SYMBOL INDEX (266 symbols across 27 files)

FILE: datasets/datafeeder_tacotron2.py
  function get_frame (line 22) | def get_frame(path):
  function get_path_dict (line 28) | def get_path_dict(data_dirs, hparams, config,data_type, n_test=None,rng=...
  class DataFeederTacotron2 (line 73) | class DataFeederTacotron2(threading.Thread):
    method __init__ (line 76) | def __init__(self, coordinator, data_dirs,hparams, config, batches_per...
    method start_in_session (line 180) | def start_in_session(self, session, start_step):
    method run (line 186) | def run(self):
    method _enqueue_next_group (line 195) | def _enqueue_next_group(self):
    method _get_next_example (line 229) | def _get_next_example(self, data_dir):
  function _prepare_batch (line 276) | def _prepare_batch(batch, reduction_factor, rng, data_type=None):
  function _prepare_inputs (line 298) | def _prepare_inputs(inputs):  # inputs: batch 길이 만큼의 list
  function _prepare_targets (line 307) | def _prepare_targets(targets, alignment):
  function _prepare_stop_token_targets (line 312) | def _prepare_stop_token_targets(targets, alignment):
  function _pad_input (line 317) | def _pad_input(x, length):
  function _pad_target (line 321) | def _pad_target(t, length):
  function _pad_stop_token_target (line 326) | def _pad_stop_token_target(t, length):
  function _round_up (line 329) | def _round_up(x, multiple):

FILE: datasets/datafeeder_wavenet.py
  function get_path_dict (line 16) | def get_path_dict(data_dirs, min_length):
  function assert_ready_for_upsampling (line 38) | def assert_ready_for_upsampling(x, c,hop_size):
  function ensure_divisible (line 41) | def ensure_divisible(length, divisible_by=256, lower=True):
  class DataFeederWavenet (line 50) | class DataFeederWavenet(threading.Thread):
    method __init__ (line 51) | def __init__(self,coord,data_dirs,batch_size, gc_enable=False,test_mod...
    method run (line 96) | def run(self):
    method start_in_session (line 102) | def start_in_session(self, session,start_step):
    method make_batches (line 107) | def make_batches(self):
    method _get_next_example (line 122) | def _get_next_example(self, data_dir):
  function _prepare_batch (line 163) | def _prepare_batch(batch):

FILE: datasets/moon.py
  function build_from_path (line 11) | def build_from_path(hparams, in_dir, out_dir, num_workers=1, tqdm=lambda...
  function _process_utterance (line 52) | def _process_utterance(out_dir, wav_path, text, hparams):

FILE: datasets/son.py
  function build_from_path (line 11) | def build_from_path(hparams, in_dir, out_dir, num_workers=1, tqdm=lambda...
  function _process_utterance (line 47) | def _process_utterance(out_dir, wav_path, text, hparams):

FILE: generate.py
  function _interp (line 37) | def _interp(feats, in_range):
  function get_arguments (line 42) | def get_arguments():
  function create_seed (line 92) | def create_seed(filename,sample_rate,quantization_channels,window_size,s...
  function main (line 110) | def main():

FILE: hparams.py
  function hparams_debug_string (line 233) | def hparams_debug_string():

FILE: preprocess.py
  function preprocess (line 19) | def preprocess(mod, in_dir, out_root,num_workers):
  function write_metadata (line 25) | def write_metadata(metadata, out_dir):

FILE: synthesizer.py
  class Synthesizer (line 39) | class Synthesizer(object):
    method close (line 40) | def close(self):
    method load (line 44) | def load(self, checkpoint_path, num_speakers=2, checkpoint_step=None, ...
    method synthesize (line 83) | def synthesize(self,
  function plot_graph_and_save_audio (line 161) | def plot_graph_and_save_audio(args,
  function get_most_recent_checkpoint (line 246) | def get_most_recent_checkpoint(checkpoint_dir, checkpoint_step=None):
  function short_concat (line 258) | def short_concat(

FILE: tacotron2/__init__.py
  function create_model (line 7) | def create_model(hparams):
  function get_most_recent_checkpoint (line 11) | def get_most_recent_checkpoint(checkpoint_dir):

