class_docstr: VGG + Transformer encoder
class_docstr_tok: ["VGG","+","Transformer","encoder"]
code: def reorder_encoder_out(self, encoder_out, new_order):
      encoder_out["encoder_out"] = encoder_out[
          "encoder_out"
      ].index_select(1, new_order)
      if encoder_out["encoder_padding_mask"] is not None:
          encoder_out["encoder_padding_mask"] = encoder_out[
              "encoder_padding_mask"
          ].index_select(1, new_order)
      return encoder_out
  
imports: import argparse
  import math
  from collections.abc import Iterable
  import torch
  import torch.nn
  from examples.speech_recognition.data.data_utils import lengths_to_encoder_padding_mask
  from fairseq import utils
  from fairseq.models import FairseqEncoder, FairseqEncoderDecoderModel, FairseqEncoderModel, FairseqIncrementalDecoder, register_model, register_model_architecture
  from fairseq.modules import LinearizedConvolution, TransformerDecoderLayer, TransformerEncoderLayer, VGGBlock
label_desc: Use image node_id 9 for calling the VGGTransformerEncoder obj's underlying member method code with example usage: obj.reorder_encoder_out(encoder_out, new_order) and returns: encoder_out