我不能使用带有 requires_grad 参数的 torch.Tensor()(torch 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]])
with 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
最佳答案
您正在使用不带 requires_grad
标志的 torch.Tensor
类构造函数创建张量 x
。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:添加文档链接:torch.Tensor
关于python - 带有 requires_grad 参数的 torch.Tensor(),我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/53201921/