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.
   */
  #include "common/common.h"
  #include "common/cvop_common.h"
  #include "dataset/kernels/image/random_color_adjust_op.h"
  #include "dataset/core/cv_tensor.h"
  #include "utils/log_adapter.h"
  
  using namespace mindspore::dataset;
  using mindspore::MsLogLevel::INFO;
  using mindspore::ExceptionType::NoExceptionType;
  using mindspore::LogStream;
  
  class MindDataTestRandomColorAdjustOp : public UT::CVOP::CVOpCommon {
   public:
    MindDataTestRandomColorAdjustOp() : CVOpCommon() {}
  };
  
  TEST_F(MindDataTestRandomColorAdjustOp, TestOp1) {
    MS_LOG(INFO) << "Doing testRandomColorAdjustOp.";
  
    std::shared_ptr<Tensor> output_tensor;
    std::unique_ptr<RandomColorAdjustOp> op(new RandomColorAdjustOp(0.7, 1.3, 0.8, 1.2, 0.8, 1.2, -0.2, 0.2));
    EXPECT_TRUE(op->OneToOne());
    Status s = op->Compute(input_tensor_, &output_tensor);
    EXPECT_TRUE(s.IsOk());
    EXPECT_EQ(input_tensor_->shape()[0], output_tensor->shape()[0]);
    EXPECT_EQ(input_tensor_->shape()[1], output_tensor->shape()[1]);
  }
  
  TEST_F(MindDataTestRandomColorAdjustOp, TestOp2) {
    MS_LOG(INFO) << "Doing testRandomColorAdjustOp2.";
  
    std::shared_ptr<Tensor> output_tensor;
    std::unique_ptr<RandomColorAdjustOp> op(new RandomColorAdjustOp(0.7, 1.3, 0.8, 1.2, 0.8, 1.2, -0.2, 0.2));
  
    Status s = op->Compute(input_tensor_, &output_tensor);
    EXPECT_TRUE(s.IsOk());
    EXPECT_EQ(input_tensor_->shape()[0], output_tensor->shape()[0]);
    EXPECT_EQ(input_tensor_->shape()[1], output_tensor->shape()[1]);
  }
  
  TEST_F(MindDataTestRandomColorAdjustOp, TestOp3) {
    MS_LOG(INFO) << "Doing testRandomColorAdjustOp Brightness.";
  
    std::shared_ptr<Tensor> output_tensor;
    std::unique_ptr<RandomColorAdjustOp> op(new RandomColorAdjustOp(0.8, 0.8, 0, 0, 0, 0, 0, 0));
  
    Status s = op->Compute(input_tensor_, &output_tensor);
    EXPECT_TRUE(s.IsOk());
    EXPECT_EQ(input_tensor_->shape()[0], output_tensor->shape()[0]);
    EXPECT_EQ(input_tensor_->shape()[1], output_tensor->shape()[1]);
  }
  
  TEST_F(MindDataTestRandomColorAdjustOp, TestOp4) {
    MS_LOG(INFO) << "Doing testRandomColorAdjustOp Brightness.";
  
    std::shared_ptr<Tensor> output_tensor;
    std::unique_ptr<RandomColorAdjustOp> op(new RandomColorAdjustOp(0.8, 0.8, 0, 0, 0, 0, 0.2, 0.2));
  
    Status s = op->Compute(input_tensor_, &output_tensor);
    EXPECT_TRUE(s.IsOk());
    EXPECT_EQ(input_tensor_->shape()[0], output_tensor->shape()[0]);
    EXPECT_EQ(input_tensor_->shape()[1], output_tensor->shape()[1]);
  }
  