예제 #1
0
def get_loss(inputs, outputs, params):
  """Computes the rotator loss."""
  g_loss = tf.zeros(dtype=tf.float32, shape=[])

  if hasattr(params, 'image_weight'):
    g_loss += losses.add_rotator_image_loss(inputs, outputs, params.step_size,
                                            params.image_weight)

  if hasattr(params, 'mask_weight'):
    g_loss += losses.add_rotator_mask_loss(inputs, outputs, params.step_size,
                                           params.mask_weight)

  slim.summaries.add_scalar_summary(
      g_loss, 'rotator_loss', prefix='losses')

  return g_loss
예제 #2
0
def get_loss(inputs, outputs, params):
  """Computes the rotator loss."""
  g_loss = tf.zeros(dtype=tf.float32, shape=[])

  if hasattr(params, 'image_weight'):
    g_loss += losses.add_rotator_image_loss(inputs, outputs, params.step_size,
                                            params.image_weight)

  if hasattr(params, 'mask_weight'):
    g_loss += losses.add_rotator_mask_loss(inputs, outputs, params.step_size,
                                           params.mask_weight)

  slim.summaries.add_scalar_summary(
      g_loss, 'rotator_loss', prefix='losses')

  return g_loss