chainer.functions.max_pooling_2d¶

chainer.functions.max_pooling_2d(x, ksize, stride=None, pad=0, cover_all=True, return_indices=False)[source]¶

Spatial max pooling function.

This function acts similarly to Convolution2D, but it computes the maximum of input spatial patch for each channel without any parameter instead of computing the inner products.

Parameters:	x (Variable) – Input variable. ksize (int or pair of ints) – Size of pooling window. `ksize=k` and `ksize=(k, k)` are equivalent. stride (int or pair of ints or None) – Stride of pooling applications. `stride=s` and `stride=(s, s)` are equivalent. If `None` is specified, then it uses same stride as the pooling window size. pad (int or pair of ints) – Spatial padding width for the input array. `pad=p` and `pad=(p, p)` are equivalent. cover_all (bool) – If `True`, all spatial locations are pooled into some output pixels. It may make the output size larger. return_indices (bool) – If `True`, pooling indices array is returned together with the output variable. The returned indices are expected for use by `chainer.functions.upsampling_2d()`. Note that cuDNN will not be used for this function if `return_indices` is set to `True`, as cuDNN does not return indices information.
Returns:	When `return_indices` is `False` (default), returns the output variable. When `True`, returns the tuple of the output variable and pooling indices (ndarray). Pooling indices will be on the same device as the input.
Return type:	Variable or tuple