Pytorch里面的X.view(-1)操作
import torch
a = torch.randn(3,5,2)
print(a)
print(a.view(-1))运行结果：
tensor([[[-0.6887, 0.2203],
[-1.6103, -0.7423],
[ 0.3097, -2.9694],
[ 1.2073, -0.3370],
[-0.5506, 0.4753]],
[[-1.3605, 1.9303],
[-1.5382, -1.0865],
[-0.9208, -0.1754],
[ 0.1476, -0.8866],
[ 0.4519, 0.2771]],
[[ 0.6662, 1.1027],
[-0.0912, -0.6284],
[-1.0253, -0.3542],
[ 0.6909, -1.3905],
[-2.1140, 1.3426]]])
tensor([-0.6887, 0.2203, -1.6103, -0.7423, 0.3097, -2.9694, 1.2073, -0.3370,
-0.5506, 0.4753, -1.3605, 1.9303, -1.5382, -1.0865, -0.9208, -0.1754,
0.1476, -0.8866, 0.4519, 0.2771, 0.6662, 1.1027, -0.0912, -0.6284,
-1.0253, -0.3542, 0.6909, -1.3905, -2.1140, 1.3426])
结论
X.view(-1)中的-1本意是根据另外一个数来自动调整维度，但是这里只有一个维度，因此就会将X里面的所有维度数据转化成一维的，并且按先后顺序排列。
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原文链接：https://blog.csdn.net/qq_38929105/article/details/106438045