft_lp_filter (line 431) | def fft_lp_filter(spec, bin_start, bin_stop):
  function fft_hp_filter (line 442) | def fft_hp_filter(spec, bin_start, bin_stop):
  function mirroring (line 453) | def mirroring(a, spec_m, input_high_end, mp):
  function ensembling (line 493) | def ensembling(a, specs):
  function stft (line 510) | def stft(wave, nfft, hl):
  function istft (line 520) | def istft(spec, hl):

FILE: infer/lib/uvr5_pack/utils.py
  function load_data (line 8) | def load_data(file_name: str = "./infer/lib/uvr5_pack/name_params.json")...
  function make_padding (line 15) | def make_padding(width, cropsize, offset):
  function inference (line 25) | def inference(X_spec, device, model, aggressiveness, data):
  function _get_name_params (line 102) | def _get_name_params(model_path, model_hash):

FILE: infer/modules/ipex/__init__.py
  function ipex_init (line 12) | def ipex_init():  # pylint: disable=too-many-statements

FILE: infer/modules/ipex/attention.py
  function torch_bmm (line 9) | def torch_bmm(input, mat2, *, out=None):
  function scaled_dot_product_attention (line 84) | def scaled_dot_product_attention(
  function attention_init (line 215) | def attention_init():

FILE: infer/modules/ipex/gradscaler.py
  function _unscale_grads_ (line 15) | def _unscale_grads_(
  function unscale_ (line 66) | def unscale_(self, optimizer):
  function update (line 116) | def update(self, new_scale=None):
  function gradscaler_init (line 182) | def gradscaler_init():

FILE: infer/modules/ipex/hijacks.py
  class CondFunc (line 9) | class CondFunc:  # pylint: disable=missing-class-docstring
    method __new__ (line 10) | def __new__(cls, orig_func, sub_func, cond_func):
    method __init__ (line 31) | def __init__(self, orig_func, sub_func, cond_func):
    method __call__ (line 36) | def __call__(self, *args, **kwargs):
  function _shutdown_workers (line 46) | def _shutdown_workers(self):
  class DummyDataParallel (line 80) | class DummyDataParallel(
    method __new__ (line 83) | def __new__(
  function return_null_context (line 91) | def return_null_context(*args, **kwargs):  # pylint: disable=unused-argu...
  function check_device (line 95) | def check_device(device):
  function return_xpu (line 103) | def return_xpu(device):
  function ipex_no_cuda (line 115) | def ipex_no_cuda(orig_func, *args, **kwargs):
  function ipex_autocast (line 124) | def ipex_autocast(*args, **kwargs):
  function torch_cat (line 134) | def torch_cat(tensor, *args, **kwargs):
  function interpolate (line 150) | def interpolate(
  function linalg_solve (line 186) | def linalg_solve(A, B, *args, **kwargs):  # pylint: disable=invalid-name
  function ipex_hijacks (line 196) | def ipex_hijacks():

FILE: infer/modules/onnx/export.py
  function export_onnx (line 6) | def export_onnx(ModelPath, ExportedPath):

FILE: infer/modules/train/extract/extract_f0_print.py
  function printt (line 23) | def printt(strr):
  class FeatureInput (line 33) | class FeatureInput(object):
    method __init__ (line 34) | def __init__(self, samplerate=16000, hop_size=160):
    method compute_f0 (line 44) | def compute_f0(self, path, f0_method):
    method coarse_f0 (line 95) | def coarse_f0(self, f0):
    method go (line 111) | def go(self, paths, f0_method):

FILE: infer/modules/train/extract/extract_f0_rmvpe.py
  function printt (line 27) | def printt(strr):
  class FeatureInput (line 33) | class FeatureInput(object):
    method __init__ (line 34) | def __init__(self, samplerate=16000, hop_size=160):
    method compute_f0 (line 44) | def compute_f0(self, path, f0_method):
    method coarse_f0 (line 58) | def coarse_f0(self, f0):
    method go (line 74) | def go(self, paths, f0_method):

FILE: infer/modules/train/extract/extract_f0_rmvpe_dml.py
  function printt (line 25) | def printt(strr):
  class FeatureInput (line 31) | class FeatureInput(object):
    method __init__ (line 32) | def __init__(self, samplerate=16000, hop_size=160):
    method compute_f0 (line 42) | def compute_f0(self, path, f0_method):
    method coarse_f0 (line 56) | def coarse_f0(self, f0):
    method go (line 72) | def go(self, paths, f0_method):

FILE: infer/modules/train/extract_feature_print.py
  function forward_dml (line 38) | def forward_dml(ctx, x, scale):
  function printt (line 48) | def printt(strr):
  function readwave (line 66) | def readwave(wav_path, normalize=False):

FILE: infer/modules/train/preprocess.py
  function println (line 29) | def println(strr):
  class PreProcess (line 35) | class PreProcess:
    method __init__ (line 36) | def __init__(self, sr, exp_dir, per=3.7):
    method norm_write (line 59) | def norm_write(self, tmp_audio, idx0, idx1):
    method pipeline (line 81) | def pipeline(self, path, idx0):
    method pipeline_mp (line 107) | def pipeline_mp(self, infos):
    method pipeline_mp_inp_dir (line 111) | def pipeline_mp_inp_dir(self, inp_root, n_p):
  function preprocess_trainset (line 134) | def preprocess_trainset(inp_root, sr, n_p, exp_dir, per):

