def testCreateAveragePooling1DChannelsFirst(self): width = 7 channels = 3 images = tf.random.uniform((5, channels, width)) layer = pooling_layers.AveragePooling1D( 2, strides=2, data_format='channels_first') output = layer.apply(images) self.assertListEqual(output.get_shape().as_list(), [5, channels, width // 2])
def testCreateAveragePooling1D(self): width = 7 channels = 3 images = tf.random.uniform((5, width, channels)) layer = pooling_layers.AveragePooling1D(2, strides=2) output = layer(images) self.assertListEqual( output.get_shape().as_list(), [5, width // 2, channels] )