()
return (dataset_blob, train_data, train_label, train_mu, train_sigma,
          index_grouped_by_label)
Load WaveGAN's dataset.

  The loaded dataset consists of:
    - original data (dataset_blob, train_data, train_label),
    - encoded data from a pretrained model (train_mu, train_sigma), and
    - index grouped by label (index_grouped_by_label).

  Some of these attributes are not avaiable (set as None) but are left here
  to keep everything aligned with returned value of `load_dataset`.

  Returns:
    An tuple of abovementioned components in the dataset.
Load WaveGAN's dataset.
Load WaveGAN s dataset .
def load_dataset_wavegan():
  """Load WaveGAN's dataset.

  The loaded dataset consists of:
    - original data (dataset_blob, train_data, train_label),
    - encoded data from a pretrained model (train_mu, train_sigma), and
    - index grouped by label (index_grouped_by_label).

  Some of these attributes are not avaiable (set as None) but are left here
  to keep everything aligned with returned value of `load_dataset`.

  Returns:
    An tuple of abovementioned components in the dataset.
  """

  latent_dir = os.path.expanduser(FLAGS.wavegan_latent_dir)
  path_train = os.path.join(latent_dir, 'data_train.npz')
  train = np.load(path_train)
  train_z = train['z']
  train_label = train['label']
  index_grouped_by_label = common.get_index_grouped_by_label(train_label)

  dataset_blob, train_data = None, None
  train_mu, train_sigma = train_z, None
  return (dataset_blob, train_data, train_label, train_mu, train_sigma,
          index_grouped_by_label)
def load_dataset_wavegan ( ) : latent_dir = os . path . expanduser ( FLAGS . wavegan_latent_dir ) path_train = os . path . join ( latent_dir , 'data_train.npz' ) train = np . load ( path_train ) train_z = train [ 'z' ] train_label = train [ 'label' ] index_grouped_by_label = common . get_index_grouped_by_label ( train_label ) dataset_blob , train_data = None , None train_mu , train_sigma = train_z , None return ( dataset_blob , train_data , train_label , train_mu , train_sigma , index_grouped_by_label )