code: def _generate_examples(self, file_path):
      
  
      with tf.io.gfile.GFile(file_path) as f:
        raw_data = csv.DictReader(f)
        for row in raw_data:
          survive_val = row.pop("survived")
          yield {
              "survived": convert_to_label(survive_val, _SURVIVED_DICT),
              "features": {
                  name: FEATURE_DICT[name][1](value)
                  for name, value in row.items()
              }
          }
docs: Generate features and target given the directory path.
  
      Args:
        file_path: path where the csv file is stored
  
      Yields:
        The features and the target