Can someone explain the src and the src_mask shape of transformer.
For example, I have a tokenized text sentence with max_len=128.
This sentence go through a nn.Embedding(src_vocab=5000, emb_dim=128)
The output of the embedding will be a tensor with shape (N, 128,128), where N=batch_size.
The transformer docs 58 tell that src input and src_mask have shape:
src: (S,N,E) and src_mask: (S,S)
where S is the source sequence length, N is the batch size, E is the feature number.
Should I do some changes on embedding output to use as input on transformer layer?
I’m a bit confused  .