class_docstr: No-op encoder.
  
  Useful for decoder-only transformers.
class_docstr_tok: ["No-op","encoder",".","Useful","for","decoder-only","transformers","."]
docstr: TransformerGeneratorModel expects ``(encoder_output, encoder_mask)``.
docstr_tok: ["TransformerGeneratorModel","expects","``","(","encoder_output",",","encoder_mask",")","``","."]
code: def forward(self, xs):
      """
      TransformerGeneratorModel expects ``(encoder_output, encoder_mask)``.
      """
      return xs, None
  
imports: from __future__ import annotations
  from typing import Tuple, Optional, Union
  import numpy
  import torch
  import torch.nn
  from parlai.agents.transformer.modules import create_position_codes, get_n_positions_from_options, LAYER_NORM_EPS, MultiHeadAttention, TransformerFFN
  from parlai.agents.transformer.modules.modular import swappable
  from parlai.core.opt import Opt
  from parlai.core.params import default
  from parlai.utils.misc import warn_once
  from parlai.utils.torch import PipelineHelper
  from parlai.utils.fsdp import fsdp_wrap
  from parlai.nn.checkpoint import checkpoint_wrapper
label_desc: Use image node_id 2 for calling the PassThroughEncoder obj's underlying member method code with example usage: obj.forward(xs) and returns: xs,  None