text: #  Copyright (c) ZenML GmbH 2021. 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 sklearn.base import ClassifierMixin
  from sklearn.datasets import load_digits
  from sklearn.model_selection import train_test_split
  from sklearn.svm import SVC
  
  
  def get_digits() -> Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]:
      """Returns the digits dataset in the form of a tuple of numpy
      arrays."""
      digits = load_digits()
      # flatten the images
      n_samples = len(digits.images)
      data = digits.images.reshape((n_samples, -1))
  
      # Split data into 50% train and 50% test subsets
      X_train, X_test, y_train, y_test = train_test_split(
          data, digits.target, test_size=0.5, shuffle=False
      )
      return X_train, X_test, y_train, y_test
  
  
  def get_digits_model() -> ClassifierMixin:
      """Creates a support vector classifier for digits dataset."""
      return SVC(gamma=0.001)
  