Python torch uint8张量索引

我正在try 按in_inds对Signal_Matrix进行切片，但我想uint8索引是不同的.有人能解释一下它是如何工作的吗？

signal_matrix = torch.tensor(
                       [[0, 0, 1, 1],
                        [0, 0, 0, 0],
                        [0, 0, 1, 1],
                        [0, 1, 1, 0],
                        [1, 0, 1, 0],
                        [0, 0, 0, 0],
                        [0, 0, 0, 0],
                        [0, 0, 0, 0],
                        [0, 0, 0, 0]], dtype=torch.uint8)

in_inds = torch.tensor(
         [[ 0,  2,  3],                     
          [ 1,  2,  4],
          [ 0,  0,  0]][::-1], dtype= torch.uint8
          )

out_inds = torch.tensor(
         [ 5, 6, 7], dtype= torch.uint8)

op_inds = torch.tensor(
        [ [1, 1, 1, 1],                    
          [0, 0, 0, 0],
          [2, 2, 2, 2]], dtype= torch.uint8)

in_signals = signal_matrix[in_inds]

IndexError: The shape of the mask [3, 3] at index 0 does not match the shape of the indexed tensor [9, 4] at index 0个

总的来说，我预计会是这样的.同样的结果也适用于int32.

tensor([[[0, 0, 1, 1],
         [0, 0, 1, 1],
         [0, 0, 1, 1]],

        [[0, 0, 0, 0],
         [0, 0, 1, 1],
         [1, 0, 1, 0]],

        [[0, 0, 1, 1],
         [0, 0, 1, 1],
         [0, 1, 1, 0]]], dtype=torch.int32)