I have pytorch Tensor with shape
(batch_size, step, vec_size), for example, a
Tensor(32, 64, 128), let’s call it A.
I have another
Tensor(batch_size, vec_size), e.g.
Tensor(32, 128), let’s call it B.
I want to insert B into a certain position at axis 1 of A. The insert positions are given in a
Tensor(batch_size), named P.
I understand there is no Empty tensor(like an empty list) in pytorch, so, I initialize A as zeros, and add B at a certain position at axis 1 of A.
A = Variable(torch.zeros(batch_size, step, vec_size))
What I’m doing is like:
for i in range(batch_size): pos = P[i] A[i][pos] = A[i][pos] + B[i]
But I get an Error:
RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation
Then, I make a clone of A each inside the loop:
for i in range(batch_size): A_clone = A.clone() pos = P[i] A_clone[i][pos] = A_clone[i][pos] + B[i]
This is very slow for autograd, I wonder if there any better solutions? Thank you.