select(dim, index)
:第一个参数为索引的维度,第二个参数为索引的维度的序列号
import torch
a = torch.rand((3, 4))
print(a)
>>> tensor([[0.8664, 0.9759, 0.3063, 0.0686],
[0.6778, 0.0574, 0.3194, 0.4253],
[0.5045, 0.8318, 0.1745, 0.3150]])
print(a.select(dim=1, index=1))
>>> tensor([0.9759, 0.0574, 0.8318])
使用copy_赋值修改张量
import torch
a = torch.rand((3, 4)
print(a)
>>> tensor([[0.6115, 0.2551, 0.8714, 0.3236],
[0.3369, 0.4372, 0.2083, 0.4733],
[0.0046, 0.0981, 0.9148, 0.7852]])
y = torch.tensor([3, 2, 1])
a.select(1, 1).copy_(y.data)
print(a)
>>> tensor([[0.6115, 3.0000, 0.8714, 0.3236],
[0.3369, 2.0000, 0.2083, 0.4733],
[0.0046, 1.0000, 0.9148, 0.7852]])
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