sequence length, N is the batch size, E is the feature number
  -[ Examples ]-

  >>> output = transformer_model(src, tgt, src_mask=src_mask, tgt_mask=tgt_mask)

static generate_square_subsequent_mask(sz, device='cpu')
  Generate a square mask for the sequence. The masked positions
  are filled with float('-inf'). Unmasked positions are filled
  with float(0.0).

  Return type:
     *Tensor*
