Thanks for your reply!!
I’m a bit confusing with this embedding layer output. I’ll try explain:
My sentences have size: torch.size([128]).
So, if I’m using a batch size of 32 the tensor will have size:
torch.size([32,128]) - > shape = (N, S)
When I send this tensor to the embedding layer (with src_vocab = 5000 and emb_dim=128) the output will have size:
torch.tensor([32, 128, 128]) -> shape = (N, S, E).
This is confusing me, should I permute first and second dimensions to become shape = (S, N, E) ?