作用：在None的位置上增加一个维度.

一行Tensor

import torch
x = torch.randint(4,(1, 4))
print(x)
a = x[None, :, :]
print(f'a.shape: {a.shape}')
b = x[:, None, :2]
print(b)
print(f'b.shape: {b.shape}')
c = x[:, None, 2:]
print(c)
print(f'c.shape: {c.shape}')
>>>
tensor([[0, 3, 2, 1]])
a.shape: torch.Size([1, 1, 4])
tensor([[[0, 3]]])
b.shape: torch.Size([1, 1, 2])
tensor([[[2, 1]]])
c.shape: torch.Size([1, 1, 2])

二维矩阵

import torch
x = torch.arange(12).reshape(3, 4)
print(x)
a = x[None, :, :]
print(f'a.shape: {a.shape}')
b = x[:, None, :2]
print(b)
print(f'b.shape: {b.shape}')
>>>
tensor([[ 0,  1,  2,  3],[ 4,  5,  6,  7],[ 8,  9, 10, 11]])
a.shape: torch.Size([1, 3, 4])
tensor([[[0, 1]],[[4, 5]],[[8, 9]]])
b.shape: torch.Size([3, 1, 2])