1 tf.nn.max_pool(
2 value,
3 ksize,
4 strides,
5 padding,
6 data_format='NHWC',
7 name=None
8 )
Pooling is similar to convolution, The reason is that pooling is similar to subsampling
1 tf.layers.max_pooling2d(
2 inputs,
3 pool_size,
4 strides,
5 padding='valid',
6 data_format='channels_last',
7 name=None
8 )