text: # Copyright 2019 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.
  # ==============================================================================
  import mindspore.common.dtype as mstype
  import mindspore.dataset as ds
  from mindspore import log as logger
  
  # just a basic test with parallel random data op
  def test_randomdataset_basic1():
      logger.info("Test randomdataset basic 1")
  
      schema = ds.Schema()
      schema.add_column('image', de_type=mstype.uint8, shape=[2])
      schema.add_column('label', de_type=mstype.uint8, shape=[1])
  
      # apply dataset operations
      ds1 = ds.RandomDataset(schema=schema, total_rows=50, num_parallel_workers=4)
      ds1 = ds1.repeat(4)
  
      num_iter = 0
      for data in ds1.create_dict_iterator():  # each data is a dictionary
          # in this example, each dictionary has keys "image" and "label"
          logger.info("{} image: {}".format(num_iter, data["image"]))
          logger.info("{} label: {}".format(num_iter, data["label"]))
          num_iter += 1
  
      logger.info("Number of data in ds1: {}".format(num_iter))
      assert num_iter == 200
      logger.info("Test randomdataset basic 1 complete")
  
  
  # Another simple test
  def test_randomdataset_basic2():
      logger.info("Test randomdataset basic 2")
  
      schema = ds.Schema()
      schema.add_column('image', de_type=mstype.uint8,
                        shape=[640, 480, 3])  # 921600 bytes (a bit less than 1 MB per image)
      schema.add_column('label', de_type=mstype.uint8, shape=[1])
  
      # Make up 10 rows
      ds1 = ds.RandomDataset(schema=schema, total_rows=10, num_parallel_workers=1)
      ds1 = ds1.repeat(4)
  
      num_iter = 0
      for data in ds1.create_dict_iterator():  # each data is a dictionary
          # in this example, each dictionary has keys "image" and "label"
          # logger.info(data["image"])
          logger.info("printing the label: {}".format(data["label"]))
          num_iter += 1
  
      logger.info("Number of data in ds1: {}".format(num_iter))
      assert num_iter == 40
      logger.info("Test randomdataset basic 2 complete")
  
  
  # Another simple test
  def test_randomdataset_basic3():
      logger.info("Test randomdataset basic 3")
  
      # Make up 10 samples, but here even the schema is randomly created
      # The columns are named like this "c0", "c1", "c2" etc
      # But, we will use a tuple iterator instead of dict iterator so the column names
      # are not needed to iterate
      ds1 = ds.RandomDataset(total_rows=10, num_parallel_workers=1)
      ds1 = ds1.repeat(2)
  
      num_iter = 0
      for _ in ds1.create_tuple_iterator():
          num_iter += 1
  
      logger.info("Number of data in ds1: {}".format(num_iter))
      assert num_iter == 20
      logger.info("Test randomdataset basic 3 Complete")
  
  if __name__ == '__main__':
      test_randomdataset_basic1()
      test_randomdataset_basic2()
      test_randomdataset_basic3()
  