class_docstr: `FeatureConnector` for text, encoding to integers with a `TextEncoder`.
code: def load_metadata(self, data_dir, feature_name: str) -> None:
      if self._encoder_cls:
          fname_prefix = _file_name_prefix_for_metadata(
              feature_name, data_dir
          )
          self._encoder = self._encoder_cls.load_from_file(
              fname_prefix
          )  # pytype: disable=attribute-error
          return
  
      # Error checking: ensure there are no metadata files
      feature_files = list(
          epath.Path(data_dir).glob(f"{feature_name}.text*")
      )
      if feature_files:
          raise ValueError(
              "Text feature files found for feature %s but encoder_cls=None. "
              "Make sure to set encoder_cls in the TextEncoderConfig. "
              "Files: %s" % (feature_name, feature_files)
          )
  
imports: import html
  import os
  import textwrap
  from typing import Union
  from absl import logging
  from etils import epath
  import numpy
  from tensorflow_datasets.core.deprecated import text
  from tensorflow_datasets.core.features import feature
  from tensorflow_datasets.core.features import tensor_feature
  from tensorflow_datasets.core.proto import feature_pb2
  from tensorflow_datasets.core.utils import type_utils
label_desc: Use image node_id 11 for calling the Text obj's underlying member method code with example usage: obj.load_metadata(data_dir, feature_name) without return types