code: def hub_models(cls):
      base_url = "http://dl.fbaipublicfiles.com/fairseq/s2t"
      model_ids = [
          "xm_transformer_600m-es_en-multi_domain",
          "xm_transformer_600m-ru_en-multi_domain",
          "xm_transformer_600m-fr_en-multi_domain",
          "xm_transformer_600m-en_es-multi_domain",
          "xm_transformer_600m-en_ru-multi_domain",
          "xm_transformer_600m-en_fr-multi_domain",
          "xm_transformer_600m-en_zh-multi_domain",
          "xm_transformer_600m-en_ar-multi_domain",
          "xm_transformer_600m-en_tr-multi_domain",
          "xm_transformer_600m-en_vi-multi_domain",
          "xm_transformer-21_en-xls_r_300m",
          "xm_transformer-en_15-xls_r_300m",
          "xm_transformer-21_en-xls_r_1b",
          "xm_transformer-en_15-xls_r_1b",
          "xm_transformer-21_en-xls_r_2b",
          "xm_transformer-en_15-xls_r_2b",
          "xm_transformer-22_16-xls_r_2b",
          "xm_transformer_s2ut_800m-es-en-st-asr-bt_h1_2022",
          "xm_transformer_s2ut_800m-en-es-st_plus_asr",
          "xm_transformer_s2ut_800m-hk-en-h1_2022",
          "xm_transformer_s2ut_800m-en-hk-h1_2022",
      ]
      return {i: f"{base_url}/{i}.tar.gz" for i in model_ids}
  
imports: import copy
  import logging
  from typing import Dict, List, Optional, Tuple
  import numpy
  import torch
  import torch.nn
  from torch import Tensor
  from fairseq import checkpoint_utils, utils
  from fairseq.data.data_utils import lengths_to_padding_mask
  from fairseq.models import FairseqEncoder, FairseqEncoderDecoderModel, FairseqEncoderModel, FairseqLanguageModel, register_model, register_model_architecture
  from fairseq.models.speech_to_speech.modules.ctc_decoder import CTCDecoder
  from fairseq.models.speech_to_text.hub_interface import S2THubInterface
  from fairseq.models.transformer import Embedding, TransformerDecoder, TransformerModelBase
  from fairseq.models.wav2vec import Wav2VecEncoder
  from fairseq.modules.layer_norm import LayerNorm
label_desc: Use image node_id 1 for calling the XMTransformerModel obj's underlying member method code with example usage: obj.hub_models(cls) and returns: unknown