code: def _data_augmentation(feature_dict):
      """Perform data augmentation on batches of data.
  
      Args:
        feature_dict: a dict containing features of samples
  
      Returns:
        The feature dict with augmented features
      """
      image_features = feature_dict[_transformed_name(_IMAGE_KEY)]
      image_features = _image_augmentation(image_features)
      feature_dict[_transformed_name(_IMAGE_KEY)] = image_features
      return feature_dict
  
imports: import os
  from typing import List
  import absl
  import flatbuffers
  import tensorflow
  import tensorflow_transform
  from tfx.components.trainer.fn_args_utils import DataAccessor
  from tfx.components.trainer.fn_args_utils import FnArgs
  from tfx.components.trainer.rewriting import converters
  from tfx.components.trainer.rewriting import rewriter
  from tfx.components.trainer.rewriting import rewriter_factory
  from tfx.dsl.io import fileio
  from tfx_bsl.tfxio import dataset_options
  from tflite_support import metadata_schema_py_generated
  from tflite_support import metadata
label_desc: Use image node_id 4 for calling a global function with example usage: _data_augmentation(feature_dict) and returns: feature_dict