FILE: tacotron2/helpers.py
  class TacoTestHelper (line 10) | class TacoTestHelper(Helper):
    method __init__ (line 11) | def __init__(self, batch_size, output_dim, r):
    method batch_size (line 18) | def batch_size(self):
    method sample_ids_dtype (line 22) | def sample_ids_dtype(self):
    method sample_ids_shape (line 26) | def sample_ids_shape(self):
    method initialize (line 29) | def initialize(self, name=None):
    method sample (line 32) | def sample(self, time, outputs, state, name=None):
    method next_inputs (line 35) | def next_inputs(self, time, outputs, state, sample_ids, name=None):
  class TacoTrainingHelper (line 46) | class TacoTrainingHelper(Helper):
    method __init__ (line 47) | def __init__(self, targets, output_dim, r):
    method batch_size (line 63) | def batch_size(self):
    method sample_ids_dtype (line 67) | def sample_ids_dtype(self):
    method sample_ids_shape (line 71) | def sample_ids_shape(self):
    method initialize (line 75) | def initialize(self, name=None):
    method sample (line 78) | def sample(self, time, outputs, state, name=None):
    method next_inputs (line 81) | def next_inputs(self, time, outputs, state, sample_ids, name=None):  #...
  function _go_frames (line 90) | def _go_frames(batch_size, output_dim):

FILE: tacotron2/modules.py
  function prenet (line 10) | def prenet(inputs, is_training, layer_sizes, drop_prob, scope=None):
  function cbhg (line 21) | def cbhg(inputs, input_lengths, is_training, bank_size, bank_channel_siz...
  function batch_tile (line 73) | def batch_tile(tensor, batch_size):
  function highwaynet (line 79) | def highwaynet(inputs, scope):
  function conv1d (line 88) | def conv1d(inputs, kernel_size, channels, activation, is_training, scope):

FILE: tacotron2/rnn_wrappers.py
  class ZoneoutLSTMCell (line 17) | class ZoneoutLSTMCell(RNNCell):
    method __init__ (line 27) | def __init__(self, num_units, is_training, zoneout_factor_cell=0., zon...
    method state_size (line 43) | def state_size(self):
    method output_size (line 47) | def output_size(self):
    method __call__ (line 50) | def __call__(self, inputs, state, scope=None):
  class DecoderWrapper (line 80) | class DecoderWrapper(RNNCell):
    method __init__ (line 83) | def __init__(self, cell, is_training, prenet_sizes, dropout_prob,infer...
    method state_size (line 96) | def state_size(self):
    method output_size (line 100) | def output_size(self):
    method call (line 103) | def call(self, inputs, state):
    method zero_state (line 110) | def zero_state(self, batch_size, dtype):
  class LocationSensitiveAttention (line 115) | class LocationSensitiveAttention(BahdanauAttention):
    method __init__ (line 131) | def __init__(self,
    method __call__ (line 188) | def __call__(self, query, state):
  function _location_sensitive_score (line 248) | def _location_sensitive_score(W_query, W_fil, W_keys):
  function _smoothing_normalization (line 283) | def _smoothing_normalization(e):
  class GmmAttention (line 304) | class GmmAttention(AttentionMechanism):
    method __init__ (line 305) | def __init__(self,
    method values (line 332) | def values(self):
    method batch_size (line 336) | def batch_size(self):
    method alignments_size (line 340) | def alignments_size(self):
    method state_size (line 344) | def state_size(self):
    method initial_alignments (line 347) | def initial_alignments(self, batch_size, dtype):
    method initial_state (line 351) | def initial_state(self, batch_size, dtype):
    method __call__ (line 355) | def __call__(self, query, state):

FILE: tacotron2/tacotron2.py
  class Tacotron2 (line 31) | class Tacotron2():
    method __init__ (line 32) | def __init__(self, hparams):
    method initialize (line 36) | def initialize(self, inputs, input_lengths, num_speakers, speaker_id=N...
    method add_loss (line 234) | def add_loss(self):
    method add_optimizer (line 272) | def add_optimizer(self, global_step):
    method _learning_rate_decay (line 302) | def _learning_rate_decay(self, init_lr, global_step):

