SYMBOL INDEX (90 symbols across 7 files)

FILE: convert.py
  function sp2wav (line 22) | def sp2wav(sp):
  function get_world_param (line 28) | def get_world_param(f_h5, src_speaker, utt_id, tar_speaker, tar_speaker_...
  function synthesis (line 49) | def synthesis(f0, sp, ap, sr=16000):
  function convert_sp (line 58) | def convert_sp(sp, c, solver, gen=True):
  function convert_mc (line 66) | def convert_mc(mc, c, solver, gen=True):
  function get_model (line 74) | def get_model(hps_path='./hps/vctk.json', model_path='/storage/model/voi...
  function convert_all_sp (line 82) | def convert_all_sp(h5_path, src_speaker, tar_speaker, gen=True,
  function convert_all_mc (line 100) | def convert_all_mc(h5_path, src_speaker, tar_speaker, gen=False,

FILE: model.py
  function pad_layer (line 7) | def pad_layer(inp, layer, is_2d=False):
  function pixel_shuffle_1d (line 29) | def pixel_shuffle_1d(inp, upscale_factor=2):
  function upsample (line 39) | def upsample(x, scale_factor=2):
  function RNN (line 43) | def RNN(inp, layer):
  function linear (line 52) | def linear(inp, layer):
  function append_emb (line 63) | def append_emb(emb, expand_size, output):
  class PatchDiscriminator (line 69) | class PatchDiscriminator(nn.Module):
    method __init__ (line 70) | def __init__(self, n_class=33, ns=0.2, dp=0.1):
    method conv_block (line 95) | def conv_block(self, x, conv_layer, after_layers):
    method forward (line 102) | def forward(self, x, classify=False):
  class SpeakerClassifier (line 122) | class SpeakerClassifier(nn.Module):
    method __init__ (line 123) | def __init__(self, c_in=512, c_h=512, n_class=8, dp=0.1, ns=0.01):
    method conv_block (line 144) | def conv_block(self, x, conv_layers, after_layers, res=True):
    method forward (line 155) | def forward(self, x):
  class Decoder (line 164) | class Decoder(nn.Module):
    method __init__ (line 165) | def __init__(self, c_in=512, c_out=513, c_h=512, c_a=8, emb_size=128, ...
    method conv_block (line 194) | def conv_block(self, x, conv_layers, norm_layer, emb, res=True):
    method dense_block (line 210) | def dense_block(self, x, emb, layers, norm_layer, res=True):
    method forward (line 221) | def forward(self, x, c):
  class Encoder (line 241) | class Encoder(nn.Module):
    method __init__ (line 242) | def __init__(self, c_in=513, c_h1=128, c_h2=512, c_h3=128, ns=0.2, dp=...
    method conv_block (line 276) | def conv_block(self, x, conv_layers, norm_layers, res=True):
    method dense_block (line 289) | def dense_block(self, x, layers, norm_layers, res=True):
    method forward (line 300) | def forward(self, x):

FILE: preprocess/make_dataset_vctk.py
  function read_speaker_info (line 11) | def read_speaker_info(path='/storage/datasets/VCTK/VCTK-Corpus/speaker-i...

FILE: preprocess/make_single_samples.py
  class Sampler (line 8) | class Sampler(object):
    method __init__ (line 9) | def __init__(self, h5_path, dset, seg_len, used_speaker_path):
    method get_utt_len (line 22) | def get_utt_len(self):
    method rm_too_short_utt (line 31) | def rm_too_short_utt(self, limit):
    method read_speakers (line 36) | def read_speakers(self, path):
    method sample_utt (line 41) | def sample_utt(self, speaker_id, n_samples=1):
    method rand (line 48) | def rand(self, l):
    method sample_single (line 52) | def sample_single(self):

FILE: preprocess/tacotron/norm_utils.py
  class hyperparams (line 20) | class hyperparams(object):
    method __init__ (line 21) | def __init__(self):
  function get_spectrograms (line 40) | def get_spectrograms(fpath):
  function spectrogram2wav (line 103) | def spectrogram2wav(mag):
  function griffin_lim (line 126) | def griffin_lim(spectrogram):
  function invert_spectrogram (line 141) | def invert_spectrogram(spectrogram):
  function plot_alignment (line 148) | def plot_alignment(alignment, gs):
  function learning_rate_decay (line 161) | def learning_rate_decay(init_lr, global_step, warmup_steps=4000.):
  function load_spectrograms (line 166) | def load_spectrograms(fpath):

FILE: solver.py
  class Solver (line 24) | class Solver(object):
    method __init__ (line 25) | def __init__(self, hps, data_loader, log_dir='./log/'):
    method build_model (line 33) | def build_model(self):
    method save_model (line 49) | def save_model(self, model_path, iteration, enc_only=True):
    method load_model (line 73) | def load_model(self, model_path, enc_only=True):
    method set_eval (line 84) | def set_eval(self):
    method test_step (line 91) | def test_step(self, x, c, gen=False):
    method permute_data (line 100) | def permute_data(self, data):
    method sample_c (line 105) | def sample_c(self, size):
    method encode_step (line 113) | def encode_step(self, x):
    method decode_step (line 117) | def decode_step(self, enc, c):
    method patch_step (line 121) | def patch_step(self, x, x_tilde, is_dis=True):
    method gen_step (line 131) | def gen_step(self, enc, c):
    method clf_step (line 135) | def clf_step(self, enc):
    method cal_loss (line 139) | def cal_loss(self, logits, y_true):
    method train (line 145) | def train(self, model_path, flag='train', mode='train'):

FILE: utils.py
  function cc (line 17) | def cc(net):
  function gen_noise (line 23) | def gen_noise(x_dim, y_dim):
  function to_var (line 28) | def to_var(x, requires_grad=True):
  function reset_grad (line 32) | def reset_grad(net_list):
  function grad_clip (line 36) | def grad_clip(net_list, max_grad_norm):
  function calculate_gradients_penalty (line 40) | def calculate_gradients_penalty(netD, real_data, fake_data):
  function cal_acc (line 61) | def cal_acc(logits, y_true):
  class Hps (line 66) | class Hps(object):
    method __init__ (line 67) | def __init__(self):
    method get_tuple (line 97) | def get_tuple(self):
    method load (line 100) | def load(self, path):
    method dump (line 105) | def dump(self, path):
  class DataLoader (line 109) | class DataLoader(object):
    method __init__ (line 110) | def __init__(self, dataset, batch_size=16):
    method all (line 116) | def all(self, size=1000):
    method __iter__ (line 127) | def __iter__(self):
    method __next__ (line 130) | def __next__(self):
  class SingleDataset (line 141) | class SingleDataset(data.Dataset):
    method __init__ (line 142) | def __init__(self, h5_path, index_path, dset='train', seg_len=128):
    method __getitem__ (line 150) | def __getitem__(self, i):
    method __len__ (line 159) | def __len__(self):
  class Logger (line 162) | class Logger(object):
    method __init__ (line 163) | def __init__(self, log_dir='./log'):
    method scalar_summary (line 166) | def scalar_summary(self, tag, value, step):