content: #  Copyright (c) ZenML GmbH 2022. All Rights Reserved.
  #
  #  Licensed under the Apache License, Version 2.0 (the "License");
  #  you may not use this file except in compliance with the License.
  #  You may obtain a copy of the License at:
  #
  #       https://www.apache.org/licenses/LICENSE-2.0
  #
  #  Unless required by applicable law or agreed to in writing, software
  #  distributed under the License is distributed on an "AS IS" BASIS,
  #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
  #  or implied. See the License for the specific language governing
  #  permissions and limitations under the License.
  from typing import Tuple
  
  import numpy as np
  from typing_extensions import Annotated
  
  from zenml import step
  
  
  @step
  def normalizer(
      X_train: np.ndarray, X_test: np.ndarray
  ) -> Tuple[
      Annotated[np.ndarray, "X_train_normed"],
      Annotated[np.ndarray, "X_test_normed"],
  ]:
      """Normalize the values for all the images so they are between 0 and 1."""
      x_train_normed = X_train / 255.0
      x_test_normed = X_test / 255.0
      return x_train_normed, x_test_normed
  