def testCreateAveragePooling2DChannelsFirst(self):
height, width = 5, 6
images = tf.random.uniform((3, 4, height, width))
layer = pooling_layers.AveragePooling2D((2, 2),
strides=(1, 1),
padding='valid',
data_format='channels_first')
output = layer.apply(images)
self.assertListEqual(output.get_shape().as_list(), [3, 4, 4, 5])
def testCreateAveragePooling2DChannelsFirstWithNoneBatch(self):
height, width = 5, 6
images = tf.compat.v1.placeholder(dtype='float32',
shape=(None, 4, height, width))
layer = pooling_layers.AveragePooling2D((2, 2),
strides=(1, 1),
padding='valid',
data_format='channels_first')
output = layer.apply(images)
self.assertListEqual(output.get_shape().as_list(), [None, 4, 4, 5])
def testCreateAveragePooling2D(self):
height, width = 7, 9
images = tf.random.uniform((5, height, width, 4))
layer = pooling_layers.AveragePooling2D([2, 2], strides=2)
output = layer(images)
self.assertListEqual(output.get_shape().as_list(), [5, 3, 4, 4])