FILE: infer/modules/train/train.py
  class EpochRecorder (line 82) | class EpochRecorder:
    method __init__ (line 83) | def __init__(self):
    method record (line 86) | def record(self):
  function main (line 95) | def main():
  function run (line 120) | def run(rank, n_gpus, hps, logger: logging.Logger):
  function train_and_evaluate (line 299) | def train_and_evaluate(

FILE: infer/modules/uvr5/mdxnet.py
  class ConvTDFNetTrim (line 15) | class ConvTDFNetTrim:
    method __init__ (line 16) | def __init__(
    method stft (line 41) | def stft(self, x):
    method istft (line 58) | def istft(self, x, freq_pad=None):
  function get_models (line 78) | def get_models(device, dim_f, dim_t, n_fft):
  class Predictor (line 90) | class Predictor:
    method __init__ (line 91) | def __init__(self, args):
    method demix (line 109) | def demix(self, mix):
    method demix_base (line 143) | def demix_base(self, mixes, margin_size):
    method prediction (line 199) | def prediction(self, m, vocal_root, others_root, format):
  class MDXNetDereverb (line 241) | class MDXNetDereverb:
    method __init__ (line 242) | def __init__(self, chunks, device):
    method _path_audio_ (line 255) | def _path_audio_(self, input, vocal_root, others_root, format, is_hp3=...

FILE: infer/modules/uvr5/modules.py
  function uvr (line 17) | def uvr(model_name, inp_root, save_root_vocal, paths, save_root_ins, agg...

FILE: infer/modules/uvr5/vr.py
  class AudioPre (line 18) | class AudioPre:
    method __init__ (line 19) | def __init__(self, agg, model_path, device, is_half, tta=False):
    method _path_audio_ (line 44) | def _path_audio_(
  class AudioPreDeEcho (line 198) | class AudioPreDeEcho:
    method __init__ (line 199) | def __init__(self, agg, model_path, device, is_half, tta=False):
    method _path_audio_ (line 225) | def _path_audio_(

FILE: infer/modules/vc/modules.py
  class VC (line 22) | class VC:
    method __init__ (line 23) | def __init__(self, config):
    method get_vc (line 36) | def get_vc(self, sid, *to_return_protect):
    method vc_single (line 146) | def vc_single(
    method vc_multi (line 227) | def vc_multi(

FILE: infer/modules/vc/pipeline.py
  function cache_harvest_f0 (line 30) | def cache_harvest_f0(input_audio_path, fs, f0max, f0min, frame_period):
  function change_rms (line 43) | def change_rms(data1, sr1, data2, sr2, rate):  # 1是输入音频，2是输出音频,rate是2的占比
  class Pipeline (line 65) | class Pipeline(object):
    method __init__ (line 66) | def __init__(self, tgt_sr, config):
    method get_f0 (line 84) | def get_f0(
    method vc (line 186) | def vc(
    method pipeline (line 281) | def pipeline(

FILE: infer/modules/vc/utils.py
  function get_index_path_from_model (line 6) | def get_index_path_from_model(sid):
  function load_hubert (line 22) | def load_hubert(config):

FILE: tools/calc_rvc_model_similarity.py
  function cal_cross_attn (line 13) | def cal_cross_attn(to_q, to_k, to_v, rand_input):
  function model_hash (line 32) | def model_hash(filename):
  function eval (line 46) | def eval(model, n, input):
  function main (line 56) | def main(path, root):

FILE: tools/download_models.py
  function dl_model (line 10) | def dl_model(link, model_name, dir_name):

FILE: tools/infer/infer-pm-index256.py
  function get_f0 (line 88) | def get_f0(x, p_len, f0_up_key=0):

FILE: tools/infer_batch_rvc.py
  function arg_parse (line 19) | def arg_parse() -> tuple:
  function main (line 41) | def main():

FILE: tools/infer_cli.py
  function arg_parse (line 19) | def arg_parse() -> tuple:
  function main (line 41) | def main():

FILE: tools/rvc_for_realtime.py
  function printt (line 38) | def printt(strr, *args):
  class RVC (line 47) | class RVC:
    method __init__ (line 48) | def __init__(
    method change_key (line 195) | def change_key(self, new_key):
    method change_index_rate (line 198) | def change_index_rate(self, new_index_rate):
    method get_f0_post (line 205) | def get_f0_post(self, f0):
    method get_f0 (line 218) | def get_f0(self, x, f0_up_key, n_cpu, method="harvest"):
    method get_f0_crepe (line 289) | def get_f0_crepe(self, x, f0_up_key):
    method get_f0_rmvpe (line 313) | def get_f0_rmvpe(self, x, f0_up_key):
    method get_f0_fcpe (line 328) | def get_f0_fcpe(self, x, f0_up_key):
    method infer (line 347) | def infer(

FILE: tools/torchgate/torchgate.py
  class TorchGate (line 8) | class TorchGate(torch.nn.Module):
    method __init__ (line 33) | def __init__(
    method _generate_mask_smoothing_filter (line 75) | def _generate_mask_smoothing_filter(self) -> Union[torch.Tensor, None]:
    method _stationary_mask (line 128) | def _stationary_mask(
    method _nonstationary_mask (line 178) | def _nonstationary_mask(self, X_abs: torch.Tensor) -> torch.Tensor:
    method forward (line 210) | def forward(

FILE: tools/torchgate/utils.py
  function amp_to_db (line 6) | def amp_to_db(
  function temperature_sigmoid (line 29) | def temperature_sigmoid(x: torch.Tensor, x0: float, temp_coeff: float) -...
  function linspace (line 45) | def linspace(