FILE: text/__init__.py
  function convert_to_en_symbols (line 24) | def convert_to_en_symbols():
  function remove_puncuations (line 35) | def remove_puncuations(text):
  function text_to_sequence (line 38) | def text_to_sequence(text, as_token=False):
  function _text_to_sequence (line 44) | def _text_to_sequence(text, cleaner_names, as_token):
  function sequence_to_text (line 78) | def sequence_to_text(sequence, skip_eos_and_pad=False, combine_jamo=False):
  function _clean_text (line 104) | def _clean_text(text, cleaner_names):
  function _symbols_to_sequence (line 114) | def _symbols_to_sequence(symbols):
  function _arpabet_to_sequence (line 118) | def _arpabet_to_sequence(text):
  function _should_keep_symbol (line 122) | def _should_keep_symbol(s):

FILE: text/cleaners.py
  function korean_cleaners (line 27) | def korean_cleaners(text):
  function expand_abbreviations (line 56) | def expand_abbreviations(text):
  function expand_numbers (line 62) | def expand_numbers(text):
  function lowercase (line 66) | def lowercase(text):
  function collapse_whitespace (line 70) | def collapse_whitespace(text):
  function convert_to_ascii (line 73) | def convert_to_ascii(text):
  function basic_cleaners (line 78) | def basic_cleaners(text):
  function transliteration_cleaners (line 85) | def transliteration_cleaners(text):
  function english_cleaners (line 93) | def english_cleaners(text):

FILE: text/en_numbers.py
  function _remove_commas (line 14) | def _remove_commas(m):
  function _expand_decimal_point (line 18) | def _expand_decimal_point(m):
  function _expand_dollars (line 22) | def _expand_dollars(m):
  function _expand_ordinal (line 43) | def _expand_ordinal(m):
  function _expand_number (line 47) | def _expand_number(m):
  function normalize_numbers (line 62) | def normalize_numbers(text):

FILE: text/english.py
  function _remove_commas (line 14) | def _remove_commas(m):
  function _expand_decimal_point (line 18) | def _expand_decimal_point(m):
  function _expand_dollars (line 22) | def _expand_dollars(m):
  function _expand_ordinal (line 43) | def _expand_ordinal(m):
  function _expand_number (line 47) | def _expand_number(m):
  function normalize (line 62) | def normalize(text):

FILE: text/korean.py
  function is_lead (line 29) | def is_lead(char):
  function is_vowel (line 32) | def is_vowel(char):
  function is_tail (line 35) | def is_tail(char):
  function get_mode (line 38) | def get_mode(char):
  function _get_text_from_candidates (line 48) | def _get_text_from_candidates(candidates):
  function jamo_to_korean (line 56) | def jamo_to_korean(text):
  function compare_sentence_with_jamo (line 137) | def compare_sentence_with_jamo(text1, text2):
  function tokenize (line 140) | def tokenize(text, as_id=False):
  function tokenizer_fn (line 150) | def tokenizer_fn(iterator):
  function normalize (line 153) | def normalize(text):
  function normalize_with_dictionary (line 168) | def normalize_with_dictionary(text, dic):
  function normalize_english (line 175) | def normalize_english(text):
  function normalize_upper (line 186) | def normalize_upper(text):
  function normalize_quote (line 194) | def normalize_quote(text):
  function normalize_number (line 209) | def normalize_number(text):
  function number_to_korean (line 239) | def number_to_korean(num_str, is_count=False):
  function test_normalize (line 311) | def test_normalize(text):

FILE: train_tacotron2.py
  function get_git_commit (line 32) | def get_git_commit():
  function add_stats (line 39) | def add_stats(model, model2=None, scope_name='train'):
  function save_and_plot_fn (line 69) | def save_and_plot_fn(args, log_dir, step, loss, prefix):
  function save_and_plot (line 86) | def save_and_plot(sequences, spectrograms,alignments, log_dir, step, los...
  function train (line 95) | def train(log_dir, config):
  function main (line 239) | def main():

FILE: train_vocoder.py
  function eval_step (line 28) | def eval_step(sess,logdir,step,waveform,upsampled_local_condition_data,s...
  function create_network (line 94) | def create_network(hp,batch_size,num_speakers,is_training):
  function main (line 116) | def main():

