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]
)