In my PyTorch program, I have a matrix which is continuously updated over runtime.
I wonder how to perform this update. I tried using something like this:
matrix[0, index] = hidden[0]
Both matrix
and hidden
are autograd Variables. When using the example above I'm getting the following error message:
RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation
I wonder how to get around this and perform the update without using in-place operations.
Probably slicing the matrix and creating a new matrix with torch.cat would work, but this doesn't seem to be a very nice solution.
Is there a better way doing this?
Thanks in advance!
Maybe posting a piece of code could help, but have you tried using a dataset ? You could sequentially run through data efficiently with it.
http://pytorch.org/docs/master/data.html#torch.utils.data.TensorDataset
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