code: def run(self):
      if self._model_type == "albert":
          try:
              from ..models.albert.convert_albert_original_tf_checkpoint_to_pytorch import (
                  convert_tf_checkpoint_to_pytorch,
              )
          except ImportError:
              raise ImportError(IMPORT_ERROR_MESSAGE)
  
          convert_tf_checkpoint_to_pytorch(
              self._tf_checkpoint,
              self._config,
              self._pytorch_dump_output,
          )
      elif self._model_type == "bert":
          try:
              from ..models.bert.convert_bert_original_tf_checkpoint_to_pytorch import (
                  convert_tf_checkpoint_to_pytorch,
              )
          except ImportError:
              raise ImportError(IMPORT_ERROR_MESSAGE)
  
          convert_tf_checkpoint_to_pytorch(
              self._tf_checkpoint,
              self._config,
              self._pytorch_dump_output,
          )
      elif self._model_type == "funnel":
          try:
              from ..models.funnel.convert_funnel_original_tf_checkpoint_to_pytorch import (
                  convert_tf_checkpoint_to_pytorch,
              )
          except ImportError:
              raise ImportError(IMPORT_ERROR_MESSAGE)
  
          convert_tf_checkpoint_to_pytorch(
              self._tf_checkpoint,
              self._config,
              self._pytorch_dump_output,
          )
      elif self._model_type == "t5":
          try:
              from ..models.t5.convert_t5_original_tf_checkpoint_to_pytorch import (
                  convert_tf_checkpoint_to_pytorch,
              )
          except ImportError:
              raise ImportError(IMPORT_ERROR_MESSAGE)
  
          convert_tf_checkpoint_to_pytorch(
              self._tf_checkpoint,
              self._config,
              self._pytorch_dump_output,
          )
      elif self._model_type == "gpt":
          from ..models.openai.convert_openai_original_tf_checkpoint_to_pytorch import (
              convert_openai_checkpoint_to_pytorch,
          )
  
          convert_openai_checkpoint_to_pytorch(
              self._tf_checkpoint,
              self._config,
              self._pytorch_dump_output,
          )
      elif self._model_type == "transfo_xl":
          try:
              from ..models.transfo_xl.convert_transfo_xl_original_tf_checkpoint_to_pytorch import (
                  convert_transfo_xl_checkpoint_to_pytorch,
              )
          except ImportError:
              raise ImportError(IMPORT_ERROR_MESSAGE)
  
          if "ckpt" in self._tf_checkpoint.lower():
              TF_CHECKPOINT = self._tf_checkpoint
              TF_DATASET_FILE = ""
          else:
              TF_DATASET_FILE = self._tf_checkpoint
              TF_CHECKPOINT = ""
          convert_transfo_xl_checkpoint_to_pytorch(
              TF_CHECKPOINT,
              self._config,
              self._pytorch_dump_output,
              TF_DATASET_FILE,
          )
      elif self._model_type == "gpt2":
          try:
              from ..models.gpt2.convert_gpt2_original_tf_checkpoint_to_pytorch import (
                  convert_gpt2_checkpoint_to_pytorch,
              )
          except ImportError:
              raise ImportError(IMPORT_ERROR_MESSAGE)
  
          convert_gpt2_checkpoint_to_pytorch(
              self._tf_checkpoint,
              self._config,
              self._pytorch_dump_output,
          )
      elif self._model_type == "xlnet":
          try:
              from ..models.xlnet.convert_xlnet_original_tf_checkpoint_to_pytorch import (
                  convert_xlnet_checkpoint_to_pytorch,
              )
          except ImportError:
              raise ImportError(IMPORT_ERROR_MESSAGE)
  
          convert_xlnet_checkpoint_to_pytorch(
              self._tf_checkpoint,
              self._config,
              self._pytorch_dump_output,
              self._finetuning_task_name,
          )
      elif self._model_type == "xlm":
          from ..models.xlm.convert_xlm_original_pytorch_checkpoint_to_pytorch import (
              convert_xlm_checkpoint_to_pytorch,
          )
  
          convert_xlm_checkpoint_to_pytorch(
              self._tf_checkpoint, self._pytorch_dump_output
          )
      elif self._model_type == "lxmert":
          from ..models.lxmert.convert_lxmert_original_pytorch_checkpoint_to_pytorch import (
              convert_lxmert_checkpoint_to_pytorch,
          )
  
          convert_lxmert_checkpoint_to_pytorch(
              self._tf_checkpoint, self._pytorch_dump_output
          )
      elif self._model_type == "rembert":
          from ..models.rembert.convert_rembert_tf_checkpoint_to_pytorch import (
              convert_rembert_tf_checkpoint_to_pytorch,
          )
  
          convert_rembert_tf_checkpoint_to_pytorch(
              self._tf_checkpoint,
              self._config,
              self._pytorch_dump_output,
          )
      else:
          raise ValueError(
              "--model_type should be selected in the list [bert, gpt, gpt2, t5, transfo_xl, xlnet, xlm, lxmert]"
          )
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/src/transformers/commands/convert.py
imports: from argparse import ArgumentParser, Namespace
  from ..utils import logging
  from .None import BaseTransformersCLICommand
label_desc: Use image node_id 3 for calling the ConvertCommand obj's underlying member method code with example usage: obj.run() without return types