def testMaxPooling2DPaddingSame(self):
height, width = 7, 9
images = random_ops.random_uniform((5, height, width, 4), seed=1)
layer = pooling_layers.MaxPooling2D(
images.get_shape()[1:3], strides=2, padding='same')
output = layer.apply(images)
self.assertListEqual(output.get_shape().as_list(), [5, 4, 5, 4])
def testCreateMaxPooling2DChannelsFirst(self):
height, width = 7, 9
images = random_ops.random_uniform((5, 2, height, width))
layer = pooling_layers.MaxPooling2D([2, 2],
strides=1,
data_format='channels_first')
output = layer.apply(images)
self.assertListEqual(output.get_shape().as_list(), [5, 2, 6, 8])
def testCreatePooling2DWithStrides(self):
height, width = 6, 8
# Test strides tuple
images = random_ops.random_uniform((5, height, width, 3), seed=1)
layer = pooling_layers.MaxPooling2D([2, 2], strides=(2, 2), padding='same')
output = layer.apply(images)
self.assertListEqual(output.get_shape().as_list(),
[5, height / 2, width / 2, 3])
# Test strides integer
layer = pooling_layers.MaxPooling2D([2, 2], strides=2, padding='same')
output = layer.apply(images)
self.assertListEqual(output.get_shape().as_list(),
[5, height / 2, width / 2, 3])
# Test unequal strides
layer = pooling_layers.MaxPooling2D([2, 2], strides=(2, 1), padding='same')
output = layer.apply(images)
self.assertListEqual(output.get_shape().as_list(),
[5, height / 2, width, 3])
def testCreateMaxPooling2D(self): height, width = 7, 9 images = random_ops.random_uniform((5, height, width, 4)) layer = pooling_layers.MaxPooling2D([2, 2], strides=2) output = layer.apply(images) self.assertListEqual(output.get_shape().as_list(), [5, 3, 4, 4])