Pytorch maxpooling over channels dimension

Question

I was trying to build a cnn to with Pytorch, and had difficulty in maxpooling. I have taken the cs231n held by Stanford. As I recalled, maxpooling can be used as a dimension

Answer 1

Would something like this work?

from torch.nn import MaxPool1D
import torch.nn.functional as F

class ChannelPool(MaxPool1D):
    def forward(self, input):
        n, c, w, h = input.size()
        input = input.view(n,c,w*h).permute(0,2,1)
        pooled =  F.max_pool1d(input, self.kernel_size, self.stride,
                        self.padding, self.dilation, self.ceil_mode,
                        self.return_indices)
        _, _, c = pooled.size()
        pooled = pooled.permute(0,2,1)
        return pooled.view(n,c,w,h)