# chainer.functions.unpooling_nd¶

chainer.functions.unpooling_nd(x, ksize, stride=None, pad=0, outsize=None, cover_all=True)[source]

Inverse operation of N-dimensional spatial pooling.

Warning

This feature is experimental. The interface can change in the future.

This function acts similarly to DeconvolutionND, but it spreads input N-dimensional array’s value without any parameter instead of computing the inner products.

Parameters
• x (Variable) – Input variable.

• ksize (int or pair of ints) – Size of pooling window $$(k_1, k_2, ..., k_N)$$. ksize=k is equivalent to (k, k, ..., k).

• stride (int, pair of ints or None) – Stride of pooling applications $$(s_1, s_2, ..., s_N)$$. stride=s is equivalent to (s, s, ..., s). 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 $$(p_1, p_2, ..., p_N)$$. pad=p is equivalent to (p, p, ..., p).

• outsize (None or pair of ints) – Expected output size of unpooling operation $$(out_1, out_2, ..., out_N)$$. If None, the size is estimated from input size, stride and padding.

• cover_all (bool) – If True, the pooling window is assumed to cover all of the output array, eventually the output size may be smaller than that in the case cover_all is False.

Returns

Output variable.

Return type

Variable