如何在PyTorch中将张量大小从[a, b]转换为[a, b, k]

Question

我想给张量增加一个额外的维度，并将这个维度的值设置为一个特定的值。为例子,

print(a.size)
torch.Size([10, 5])

# after tranformation and set a to b
print(b.size)
torch.Size([10, 5, 1])

# after transformation and set a to c
print(c.size)
torch.Size([10, 2, 5])

提前感谢。

Answer 1

torch.stack允许您沿着新的维度连接两个数组

value = 1.37
a = torch.normal(0, 1, size=(5, 10))
c = torch.stack([a, torch.ones(a.shape) * value], dim=1)
c.shape
Out: torch.Size([5, 2, 10])

c[:, 0, :]
Out: tensor([[-0.2944, -0.7366,  0.6882, -0.7106,  0.0182, -0.1156, -1.0394, -0.7524,
0.7587, -0.6066],
[-1.0445, -2.7990,  0.0232,  0.5246, -0.7383,  0.0306, -1.0277, -0.8969,
0.4026,  0.2006],
[-1.2622, -0.6563, -1.9218, -0.6932, -1.9633,  1.8271,  0.6753, -0.7564,
0.0107, -0.2312],
[-0.8111, -1.0776, -0.8583,  0.2782, -0.8116,  0.0984,  0.4799,  0.6854,
0.4408, -0.4280],
[-1.1083,  1.8509,  0.1209,  0.5571, -1.1472,  0.2342,  0.3912,  0.7858,
0.5879,  0.4139]])
c[:, 1, :]
Out: tensor([[1.3700, 1.3700, 1.3700, 1.3700, 1.3700, 1.3700, 1.3700, 1.3700, 1.3700,
1.3700],
[1.3700, 1.3700, 1.3700, 1.3700, 1.3700, 1.3700, 1.3700, 1.3700, 1.3700,
1.3700],
[1.3700, 1.3700, 1.3700, 1.3700, 1.3700, 1.3700, 1.3700, 1.3700, 1.3700,
1.3700],
[1.3700, 1.3700, 1.3700, 1.3700, 1.3700, 1.3700, 1.3700, 1.3700, 1.3700,
1.3700],
[1.3700, 1.3700, 1.3700, 1.3700, 1.3700, 1.3700, 1.3700, 1.3700, 1.3700,
1.3700]])

Answer 2

第一部分问题可以通过unsqueeze来解决

a.shape
>>>torch.Size([10, 5])
a.unsqueeze(2).shape
>>>torch.Size([10, 5, 1]))

您也可以使用a.unsqueeze(-1)在最后一个维度上添加维度，但最好使用2，正如Python的禅意:显式优于隐式。