class_docstr: Transformers with convolutional context for ASR
  https://arxiv.org/abs/1904.11660
class_docstr_tok: ["Transformers","with","convolutional","context","for","ASR","https",":","\/\/arxiv.org\/abs\/1904.11660"]
code: def __init__(self, encoder, decoder):
      super().__init__(encoder, decoder)
  
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 1 to create a new VGGTransformerModel object from inherited base classes: FairseqEncoderDecoderModel with example: obj = VGGTransformerModel(encoder, decoder)