parameters: (model_type, checkpoint_file, output_dir, remove_variables_regex)
docstring: Returns Checkpoint dumper instance for a given model type.
  
    Parameters
    ----------
    model_type : str
        Type of deeplearning framework
    checkpoint_file : str
        Path to checkpoint file
    output_dir : str
        Path to output directory
    remove_variables_regex : str
        Regex for variables to be ignored
  
    Returns
    -------
    (TensorflowCheckpointDumper, PytorchCheckpointDumper)
        Checkpoint Dumper Instance for corresponding model type
  
    Raises
    ------
    Error
        If particular model type is not supported
docstring_summary: Returns Checkpoint dumper instance for a given model type.
docstring_tokens: Returns Checkpoint dumper instance for a given model type .
function: def get_checkpoint_dumper(model_type, checkpoint_file, output_dir, remove_variables_regex):
    """Returns Checkpoint dumper instance for a given model type.
  
    Parameters
    ----------
    model_type : str
        Type of deeplearning framework
    checkpoint_file : str
        Path to checkpoint file
    output_dir : str
        Path to output directory
    remove_variables_regex : str
        Regex for variables to be ignored
  
    Returns
    -------
    (TensorflowCheckpointDumper, PytorchCheckpointDumper)
        Checkpoint Dumper Instance for corresponding model type
  
    Raises
    ------
    Error
        If particular model type is not supported
    """
    if model_type == 'tensorflow':
      from tensorflow_checkpoint_dumper import TensorflowCheckpointDumper
  
      return TensorflowCheckpointDumper(
        checkpoint_file, output_dir, remove_variables_regex)
    elif model_type == 'pytorch':
      from pytorch_checkpoint_dumper import PytorchCheckpointDumper
  
      return PytorchCheckpointDumper(
        checkpoint_file, output_dir, remove_variables_regex)
    else:
      raise Error('Currently, "%s" models are not supported'.format(model_type))
function_tokens: def get_checkpoint_dumper ( model_type , checkpoint_file , output_dir , remove_variables_regex ) : if model_type == 'tensorflow' : from tensorflow_checkpoint_dumper import TensorflowCheckpointDumper return TensorflowCheckpointDumper ( checkpoint_file , output_dir , remove_variables_regex ) elif model_type == 'pytorch' : from pytorch_checkpoint_dumper import PytorchCheckpointDumper return PytorchCheckpointDumper ( checkpoint_file , output_dir , remove_variables_regex ) else : raise Error ( 'Currently, "%s" models are not supported' . format ( model_type ) )