SYMBOL INDEX (104 symbols across 15 files)

FILE: sing/ae/models.py
  class ConvolutionalDecoder (line 14) | class ConvolutionalDecoder(nn.Module):
    method __init__ (line 37) | def __init__(self,
    method __repr__ (line 79) | def __repr__(self):
    method forward (line 82) | def forward(self, embeddings):
    method wav_length (line 85) | def wav_length(self, embedding_length):
    method embedding_length (line 93) | def embedding_length(self, wav_length):
  class ConvolutionalEncoder (line 102) | class ConvolutionalEncoder(nn.Module):
    method __init__ (line 122) | def __init__(self,
    method __repr__ (line 153) | def __repr__(self):
    method forward (line 156) | def forward(self, signal):
  class ConvolutionalAE (line 160) | class ConvolutionalAE(nn.Module):
    method __init__ (line 182) | def __init__(self,
    method encode (line 212) | def encode(self, signal):
    method decode (line 218) | def decode(self, embeddings):
    method forward (line 224) | def forward(self, signal):
    method __repr__ (line 227) | def __repr__(self):

FILE: sing/ae/trainer.py
  class AutoencoderTrainer (line 12) | class AutoencoderTrainer(trainer.BaseTrainer):
    method _train_batch (line 17) | def _train_batch(self, batch):
    method _get_rebuilt_target (line 25) | def _get_rebuilt_target(self, batch):

FILE: sing/ae/utils.py
  class WindowedConv1d (line 15) | class WindowedConv1d(nn.Module):
    method __init__ (line 26) | def __init__(self, conv, window_name='hann', squared=True):
    method forward (line 38) | def forward(self, input):
    method __repr__ (line 49) | def __repr__(self):
  class WindowedConvTranpose1d (line 54) | class WindowedConvTranpose1d(nn.Module):
    method __init__ (line 65) | def __init__(self, conv_tr, window_name='hann', squared=True):
    method forward (line 77) | def forward(self, input):
    method __repr__ (line 89) | def __repr__(self):

FILE: sing/dsp.py
  function power (line 14) | def power(spec):
  function get_window (line 25) | def get_window(name, window_length, squared=False):
  class STFT (line 46) | class STFT(nn.Module):
    method __init__ (line 60) | def __init__(self, n_fft=1024, hop_length=None, window_name='hann'):
    method forward (line 70) | def forward(self, input):
  class SpectralLoss (line 79) | class SpectralLoss(nn.Module):
    method __init__ (line 90) | def __init__(self, base_loss=F.mse_loss, epsilon=1, **kwargs):
    method _log_spectrogram (line 96) | def _log_spectrogram(self, signal):
    method forward (line 99) | def forward(self, a, b):
  function float_wav_to_short (line 105) | def float_wav_to_short(wav):

FILE: sing/fondation/batch.py
  class BatchItem (line 12) | class BatchItem:
    method __init__ (line 28) | def __init__(self, metadata=None, tensors=None):
  function collate (line 33) | def collate(items):
  class Batch (line 51) | class Batch:
    method __init__ (line 67) | def __init__(self, metadata, tensors):
    method __len__ (line 71) | def __len__(self):
    method __iter__ (line 74) | def __iter__(self):
    method __getitem__ (line 78) | def __getitem__(self, index):
    method apply (line 96) | def apply(self, function):
    method apply_ (line 112) | def apply_(self, function):
    method cuda (line 120) | def cuda(self, *args, **kwargs):
    method cuda_ (line 126) | def cuda_(self, *args, **kwargs):
    method cpu (line 132) | def cpu(self, *args, **kwargs):
    method cpu_ (line 138) | def cpu_(self, *args, **kwargs):

FILE: sing/fondation/datasets.py
  class DatasetSubset (line 16) | class DatasetSubset:
    method __init__ (line 25) | def __init__(self, dataset, indexes):
    method __len__ (line 29) | def __len__(self):
    method __getitem__ (line 32) | def __getitem__(self, index):
  class RandomSubset (line 36) | class RandomSubset(DatasetSubset):
    method __init__ (line 46) | def __init__(self, dataset, size, random_seed=42):

