(inputs, **kwargs)
return fake_images, end_points
Builds generator network.
Builds generator network.
Builds generator network .
def generator_fn_specgram(inputs, **kwargs):
  """Builds generator network."""
  # inputs = (noises, one_hot_labels)
  with tf.variable_scope('generator_cond'):
    z = tf.concat(inputs, axis=1)
  if kwargs['to_rgb_activation'] == 'tanh':
    to_rgb_activation = tf.tanh
  elif kwargs['to_rgb_activation'] == 'linear':
    to_rgb_activation = lambda x: x
  fake_images, end_points = networks.generator(
      z,
      kwargs['progress'],
      lambda block_id: _num_filters_fn(block_id, **kwargs),  # pylint:disable=unnecessary-lambda
      kwargs['resolution_schedule'],
      num_blocks=kwargs['num_blocks'],
      kernel_size=kwargs['kernel_size'],
      colors=2,
      to_rgb_activation=to_rgb_activation,
      simple_arch=kwargs['simple_arch'])
  shape = fake_images.shape
  normalizer = data_normalizer.registry[kwargs['data_normalizer']](kwargs)
  fake_images = normalizer.denormalize_op(fake_images)
  fake_images.set_shape(shape)
  return fake_images, end_points
def generator_fn_specgram ( inputs , * * kwargs ) : # inputs = (noises, one_hot_labels) with tf . variable_scope ( 'generator_cond' ) : z = tf . concat ( inputs , axis = 1 ) if kwargs [ 'to_rgb_activation' ] == 'tanh' : to_rgb_activation = tf . tanh elif kwargs [ 'to_rgb_activation' ] == 'linear' : to_rgb_activation = lambda x : x fake_images , end_points = networks . generator ( z , kwargs [ 'progress' ] , lambda block_id : _num_filters_fn ( block_id , * * kwargs ) , # pylint:disable=unnecessary-lambda kwargs [ 'resolution_schedule' ] , num_blocks = kwargs [ 'num_blocks' ] , kernel_size = kwargs [ 'kernel_size' ] , colors = 2 , to_rgb_activation = to_rgb_activation , simple_arch = kwargs [ 'simple_arch' ] ) shape = fake_images . shape normalizer = data_normalizer . registry [ kwargs [ 'data_normalizer' ] ] ( kwargs ) fake_images = normalizer . denormalize_op ( fake_images ) fake_images . set_shape ( shape ) return fake_images , end_points