untimeError: size mismatch, m1: [32 x 512], m2: [1024 x 10] at C:/cb/pytorch_1000000000000/work/ate

Question

コード
```Hi,
I got this error. I tried to fix it but could not do this.

This is my code:

    def forward(self, i):
        print(i.shape)
        c1_mem = c1_spike = torch.zeros(batch_size, 64, 34, 34, device=device)
        c2_mem = c2_spike = torch.zeros(batch_size, 64, 17, 17, device=device)
        c3_mem = c3_spike = torch.zeros(batch_size, 128, 8, 8, device=device)

        h1_mem = h1_spike = h1_sumspike = torch.zeros(batch_size, 1024, device=device)
        # print(h1_mem.shape)
        h2_mem = h2_spike = h2_sumspike = torch.zeros(batch_size, 10, device=device)

        for idx in range(i.shape[-1]):

            x = i[:, :, :, :, idx].cuda()
            #print(x.shape)
            x = x > torch.rand(x.size(), device=device)  # prob. firing
            print(x.shape)

            # print(x.shape)

            c1_mem, c1_spike = mem_update(self.conv1, x.float(), c1_mem, c1_spike)
            # print(c1_mem.shape)

            x = F.avg_pool2d(c1_spike, 2)

            c2_mem, c2_spike = mem_update(self.conv2, x, c2_mem, c2_spike)

            x = F.avg_pool2d(c2_spike, 2)

            c3_mem, c3_spike = mem_update(self.conv3, x, c3_mem, c3_spike)
            print(c3_mem.shape)

            x = F.avg_pool2d(c3_spike, 4)
            print(x.shape)

        **    x = x.view(x.size(0),-1)**
            print(x.shape)

            h1_mem, h1_spike = mem_update(self.fc1, x, h1_mem, h1_spike)
            h1_sumspike += h1_spike
            h2_mem, h2_spike = mem_update(self.fc2, h1_spike, h2_mem, h2_spike)
            h2_sumspike += h2_spike

        outputs = h2_sumspike / i.shape[-1]
        return outputs
Thanks

Comments

[y_waiwai]

しつもんはなんでしょうか

[Tehreem]

Sorry?