Pooling
The pooling ops sweep a rectangular window over the input tensor, computing a reduction operation for each window (average, max, or max with argmax). Each pooling op uses rectangular windows of size ksize separated by offset strides. For example, if strides is all ones every window is used, if strides is all twos every other window is used in each dimension, etc.
In detail, the output is
output[i] = reduce(value[strides * i:strides * i + ksize])where the indices also take into consideration the padding values. Please refer to the Convolution section for details about the padding calculation.
有关pooling的函数：
- tf.nn.avg_pool
- tf.nn.max_pool
- tf.nn.max_pool_with_argmax
- tf.nn.avg_pool3d
- tf.nn.max_pool3d
- tf.nn.fractional_avg_pool
- tf.nn.fractional_max_pool
- tf.nn.pool