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])