FILE: utils/__init__.py
  class ValueWindow (line 17) | class ValueWindow():
    method __init__ (line 18) | def __init__(self, window_size=100):
    method append (line 22) | def append(self, x):
    method sum (line 26) | def sum(self):
    method count (line 30) | def count(self):
    method average (line 34) | def average(self):
    method reset (line 37) | def reset(self):
  function prepare_dirs (line 39) | def prepare_dirs(config, hparams):
  function save (line 62) | def save(saver, sess, logdir, step):
  function load (line 75) | def load(saver, sess, logdir):
  function get_default_logdir (line 93) | def get_default_logdir(logdir_root):
  function validate_directories (line 100) | def validate_directories(args,hparams):
  function save_hparams (line 143) | def save_hparams(model_dir, hparams):
  function write_json (line 152) | def write_json(path, data):
  function load_hparams (line 156) | def load_hparams(hparams, load_path, skip_list=[]):
  function load_json (line 173) | def load_json(path, as_class=False, encoding='euc-kr'):
  function get_most_recent_checkpoint (line 186) | def get_most_recent_checkpoint(checkpoint_dir):
  function add_prefix (line 197) | def add_prefix(path, prefix):
  function add_postfix (line 201) | def add_postfix(path, postfix):
  function remove_postfix (line 205) | def remove_postfix(path):
  function get_time (line 209) | def get_time():
  function parallel_run (line 212) | def parallel_run(fn, items, desc="", parallel=True):
  function makedirs (line 227) | def makedirs(path):
  function str2bool (line 232) | def str2bool(v):
  function remove_file (line 235) | def remove_file(path):
  function get_git_revision_hash (line 240) | def get_git_revision_hash():
  function get_git_diff (line 242) | def get_git_diff():
  function warning (line 245) | def warning(msg):
  function get_tensors_in_checkpoint_file (line 251) | def get_tensors_in_checkpoint_file(file_name,all_tensors=True,tensor_nam...
  function build_tensors_in_checkpoint_file (line 269) | def build_tensors_in_checkpoint_file(loaded_tensors):

FILE: utils/audio.py
  function load_wav (line 11) | def load_wav(path, sr):
  function save_wav (line 14) | def save_wav(wav, path, sr):
  function save_wavenet_wav (line 19) | def save_wavenet_wav(wav, path, sr):
  function preemphasis (line 22) | def preemphasis(wav, k, preemphasize=True):
  function inv_preemphasis (line 27) | def inv_preemphasis(wav, k, inv_preemphasize=True):
  function start_and_end_indices (line 33) | def start_and_end_indices(quantized, silence_threshold=2):
  function trim_silence (line 46) | def trim_silence(wav, hparams):
  function get_hop_size (line 54) | def get_hop_size(hparams):
  function linearspectrogram (line 61) | def linearspectrogram(wav, hparams):
  function melspectrogram (line 69) | def melspectrogram(wav, hparams):
  function inv_linear_spectrogram (line 77) | def inv_linear_spectrogram(linear_spectrogram, hparams):
  function inv_mel_spectrogram (line 95) | def inv_mel_spectrogram(mel_spectrogram, hparams):
  function inv_spectrogram_tensorflow (line 112) | def inv_spectrogram_tensorflow(spectrogram,hparams):
  function inv_spectrogram (line 117) | def inv_spectrogram(spectrogram,hparams):
  function _lws_processor (line 123) | def _lws_processor(hparams):
  function _griffin_lim (line 127) | def _griffin_lim(S, hparams):
  function _stft (line 139) | def _stft(y, hparams):
  function _istft (line 145) | def _istft(y, hparams):
  function num_frames (line 150) | def num_frames(length, fsize, fshift):
  function pad_lr (line 161) | def pad_lr(x, fsize, fshift):
  function librosa_pad_lr (line 171) | def librosa_pad_lr(x, fsize, fshift):
  function _linear_to_mel (line 181) | def _linear_to_mel(spectogram, hparams):
  function _mel_to_linear (line 187) | def _mel_to_linear(mel_spectrogram, hparams):
  function _build_mel_basis (line 193) | def _build_mel_basis(hparams):
  function _amp_to_db (line 201) | def _amp_to_db(x, hparams):
  function _db_to_amp (line 205) | def _db_to_amp(x):
  function _normalize (line 208) | def _normalize(S, hparams):
  function _denormalize (line 222) | def _denormalize(D, hparams):
  function mulaw (line 244) | def mulaw(x, mu=256):
  function inv_mulaw (line 265) | def inv_mulaw(y, mu=256):
  function mulaw_quantize (line 283) | def mulaw_quantize(x, mu=256):
  function inv_mulaw_quantize (line 317) | def inv_mulaw_quantize(y, mu=256):
  function _sign (line 343) | def _sign(x):
  function _log1p (line 350) | def _log1p(x):
  function _abs (line 357) | def _abs(x):
  function _asint (line 364) | def _asint(x):
  function _asfloat (line 371) | def _asfloat(x):
  function frames_to_hours (line 377) | def frames_to_hours(n_frames,hparams):
  function get_duration (line 380) | def get_duration(audio,hparams):
  function _db_to_amp_tensorflow (line 383) | def _db_to_amp_tensorflow(x):
  function _denormalize_tensorflow (line 386) | def _denormalize_tensorflow(S,hparams):
  function _griffin_lim_tensorflow (line 389) | def _griffin_lim_tensorflow(S,hparams):
  function _istft_tensorflow (line 400) | def _istft_tensorflow(stfts,hparams):
  function _stft_tensorflow (line 404) | def _stft_tensorflow(signals,hparams):
  function _stft_parameters (line 408) | def _stft_parameters(hparams):

