def get_generators(batch_size, data_dir, desired_sample_rate, fragment_length, fragment_stride, learn_all_outputs,
nb_output_bins, use_ulaw, test_factor, data_dir_structure, randomize_batch_order, _rnd, random_train_batches):
if data_dir_structure == 'flat':
return dataset.generators(data_dir, desired_sample_rate, fragment_length, batch_size,
fragment_stride, nb_output_bins, learn_all_outputs, use_ulaw, randomize_batch_order,
_rnd, random_train_batches)
elif data_dir_structure == 'vctk':
return dataset.generators_vctk(data_dir, desired_sample_rate, fragment_length, batch_size,
fragment_stride, nb_output_bins, learn_all_outputs, use_ulaw, test_factor,
randomize_batch_order, _rnd, random_train_batches)
else:
raise ValueError('data_dir_structure must be "flat" or "vctk", is %s' % data_dir_structure)
def get_generators(batch_size, data_dir, desired_sample_rate, fragment_length, fragment_stride, learn_all_outputs,
nb_output_bins, use_ulaw, test_factor, data_dir_structure, randomize_batch_order, _rnd,
random_train_batches):
if data_dir_structure == 'flat':
return dataset.generators(data_dir, desired_sample_rate, fragment_length, batch_size,
fragment_stride, nb_output_bins, learn_all_outputs, use_ulaw, randomize_batch_order,
_rnd, random_train_batches)
elif data_dir_structure == 'vctk':
return dataset.generators_vctk(data_dir, desired_sample_rate, fragment_length, batch_size,
fragment_stride, nb_output_bins, learn_all_outputs, use_ulaw, test_factor,
randomize_batch_order, _rnd, random_train_batches)
else:
raise ValueError('data_dir_structure must be "flat" or "vctk", is %s' % data_dir_structure)