def test_block_number_dictates_number_of_layers(self): batch_size = 2 height, width = 256, 256 num_outputs = 4 images = tf.ones((batch_size, height, width, 3)) blocks = [ pix2pix.Block(64, 0.5), pix2pix.Block(128, 0), ] with tf.contrib.framework.arg_scope(pix2pix.pix2pix_arg_scope()): _, end_points = pix2pix.pix2pix_generator(images, num_outputs, blocks) num_encoder_layers = 0 num_decoder_layers = 0 for end_point in end_points: if end_point.startswith('encoder'): num_encoder_layers += 1 elif end_point.startswith('decoder'): num_decoder_layers += 1 self.assertEqual(num_encoder_layers, len(blocks)) self.assertEqual(num_decoder_layers, len(blocks))
def _reduced_default_blocks(self): """Returns the default blocks, scaled down to make test run faster.""" return [ pix2pix.Block(b.num_filters // 32, b.decoder_keep_prob) for b in pix2pix._default_generator_blocks() ]