Pytorch tensor to numpy array

Solution 1:

I believe you also have to use .detach(). I had to convert my Tensor to a numpy array on Colab which uses CUDA and GPU. I did it like the following:

# this is just my embedding matrix which is a Torch tensor object
embedding = learn.model.u_weight

embedding_list = list(range(0, 64382))

input = torch.cuda.LongTensor(embedding_list)
tensor_array = embedding(input)
# the output of the line below is a numpy array
tensor_array.cpu().detach().numpy()

Solution 2:

This worked for me:

np_arr = torch_tensor.cpu().detach().numpy()

Solution 3:

There are 4 dimensions of the tensor you want to convert.

[:, ::-1, :, :] 

: means that the first dimension should be copied as it is and converted, same goes for the third and fourth dimension.

::-1 means that for the second axes it reverses the the axes