code: from typing import NamedTuple
  
  def CsvExampleGen(
      output_examples_uri: 'ExamplesUri',
      input_base: str,
      input_config: {'JsonObject': {'data_type': 'proto:tfx.components.example_gen.Input'}},
      output_config: {'JsonObject': {'data_type': 'proto:tfx.components.example_gen.Output'}},
      range_config: {'JsonObject': {'data_type': 'proto:tfx.configs.RangeConfig'}} = None,
      beam_pipeline_args: list = None,
  ) -> NamedTuple('Outputs', [
      ('examples_uri', 'ExamplesUri'),
  ]):
      from tfx.components.example_gen.csv_example_gen.component import CsvExampleGen as component_class
  
      #Generated code
      import os
      import tempfile
      from tensorflow.io import gfile
      from google.protobuf import json_format, message
      from tfx.types import channel_utils, artifact_utils
      from tfx.components.base import base_executor
  
      arguments = locals().copy()
  
      component_class_args = {}
  
      for name, execution_parameter in component_class.SPEC_CLASS.PARAMETERS.items():
          argument_value = arguments.get(name, None)
          if argument_value is None:
              continue
          parameter_type = execution_parameter.type
          if isinstance(parameter_type, type) and issubclass(parameter_type, message.Message):
              argument_value_obj = parameter_type()
              json_format.Parse(argument_value, argument_value_obj)
          else:
              argument_value_obj = argument_value
          component_class_args[name] = argument_value_obj
  
      for name, channel_parameter in component_class.SPEC_CLASS.INPUTS.items():
          artifact_path = arguments.get(name + '_uri') or arguments.get(name + '_path')
          if artifact_path:
              artifact = channel_parameter.type()
              artifact.uri = artifact_path.rstrip('/') + '/'  # Some TFX components require that the artifact URIs end with a slash
              if channel_parameter.type.PROPERTIES and 'split_names' in channel_parameter.type.PROPERTIES:
                  # Recovering splits
                  subdirs = gfile.listdir(artifact_path)
                  # Workaround for https://github.com/tensorflow/tensorflow/issues/39167
                  subdirs = [subdir.rstrip('/') for subdir in subdirs]
                  split_names = [subdir.replace('Split-', '') for subdir in subdirs]
                  artifact.split_names = artifact_utils.encode_split_names(sorted(split_names))
              component_class_args[name] = channel_utils.as_channel([artifact])
  
      component_class_instance = component_class(**component_class_args)
  
      input_dict = channel_utils.unwrap_channel_dict(component_class_instance.inputs.get_all())
      output_dict = {}
      exec_properties = component_class_instance.exec_properties
  
      # Generating paths for output artifacts
      for name, channel in component_class_instance.outputs.items():
          artifact_path = arguments.get('output_' + name + '_uri') or arguments.get(name + '_path')
          if artifact_path:
              artifact = channel.type()
              artifact.uri = artifact_path.rstrip('/') + '/'  # Some TFX components require that the artifact URIs end with a slash
              artifact_list = [artifact]
              channel._artifacts = artifact_list
              output_dict[name] = artifact_list
  
      print('component instance: ' + str(component_class_instance))
  
      executor_context = base_executor.BaseExecutor.Context(
          beam_pipeline_args=arguments.get('beam_pipeline_args'),
          tmp_dir=tempfile.gettempdir(),
          unique_id='tfx_component',
      )
      executor = component_class_instance.executor_spec.executor_class(executor_context)
      executor.Do(
          input_dict=input_dict,
          output_dict=output_dict,
          exec_properties=exec_properties,
      )
  
      return (output_examples_uri, )
  
apis: tensorflow.io.gfile.listdir