/**
 * Copyright 2019-2021 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 <chrono>
#include <cstring>
#include <iostream>
#include <memory>
#include <string>
#include "minddata/dataset/core/client.h"
#include "minddata/dataset/core/tensor.h"
#include "minddata/dataset/core/config_manager.h"
#include "minddata/dataset/engine/datasetops/zip_op.h"
#include "minddata/dataset/engine/jagged_connector.h"
#include "common/common.h"
#include "utils/ms_utils.h"

#include "gtest/gtest.h"
#include "utils/log_adapter.h"

namespace common = mindspore::common;

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

class MindDataTestZipOp : public UT::DatasetOpTesting {};

TEST_F(MindDataTestZipOp, MindDataTestZipOpDefault) {
  /* Tree:
   *
   *
   *                  OpId(2) ZipOp
   *            /                       \
   *     OpId(0) TFReaderOp    OpId(1) TFReaderOp
   * Start with an empty execution tree
   */
  Status rc;
  MS_LOG(INFO) << "UT test TestZipBasic.";
  auto my_tree = std::make_shared<ExecutionTree>();
  // Creating TFReaderOp

  std::string dataset_path = datasets_root_path_ + "/test_tf_file_3_images/train-0000-of-0001.data";
  std::string dataset_path2 = datasets_root_path_ + "/testBatchDataset/test.data";
  std::shared_ptr<ConfigManager> config_manager = GlobalContext::config_manager();
  std::vector<std::string> columns_to_load = {};
  std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
  std::vector<std::string> files1 = {dataset_path};
  auto op_connector_size = config_manager->op_connector_size();
  std::shared_ptr<TFReaderOp> my_tfreader_op = std::make_shared<TFReaderOp>(
    1, 16, 0, files1, std::move(schema), op_connector_size, columns_to_load, false, 1, 0, false);
  rc = my_tfreader_op->Init();
  EXPECT_TRUE(rc.IsOk());
  rc = my_tree->AssociateNode(my_tfreader_op);
  EXPECT_TRUE(rc.IsOk());
  std::vector<std::string> files2 = {dataset_path2};
  std::unique_ptr<DataSchema> schema2 = std::make_unique<DataSchema>();
  std::shared_ptr<TFReaderOp> my_tfreader_op2 = std::make_shared<TFReaderOp>(
    1, 1, 0, files2, std::make_unique<DataSchema>(), op_connector_size, columns_to_load, false, 1, 0, false);
  rc = my_tfreader_op2->Init();
  EXPECT_TRUE(rc.IsOk());
  rc = my_tree->AssociateNode(my_tfreader_op2);
  EXPECT_TRUE(rc.IsOk());

  // Creating DatasetOp
  std::shared_ptr<ZipOp> zip_op = std::make_shared<ZipOp>();

  rc = my_tree->AssociateNode(zip_op);
  EXPECT_TRUE(rc.IsOk());
  rc = zip_op->AddChild(std::move(my_tfreader_op));
  EXPECT_TRUE(rc.IsOk());
  rc = zip_op->AddChild(std::move(my_tfreader_op2));
  EXPECT_TRUE(rc.IsOk());
  rc = my_tree->AssignRoot(zip_op);
  EXPECT_TRUE(rc.IsOk());
  rc = my_tree->Prepare();
  EXPECT_TRUE(rc.IsOk());

  // Launch the tree execution to kick off threads and start running the pipeline
  MS_LOG(INFO) << "Launching my tree.";
  rc = my_tree->Launch();
  EXPECT_TRUE(rc.IsOk());

  // Simulate a parse of data from our pipeline.
  std::shared_ptr<DatasetOp> rootNode = my_tree->root();

  DatasetIterator di(my_tree);
  TensorRow tensor_list;
  rc = di.FetchNextTensorRow(&tensor_list);
  EXPECT_TRUE(rc.IsOk());

  int row_count = 0;
  while (!tensor_list.empty()) {
    MS_LOG(INFO) << "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(INFO) << "Tensor print: " << common::SafeCStr(ss.str()) << ".";
    }
    rc = di.FetchNextTensorRow(&tensor_list);
    EXPECT_TRUE(rc.IsOk());
    row_count++;
  }
  ASSERT_EQ(row_count, 3);  // Should be 3 rows fetched
}

