text: # Copyright 2020 Huawei Technologies Co., Ltd
  #
  # 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
  #
  # http://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.
  # ==============================================================================
  """
  Testing RandomPerspective op in DE
  """
  import numpy as np
  import mindspore.dataset as ds
  import mindspore.dataset.transforms.vision.py_transforms as py_vision
  from mindspore.dataset.transforms.vision.utils import Inter
  from mindspore import log as logger
  from util import visualize_list, save_and_check_md5, \
      config_get_set_seed, config_get_set_num_parallel_workers
  
  
  GENERATE_GOLDEN = False
  
  DATA_DIR = ["../data/dataset/test_tf_file_3_images/train-0000-of-0001.data"]
  SCHEMA_DIR = "../data/dataset/test_tf_file_3_images/datasetSchema.json"
  
  
  def test_random_perspective_op(plot=False):
      """
      Test RandomPerspective in python transformations
      """
      logger.info("test_random_perspective_op")
      # define map operations
      transforms1 = [
          py_vision.Decode(),
          py_vision.RandomPerspective(),
          py_vision.ToTensor()
      ]
      transform1 = py_vision.ComposeOp(transforms1)
  
      transforms2 = [
          py_vision.Decode(),
          py_vision.ToTensor()
      ]
      transform2 = py_vision.ComposeOp(transforms2)
  
      #  First dataset
      data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
      data1 = data1.map(input_columns=["image"], operations=transform1())
      #  Second dataset
      data2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
      data2 = data2.map(input_columns=["image"], operations=transform2())
  
      image_perspective = []
      image_original = []
      for item1, item2 in zip(data1.create_dict_iterator(), data2.create_dict_iterator()):
          image1 = (item1["image"].transpose(1, 2, 0) * 255).astype(np.uint8)
          image2 = (item2["image"].transpose(1, 2, 0) * 255).astype(np.uint8)
          image_perspective.append(image1)
          image_original.append(image2)
      if plot:
          visualize_list(image_original, image_perspective)
  
  
  def skip_test_random_perspective_md5():
      """
      Test RandomPerspective with md5 comparison
      """
      logger.info("test_random_perspective_md5")
      original_seed = config_get_set_seed(5)
      original_num_parallel_workers = config_get_set_num_parallel_workers(1)
  
      # define map operations
      transforms = [
          py_vision.Decode(),
          py_vision.RandomPerspective(distortion_scale=0.3, prob=0.7,
                                      interpolation=Inter.BILINEAR),
          py_vision.Resize(1450), # resize to a smaller size to prevent round-off error
          py_vision.ToTensor()
      ]
      transform = py_vision.ComposeOp(transforms)
  
      #  Generate dataset
      data = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
      data = data.map(input_columns=["image"], operations=transform())
  
      # check results with md5 comparison
      filename = "random_perspective_01_result.npz"
      save_and_check_md5(data, filename, generate_golden=GENERATE_GOLDEN)
  
      # Restore configuration
      ds.config.set_seed(original_seed)
      ds.config.set_num_parallel_workers((original_num_parallel_workers))
  
  
  def test_random_perspective_exception_distortion_scale_range():
      """
      Test RandomPerspective: distortion_scale is not in [0, 1], expected to raise ValueError
      """
      logger.info("test_random_perspective_exception_distortion_scale_range")
      try:
          _ = py_vision.RandomPerspective(distortion_scale=1.5)
      except ValueError as e:
          logger.info("Got an exception in DE: {}".format(str(e)))
          assert str(e) == "Input distortion_scale is not within the required interval of (0.0 to 1.0)."
  
  
  def test_random_perspective_exception_prob_range():
      """
      Test RandomPerspective: prob is not in [0, 1], expected to raise ValueError
      """
      logger.info("test_random_perspective_exception_prob_range")
      try:
          _ = py_vision.RandomPerspective(prob=1.2)
      except ValueError as e:
          logger.info("Got an exception in DE: {}".format(str(e)))
          assert str(e) == "Input prob is not within the required interval of (0.0 to 1.0)."
  
  
  if __name__ == "__main__":
      test_random_perspective_op(plot=True)
      skip_test_random_perspective_md5()
      test_random_perspective_exception_distortion_scale_range()
      test_random_perspective_exception_prob_range()
  