【pytorch】torch.roll的简单理解

【pytorch】torch.roll的简单理解 官方解释及示例

>>> x = torch.tensor([1, 2, 3, 4, 5, 6, 7, 8]).view(4, 2)
>>> x
tensor([[1, 2],
        [3, 4],
        [5, 6],
        [7, 8]])
>>> torch.roll(x, 1, 0)
tensor([[7, 8],
        [1, 2],
        [3, 4],
        [5, 6]])
>>> torch.roll(x, -1, 0)
tensor([[3, 4],
        [5, 6],
        [7, 8],
        [1, 2]])
>>> torch.roll(x, shifts=(2, 1), dims=(0, 1))
tensor([[6, 5],
        [8, 7],
        [2, 1],
        [4, 3]])

自己理解及示例

x = torch.tensor([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]).view(4, 4)
print(x)
>>>tensor([[ 1,  2,  3,  4],
           [ 5,  6,  7,  8],
           [ 9, 10, 11, 12],
           [13, 14, 15, 16]])

# dims=0, 滚动行；dims=1, 滚动列。shifts>0, 向上或向左滚动；shifts<0, 向下或向右滚动。
y = torch.roll(x, shifts=(2, 2), dims=(0, 1))   
print(y)     
>>>tensor([[11, 12,  9, 10],
           [15, 16, 13, 14],
           [ 3,  4,  1,  2],
           [ 7,  8,  5,  6]])
过程详解：
（1）dims=(0, 1), shifts=(2, 2)， 表示向上滚动行2次，向左滚动列2次。
（2）向上滚动行2次：
tensor([[ 1,  2,  3,  4],          tensor([[ 9, 10, 11, 12],      
        [ 5,  6,  7,  8],                  [13, 14, 15, 16],
        [ 9, 10, 11, 12],       --->       [ 1,  2,  3,  4],
        [13, 14, 15, 16]])                 [ 5,  6,  7,  8]])  
（3）向左滚动列2次：
 tensor([[ 9, 10, 11, 12],         tensor([[11, 12,  9, 10],
         [13, 14, 15, 16],                 [15, 16, 13, 14],
         [ 1,  2,  3,  4],     --->        [ 3,  4,  1,  2],
         [ 5,  6,  7,  8]])                [ 7,  8,  5,  6]])


# roll reverse，变回原样
z = torch.roll(y, shifts=(-2, -2), dims=(0, 1))
print(z)
>>>tensor([[ 1,  2,  3,  4],
           [ 5,  6,  7,  8],
           [ 9, 10, 11, 12],
           [13, 14, 15, 16]])