/**
 * 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 <fstream>
#include <iostream>
#include <memory>
#include <string>

#include "common/common.h"
#include "utils/ms_utils.h"
#include "minddata/dataset/core/client.h"
#include "minddata/dataset/core/global_context.h"
#include "minddata/dataset/engine/datasetops/source/voc_op.h"
#include "minddata/dataset/engine/datasetops/source/sampler/distributed_sampler.h"
#include "minddata/dataset/engine/datasetops/source/sampler/pk_sampler.h"
#include "minddata/dataset/engine/datasetops/source/sampler/random_sampler.h"
#include "minddata/dataset/engine/datasetops/source/sampler/sampler.h"
#include "minddata/dataset/engine/datasetops/source/sampler/sequential_sampler.h"
#include "minddata/dataset/engine/datasetops/source/sampler/subset_random_sampler.h"
#include "minddata/dataset/engine/datasetops/source/sampler/weighted_random_sampler.h"
#include "minddata/dataset/util/path.h"
#include "minddata/dataset/util/status.h"
#include "gtest/gtest.h"
#include "utils/log_adapter.h"
#include "securec.h"

namespace common = mindspore::common;

using namespace mindspore::dataset;
using mindspore::MsLogLevel::ERROR;
using mindspore::ExceptionType::NoExceptionType;
using mindspore::LogStream;

std::shared_ptr<BatchOp> Batch(int batch_size = 1, bool drop = false, int rows_per_buf = 2);

std::shared_ptr<RepeatOp> Repeat(int repeat_cnt);

std::shared_ptr<ExecutionTree> Build(std::vector<std::shared_ptr<DatasetOp>> ops);

class MindDataTestVOCOp : public UT::DatasetOpTesting {
 protected:
};

TEST_F(MindDataTestVOCOp, TestVOCDetection) {
  // Start with an empty execution tree
  auto my_tree = std::make_shared<ExecutionTree>();
  std::string dataset_path;
  dataset_path = datasets_root_path_ + "/testVOC2012";

  std::string task_type("Detection");
  std::string task_mode("train");
  std::shared_ptr<VOCOp> my_voc_op;
  VOCOp::Builder builder;
  Status rc = builder.SetDir(dataset_path).SetTask(task_type).SetUsage(task_mode)
                     .Build(&my_voc_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssociateNode(my_voc_op);
  ASSERT_TRUE(rc.IsOk());
  rc = my_tree->AssignRoot(my_voc_op);
  ASSERT_TRUE(rc.IsOk());

  MS_LOG(DEBUG) << "Launch tree and begin iteration.";
  rc = my_tree->Prepare();
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->Launch();
  ASSERT_TRUE(rc.IsOk());

  // Start the loop of reading tensors from our pipeline
  DatasetIterator di(my_tree);
  TensorRow tensor_list;
  rc = di.FetchNextTensorRow(&tensor_list);
  ASSERT_TRUE(rc.IsOk());

  int row_count = 0;
  while (!tensor_list.empty()) {
    MS_LOG(DEBUG) << "Row display for row #: " << row_count << ".";

    //Display the tensor by calling the printer on it
    for (int i = 0; i < tensor_list.size(); i++) {
      std::ostringstream ss;
      ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
      MS_LOG(DEBUG) << "Tensor print: " << ss.str() << ".";
    }

    rc = di.FetchNextTensorRow(&tensor_list);
    ASSERT_TRUE(rc.IsOk());
    row_count++;
  }

  ASSERT_EQ(row_count, 9);
}

TEST_F(MindDataTestVOCOp, TestVOCSegmentation) {
  // Start with an empty execution tree
  auto my_tree = std::make_shared<ExecutionTree>();
  std::string dataset_path;
  dataset_path = datasets_root_path_ + "/testVOC2012";

  std::string task_type("Segmentation");
  std::string task_mode("train");
  std::shared_ptr<VOCOp> my_voc_op;
  VOCOp::Builder builder;
  Status rc = builder.SetDir(dataset_path).SetTask(task_type).SetUsage(task_mode)
                     .Build(&my_voc_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssociateNode(my_voc_op);
  ASSERT_TRUE(rc.IsOk());
  rc = my_tree->AssignRoot(my_voc_op);
  ASSERT_TRUE(rc.IsOk());

  MS_LOG(DEBUG) << "Launch tree and begin iteration.";
  rc = my_tree->Prepare();
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->Launch();
  ASSERT_TRUE(rc.IsOk());

  // Start the loop of reading tensors from our pipeline
  DatasetIterator di(my_tree);
  TensorRow tensor_list;
  rc = di.FetchNextTensorRow(&tensor_list);
  ASSERT_TRUE(rc.IsOk());

  int row_count = 0;
  while (!tensor_list.empty()) {
    MS_LOG(DEBUG) << "Row display for row #: " << row_count << ".";

    //Display the tensor by calling the printer on it
    for (int i = 0; i < tensor_list.size(); i++) {
      std::ostringstream ss;
      ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
      MS_LOG(DEBUG) << "Tensor print: " << ss.str() << ".";
    }

    rc = di.FetchNextTensorRow(&tensor_list);
    ASSERT_TRUE(rc.IsOk());
    row_count++;
  }

  ASSERT_EQ(row_count, 10);
}

TEST_F(MindDataTestVOCOp, TestVOCClassIndex) {
  // Start with an empty execution tree
  auto my_tree = std::make_shared<ExecutionTree>();
  std::string dataset_path;
  dataset_path = datasets_root_path_ + "/testVOC2012";

  std::string task_type("Detection");
  std::string task_mode("train");
  std::map<std::string, int32_t> class_index;
  class_index["car"] = 0;
  class_index["cat"] = 1;
  class_index["train"] = 5;
  std::shared_ptr<VOCOp> my_voc_op;
  VOCOp::Builder builder;
  Status rc =
    builder.SetDir(dataset_path).SetTask(task_type).SetUsage(task_mode)
                     .SetClassIndex(class_index)
                     .Build(&my_voc_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssociateNode(my_voc_op);
  ASSERT_TRUE(rc.IsOk());
  rc = my_tree->AssignRoot(my_voc_op);
  ASSERT_TRUE(rc.IsOk());

  MS_LOG(DEBUG) << "Launch tree and begin iteration.";
  rc = my_tree->Prepare();
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->Launch();
  ASSERT_TRUE(rc.IsOk());

  // Start the loop of reading tensors from our pipeline
  DatasetIterator di(my_tree);
  TensorRow tensor_list;
  rc = di.FetchNextTensorRow(&tensor_list);
  ASSERT_TRUE(rc.IsOk());

  int row_count = 0;
  while (!tensor_list.empty()) {
    MS_LOG(DEBUG) << "Row display for row #: " << row_count << ".";

    //Display the tensor by calling the printer on it
    for (int i = 0; i < tensor_list.size(); i++) {
      std::ostringstream ss;
      ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
      MS_LOG(DEBUG) << "Tensor print: " << ss.str() << ".";
    }

    rc = di.FetchNextTensorRow(&tensor_list);
    ASSERT_TRUE(rc.IsOk());
    row_count++;
  }

  ASSERT_EQ(row_count, 6);
}