I have a tensor in pytorch with size torch.Size([1443747, 128])
. Let’s name it tensor A
. In this tensor, 128 represents a batch size. I have another 1D tensor with size torch.Size([1443747])
. Let’s call it B
. I want to do element wise multiplication of B with A, such that B is multiplied with all 128 columns of tensor A
(obviously in an element wise manner). In other words, I want to broadcast the element wise multiplication along dimension=1
.
How can I achieve this in pytorch?
It I didn’t have a batch size involved in the tensor A (batch size = 1
), then normal *
operator would do the multiplication easily. A*B
then would have generated resultant tensor of size torch.Size([1443747])
. However, I don’t understand why pytorch is not broadcasting the tensor multiplication along dimension 1? Is there any way to do this?
What I want is, B
should be multiplied with all 128 columns of A
in an element wise manner. So, the resultant tensors’ size would be torch.Size([1443747, 128])
.