FILE: sing/fondation/trainer.py
  class BaseTrainer (line 19) | class BaseTrainer:
    method __init__ (line 46) | def __init__(self,
    method _train_epoch (line 85) | def _train_epoch(self, dataset, epoch):
    method _eval_dataset (line 111) | def _eval_dataset(self, dataset_name, dataset, epoch):
    method _train_batch (line 135) | def _train_batch(self, batch):
    method _get_rebuilt_target (line 152) | def _get_rebuilt_target(self, batch):
    method train (line 160) | def train(self):

FILE: sing/fondation/utils.py
  function random_seed_manager (line 21) | def random_seed_manager(seed):
  function progress_iterator (line 34) | def progress_iterator(iterator, divisions=100):
  function unpad1d (line 63) | def unpad1d(tensor, pad):
  function load_checkpoint (line 77) | def load_checkpoint(path):
  function save_checkpoint (line 89) | def save_checkpoint(path, epoch, state):
  function download_file (line 108) | def download_file(target, url, sha256=None):
  function fatal (line 141) | def fatal(message, error_code=1):

FILE: sing/generate.py
  function get_parser (line 26) | def get_parser():
  function main (line 69) | def main():

FILE: sing/nsynth/__init__.py
  class NSynthMetadata (line 24) | class NSynthMetadata:
    method _map_velocity (line 49) | def _map_velocity(self, metadata):
    method __init__ (line 60) | def __init__(self, path):
    method __len__ (line 89) | def __len__(self):
    method __getitem__ (line 92) | def __getitem__(self, index):
  class NSynthDataset (line 107) | class NSynthDataset:
    method __init__ (line 125) | def __init__(self, path, pad=0):
    method __len__ (line 129) | def __len__(self):
    method __getitem__ (line 132) | def __getitem__(self, index):
  function make_datasets (line 147) | def make_datasets(dataset, valid_ratio=0.1, test_ratio=0.1, random_seed=...
  function get_metadata_path (line 188) | def get_metadata_path():
  function get_nsynth_metadata (line 195) | def get_nsynth_metadata():

FILE: sing/parser.py
  function get_parser (line 13) | def get_parser():

FILE: sing/sequence/models.py
  class SequenceGenerator (line 15) | class SequenceGenerator(nn.Module):
    method __init__ (line 35) | def __init__(self,
    method forward (line 67) | def forward(self, start=0, length=None, hidden=None, **tensors):
  class SING (line 108) | class SING(nn.Module):
    method __init__ (line 119) | def __init__(self, sequence_generator, decoder):
    method forward (line 124) | def forward(self, **tensors):
  function download_pretrained_model (line 135) | def download_pretrained_model(target):

FILE: sing/sequence/trainer.py
  class SequenceGeneratorTrainer (line 14) | class SequenceGeneratorTrainer(trainer.BaseTrainer):
    method __init__ (line 26) | def __init__(self, decoder, truncated_gradient=32, **kwargs):
    method _train_batch (line 35) | def _train_batch(self, batch):
    method _get_rebuilt_target (line 65) | def _get_rebuilt_target(self, batch):
  class SINGTrainer (line 73) | class SINGTrainer(trainer.BaseTrainer):
    method _get_rebuilt_target (line 78) | def _get_rebuilt_target(self, batch):

FILE: sing/sequence/utils.py
  function generate_embeddings_dataset (line 17) | def generate_embeddings_dataset(dataset, encoder, batch_size, cuda, para...

FILE: sing/train.py
  function train_autoencoder (line 24) | def train_autoencoder(args, **kwargs):
  function train_sequence_generator (line 50) | def train_sequence_generator(args, autoencoder, cardinalities, train_dat...
  function fine_tune_sing (line 97) | def fine_tune_sing(args, sequence_generator, decoder, **kwargs):
  function main (line 113) | def main():