带有 requires_grad 参数的 torch.Tensor()

Question

我不能使用带有 requires_grad 参数的 torch.Tensor()（火炬版本：0.4.1）

没有 requires_grad ：

x = torch.Tensor([[.5, .3, 2.1]])
print(x)
> tensor([[0.5000, 0.3000, 2.1000]])

使用 requires_grad=True 或 requires_grad=False ：

x = torch.Tensor([[.5, .3, 2.1]], requires_grad=False)
print(x)
Traceback (most recent call last):
  File "D:/_P/dev/ai/pytorch/notes/tensor01.py", line 4, in <module>
    x = torch.Tensor([[.5, .3, 2.1]], requires_grad=False)
TypeError: new() received an invalid combination of arguments - got (list, requires_grad=bool), but expected one of:
 * (torch.device device)
 * (torch.Storage storage)
 * (Tensor other)
 * (tuple of ints size, torch.device device)
      didn't match because some of the keywords were incorrect: requires_grad
 * (object data, torch.device device)
      didn't match because some of the keywords were incorrect: requires_grad

Answer 1

您正在x使用torch.Tensor不带requires_grad标志的类构造函数创建张量。相反，您想使用torch.tensor()(小写 't') 方法

x = torch.tensor([[.5, .3, 2.1]], requires_grad=False)

编辑：添加到文档的链接：torch.Tensor