Tensor Copy Issue

[woodsboy]

I have a question with Tensor copy, what I want is allocate the memory for a tensor outside a loop, and fill the data inner loop, but if I use c[batchId, :, :] = t3.t(), this seems a in plane operation(not differentiable), but if I use c[batchId, :, :].data = t3.().clone(), c is not change after the loop.

is there anyone could help me with the issue? thank you!

[yunusemre]

[resolved] How does one create copy of tensors in PyTorch?

I was trying to create new copies (so that python was pointing at different objects and not just updating the same copy across multiple namespaces). I tried it by getting the actual numpy data from a tensor and using that to create a brand new tensor but that didn’t work. Why did it not work? How does one do this? >>> y 3 3 3 3 3 3 [torch.FloatTensor of size 3x2] >>> yv.data = torch.FloatTensor( y.numpy() ) >>> yv Variable containing: 3 3 3 3 3 3 [torch.FloatTensor of size 3x2] >>…

I think you should check this.