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