chainer.functions.average_pooling_nd¶

chainer.functions.average_pooling_nd(x, ksize, stride=None, pad=0)[source]¶

N-dimensionally spatial average pooling function.

This function provides a N-dimensionally generalized version of average_pooling_2d(). This acts similarly to ConvolutionND, but it computes the average of input spatial patch for each channel without any parameter instead of computing the inner products.

Parameters:	x (Variable) – Input variable. ksize (int or tuple of ints) – Size of pooling window. `ksize=k` and `ksize=(k, k, ..., k)` are equivalent. stride (int or tuple of ints or None) – Stride of pooling applications. `stride=s` and `stride=(s, s, ..., s)` are equivalent. If `None` is specified, then it uses same stride as the pooling window size. pad (int or tuple of ints) – Spatial padding width for the input array. `pad=p` and `pad=(p, p, ..., p)` are equivalent.
Returns:	Output variable.
Return type:	Variable

Note

This function currently does not support cover_all mode as max_pooling_nd(). Average pooling runs in non-cover-all mode.