torch.Tensor() with requires_grad parameter

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I can't use torch.Tensor() with requires_grad parameter (torch version : 0.4.1)

without requires_grad :

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

with requires_grad=True or 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
tensor pytorch python
1 Answers

You are creating the tensor x by using the torch.Tensor class constructor which doesn't take the requires_grad flag. Instead, you want to use torch.tensor() (lowercase 't') method

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

Edit: adding a link to docs: torch.Tensor

user_43131950
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