def test_four_layers_negative_padding(self):
batch_size = 2
input_size = 256
images = tf.ones((batch_size, input_size, input_size, 3))
with tf.contrib.framework.arg_scope(pix2pix.pix2pix_arg_scope()):
with self.assertRaises(ValueError):
pix2pix.pix2pix_discriminator(
images, num_filters=[64, 128, 256, 512], padding=-1)
def test_four_layers_negative_padding(self):
batch_size = 2
input_size = 256
images = tf.ones((batch_size, input_size, input_size, 3))
with tf.contrib.framework.arg_scope(pix2pix.pix2pix_arg_scope()):
with self.assertRaises(ValueError):
pix2pix.pix2pix_discriminator(
images, num_filters=[64, 128, 256, 512], padding=-1)
def test_four_layers_wrog_paddig(self):
batch_size = 2
input_size = 256
images = tf.ones((batch_size, input_size, input_size, 3))
with contrib_framework.arg_scope(pix2pix.pix2pix_arg_scope()):
with self.assertRaises(TypeError):
pix2pix.pix2pix_discriminator(images,
num_filters=[64, 128, 256, 512],
padding=1.5)
def test_four_layers_no_padding(self):
batch_size = 2
input_size = 256
output_size = self._layer_output_size(input_size, pad=0)
output_size = self._layer_output_size(output_size, pad=0)
output_size = self._layer_output_size(output_size, pad=0)
output_size = self._layer_output_size(output_size, stride=1, pad=0)
output_size = self._layer_output_size(output_size, stride=1, pad=0)
images = tf.ones((batch_size, input_size, input_size, 3))
with tf.contrib.framework.arg_scope(pix2pix.pix2pix_arg_scope()):
logits, end_points = pix2pix.pix2pix_discriminator(
images, num_filters=[64, 128, 256, 512], padding=0)
self.assertListEqual([batch_size, output_size, output_size, 1],
logits.shape.as_list())
self.assertListEqual([batch_size, output_size, output_size, 1],
end_points['predictions'].shape.as_list())
def test_four_layers(self):
batch_size = 2
input_size = 256
output_size = self._layer_output_size(input_size)
output_size = self._layer_output_size(output_size)
output_size = self._layer_output_size(output_size)
output_size = self._layer_output_size(output_size, stride=1)
output_size = self._layer_output_size(output_size, stride=1)
images = tf.ones((batch_size, input_size, input_size, 3))
with tf.contrib.framework.arg_scope(pix2pix.pix2pix_arg_scope()):
logits, end_points = pix2pix.pix2pix_discriminator(
images, num_filters=[64, 128, 256, 512])
self.assertListEqual([batch_size, output_size, output_size, 1],
logits.shape.as_list())
self.assertListEqual([batch_size, output_size, output_size, 1],
end_points['predictions'].shape.as_list())
def test_four_layers(self):
batch_size = 2
input_size = 256
output_size = self._layer_output_size(input_size)
output_size = self._layer_output_size(output_size)
output_size = self._layer_output_size(output_size)
output_size = self._layer_output_size(output_size, stride=1)
output_size = self._layer_output_size(output_size, stride=1)
images = tf.ones((batch_size, input_size, input_size, 3))
with slim.arg_scope(pix2pix.pix2pix_arg_scope()):
logits, end_points = pix2pix.pix2pix_discriminator(
images, num_filters=[64, 128, 256, 512])
self.assertListEqual([batch_size, output_size, output_size, 1],
logits.shape.as_list())
self.assertListEqual([batch_size, output_size, output_size, 1],
end_points['predictions'].shape.as_list())
