NLP_nn.functional.max_pool1d备忘

a = torch.randn(2, 2, 3)

a

tensor([[[ 0.3279,  0.7291,  0.6789],
         [ 0.4092, -0.0571,  0.5786]],

        [[ 0.0901,  0.1008,  1.4097],
         [-1.7903, -0.9582,  1.8200]]])

max_pool1d( input,  kernel_size ),   kernel_size: 滑动窗口大小

b = nn.functional.max_pool1d(a, a.size(2))

b.shape # torch.Size([2, 2, 1])

b

tensor([[[0.7291],
         [0.5786]],

        [[1.4097],
         [1.8200]]])