FILE: utils/infolog.py
  function init (line 14) | def init(filename, run_name, slack_url=None):
  function log (line 25) | def log(msg, slack=False):
  function _close_logfile (line 33) | def _close_logfile():
  function _send_slack (line 40) | def _send_slack(msg):

FILE: utils/plot.py
  function plot (line 25) | def plot(alignment, info, text, isKorean=True):
  function plot_alignment (line 64) | def plot_alignment(
  function plot_spectrogram (line 79) | def plot_spectrogram(pred_spectrogram, path, title=None, split_title=Fal...

FILE: wavenet/mixture.py
  function log_sum_exp (line 12) | def log_sum_exp(x):
  function log_prob_from_logits (line 20) | def log_prob_from_logits(x):
  function discretized_mix_logistic_loss (line 27) | def discretized_mix_logistic_loss(y_hat, y, num_class=256, log_scale_min...
  function sample_from_discretized_mix_logistic (line 84) | def sample_from_discretized_mix_logistic(y, log_scale_min=float(np.log(1...

FILE: wavenet/model.py
  class WaveNetModel (line 7) | class WaveNetModel(object):
    method __init__ (line 8) | def __init__(self,batch_size,dilations,filter_width,residual_channels,...
    method calculate_receptive_field (line 35) | def calculate_receptive_field(filter_width, dilations):
    method _create_causal_layer (line 40) | def _create_causal_layer(self, input_batch):
    method _create_queue (line 49) | def _create_queue(self):
    method _create_dilation_layer (line 60) | def _create_dilation_layer(self, input_batch, layer_index, dilation,lo...
    method create_upsample (line 123) | def create_upsample(self, local_condition_batch,upsample_type='SubPixe...
    method _create_network (line 147) | def _create_network(self, input_batch,local_condition_batch, global_co...
    method _one_hot (line 192) | def _one_hot(self, input_batch):
    method _embed_gc (line 204) | def _embed_gc(self, global_condition):  # global_condition = global_co...
    method predict_proba_incremental (line 238) | def predict_proba_incremental(self, waveform,upsampled_local_condition...
    method add_loss (line 270) | def add_loss(self, input_batch,local_condition=None, global_condition_...
    method add_optimizer (line 338) | def add_optimizer(self, hparams,global_step):

FILE: wavenet/ops.py
  function create_adam_optimizer (line 4) | def create_adam_optimizer(learning_rate, momentum):
  function create_sgd_optimizer (line 9) | def create_sgd_optimizer(learning_rate, momentum):
  function create_rmsprop_optimizer (line 14) | def create_rmsprop_optimizer(learning_rate, momentum):
  function mu_law_encode (line 23) | def mu_law_encode(audio, quantization_channels):
  function mu_law_decode (line 37) | def mu_law_decode(output, quantization_channels, quantization=True):
  class SubPixelConvolution (line 51) | class SubPixelConvolution(tf.layers.Conv2D):
    method __init__ (line 57) | def __init__(self, filters, kernel_size, padding, strides, NN_init, NN...
    method build (line 82) | def build(self, input_shape):
    method call (line 108) | def call(self, inputs):
    method PS (line 116) | def PS(self, inputs):
    method _phase_shift (line 138) | def _phase_shift(self, inputs, batch_size, H, W, r1, r2):
    method _init_kernel (line 154) | def _init_kernel(self, kernel_size, strides, filters):