I am receiving the following error:
RuntimeError: Only Tensors of floating point and complex dtype can require gradients.
when i run a convolution operation inside a torch.no_grad()context:
import torch.nn as nn import torch with torch.no_grad(): ker_t = torch.tensor([[1, -1] ,[-1, 1]]) in_t = torch.tensor([ [14, 7, 6, 2,] , [4 ,8 ,11 ,1], [3, 5, 9 ,10], [12, 15, 16, 13] ]) print(in_t.shape) in_t = torch.unsqueeze(in_t,0) in_t = torch.unsqueeze(in_t,0) print(in_t.shape) conv = nn.Conv2d(1, 1, kernel_size=2,stride=2,dtype=torch.long) conv.weight[:] = ker_t conv(in_t)
Now i am sure if i turn my input into floats this message will go away, but i want to work in integers.
But i was under the impression that if i am in a “with torch.no_grad()” context it should turn of the need for gradients.