class_docstr: Train Transformer for LASER task
  
  Requires --task laser
class_docstr_tok: ["Train","Transformer","for","LASER","task","Requires","--","task","laser"]
code: def forward(
      self,
      src_tokens,
      src_lengths,
      prev_output_tokens=None,
      tgt_tokens=None,
      tgt_lengths=None,
      target_language_id=-1,
      dataset_name="",
  ):
      laser_encoder_out = self.encoder(src_tokens, src_lengths)
      return self.decoder(
          prev_output_tokens,
          laser_encoder_out,
          lang_id=target_language_id,
      )
  
imports: import logging
  from typing import Any, Dict, List, Optional
  from torch import Tensor
  import torch
  import torch.nn
  from fairseq.models import FairseqEncoderDecoderModel, register_model, register_model_architecture
  from fairseq.models.transformer import base_architecture, Embedding, TransformerModel, TransformerEncoder, TransformerDecoder
  from fairseq.modules import TransformerDecoderLayer
label_desc: Use image node_id 2 for calling the LaserTransformerModel obj's underlying member method code with example usage: obj.forward(src_tokens, src_lengths, prev_output_tokens, tgt_tokens, tgt_lengths, target_language_id, dataset_name) and returns: self