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
andksize=(k, k)
are equivalent. - stride (int or pair of ints or None) – Stride of pooling applications.
stride=s
andstride=(s, s)
are equivalent. IfNone
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
andpad=(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 bychainer.functions.upsampling_2d()
. Note that cuDNN will not be used for this function ifreturn_indices
is set toTrue
, as cuDNN does not return indices information.
Returns: When
return_indices
isFalse
(default), returns the output variable. WhenTrue
, returns the tuple of the output variable and pooling indices (ndarray). Pooling indices will be on the same device as the input.Return type: