class_docstr: LightConv and DynamicConv model from `"Pay Less Attention with Lightweight and Dynamic Convolutions" (Wu, et al, 2019)
  <https://openreview.net/pdf?id=SkVhlh09tX>`_.
  To use LightConv please set ``--encoder-conv-type lightweight --decoder-conv-type lightweight``
  To use DynamicConv please set ``--encoder-conv-type dynamic --decoder-conv-type dynamic``
  
  Args:
      encoder (LightConvEncoder): the encoder
      decoder (LightConvDecoder): the decoder
  
  The LightConv model provides the following named architectures and
  command-line arguments:
  
  .. argparse::
      :ref: fairseq.models.lightconv_parser
      :prog:
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code: def hub_models(cls):
      # fmt: off
  
          def moses_subword(path):
              return {
                  'path': path,
                  'tokenizer': 'moses',
                  'bpe': 'subword_nmt',
              }
  
          return {
              'lightconv.no_glu.iwslt14.de-en': moses_subword('https://dl.fbaipublicfiles.com/fairseq/models/dynamicconv/iwslt14.de-en.lightconv.tar.gz'),
              'dynamicconv.no_glu.iwslt14.de-en': moses_subword('https://dl.fbaipublicfiles.com/fairseq/models/dynamicconv/iwslt14.de-en.dynamicconv.tar.gz'),
              'lightconv.no_glu.wmt16.en-de': moses_subword('https://dl.fbaipublicfiles.com/fairseq/models/dynamicconv/wmt16.en-de.joined-dict.lightconv.tar.gz'),
              'dynamicconv.no_glu.wmt16.en-de': moses_subword('https://dl.fbaipublicfiles.com/fairseq/models/dynamicconv/wmt16.en-de.joined-dict.dynamicconv.tar.gz'),
              'lightconv.glu.wmt16.en-de': moses_subword('https://dl.fbaipublicfiles.com/fairseq/models/dynamicconv/wmt16.en-de.joined-dict.lightconv-glu.tar.gz'),
              'dynamicconv.glu.wmt16.en-de': moses_subword('https://dl.fbaipublicfiles.com/fairseq/models/dynamicconv/wmt16.en-de.joined-dict.dynamicconv-glu.tar.gz'),
              'lightconv.glu.wmt17.en-de': moses_subword('https://dl.fbaipublicfiles.com/fairseq/models/dynamicconv/wmt16.en-de.joined-dict.lightconv-glu.tar.gz'),
              'dynamicconv.glu.wmt17.en-de': moses_subword('https://dl.fbaipublicfiles.com/fairseq/models/dynamicconv/wmt16.en-de.joined-dict.dynamicconv-glu.tar.gz'),
              'lightconv.glu.wmt14.en-fr': moses_subword('https://dl.fbaipublicfiles.com/fairseq/models/dynamicconv/wmt14.en-fr.joined-dict.lightconv-glu.tar.gz'),
              'dynamicconv.glu.wmt14.en-fr': moses_subword('https://dl.fbaipublicfiles.com/fairseq/models/dynamicconv/wmt14.en-fr.joined-dict.dynamicconv-glu.tar.gz'),
              'lightconv.glu.wmt17.zh-en': moses_subword('https://dl.fbaipublicfiles.com/fairseq/models/dynamicconv/wmt17.zh-en.lightconv-glu.tar.gz'),
              'dynamicconv.glu.wmt17.zh-en': moses_subword('https://dl.fbaipublicfiles.com/fairseq/models/dynamicconv/wmt17.zh-en.dynamicconv-glu.tar.gz'),
          }
  
imports: import math
  from typing import Any, Dict, List, Optional, Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  from fairseq import utils
  from fairseq.models import FairseqEncoder, FairseqEncoderDecoderModel, FairseqIncrementalDecoder, register_model, register_model_architecture
  from fairseq.modules import AdaptiveSoftmax, DynamicConv_scripatable, FairseqDropout, LayerNorm, LightweightConv, MultiheadAttention, PositionalEmbedding
  from fairseq.utils import safe_hasattr
  from torch import Tensor
label_desc: Use image node_id 1 for calling the LightConvModel obj's underlying member method code with example usage: obj.hub_models(cls) and returns: dict, dict