TEST_F(MindDataTestZipOp, MindDataTestZipOpRepeat) {
  /* Tree:
   *                  OpId(3) Repeat(3)
   *
   *                  OpId(2) ZipOp
   *            /                       \
   *         OpId(0) TFReaderOp    OpId(1) TFReaderOp
   *
   * Start with an empty execution tree
   */
  Status rc;
  MS_LOG(INFO) << "UT test TestZipRepeat.";
  auto my_tree = std::make_shared<ExecutionTree>();

  uint32_t num_repeats = 3;
  std::string dataset_path = datasets_root_path_ + "/test_tf_file_3_images/train-0000-of-0001.data";
  std::string dataset_path2 = datasets_root_path_ + "/testBatchDataset/test.data";
  std::shared_ptr<ConfigManager> config_manager = GlobalContext::config_manager();
  auto op_connector_size = config_manager->op_connector_size();
  std::vector<std::string> columns_to_load = {};
  std::vector<std::string> files1 = {dataset_path};
  std::unique_ptr<DataSchema> schema1 = std::make_unique<DataSchema>();
  std::shared_ptr<TFReaderOp> my_tfreader_op = std::make_shared<TFReaderOp>(
    1, 16, 0, files1, std::move(schema1), op_connector_size, columns_to_load, false, 1, 0, false);
  rc = my_tfreader_op->Init();
  EXPECT_TRUE(rc.IsOk());

  rc = my_tree->AssociateNode(my_tfreader_op);

  rc = my_tree->AssociateNode(my_tfreader_op);
  EXPECT_TRUE(rc.IsOk());
  std::vector<std::string> files2 = {dataset_path2};
  std::unique_ptr<DataSchema> schema2 = std::make_unique<DataSchema>();
  std::shared_ptr<TFReaderOp> my_tfreader_op2 = std::make_shared<TFReaderOp>(
    1, 1, 0, files2, std::move(schema2), op_connector_size, columns_to_load, false, 1, 0, false);
  rc = my_tfreader_op2->Init();
  EXPECT_TRUE(rc.IsOk());

  rc = my_tree->AssociateNode(my_tfreader_op2);
  EXPECT_TRUE(rc.IsOk());
  // Creating DatasetOp
  std::shared_ptr<ZipOp> zip_op = std::make_shared<ZipOp>();
  rc = my_tree->AssociateNode(zip_op);
  EXPECT_TRUE(rc.IsOk());
  my_tfreader_op->SetTotalRepeats(num_repeats);
  my_tfreader_op->SetNumRepeatsPerEpoch(num_repeats);
  rc = zip_op->AddChild(std::move(my_tfreader_op));
  EXPECT_TRUE(rc.IsOk());
  my_tfreader_op2->SetTotalRepeats(num_repeats);
  my_tfreader_op2->SetNumRepeatsPerEpoch(num_repeats);
  rc = zip_op->AddChild(std::move(my_tfreader_op2));
  EXPECT_TRUE(rc.IsOk());

  std::shared_ptr<RepeatOp> my_repeat_op = std::make_shared<RepeatOp>(num_repeats);
  rc = my_tree->AssociateNode(my_repeat_op);
  EXPECT_TRUE(rc.IsOk());
  zip_op->SetTotalRepeats(num_repeats);
  zip_op->SetNumRepeatsPerEpoch(num_repeats);
  rc = my_repeat_op->AddChild(zip_op);
  EXPECT_TRUE(rc.IsOk());
  rc = my_tree->AssignRoot(my_repeat_op);
  EXPECT_TRUE(rc.IsOk());
  rc = my_tree->Prepare();
  EXPECT_TRUE(rc.IsOk());

  // Launch the tree execution to kick off threads and start running the pipeline
  MS_LOG(INFO) << "Launching my tree.";
  rc = my_tree->Launch();
  EXPECT_TRUE(rc.IsOk());

  // Simulate a parse of data from our pipeline.
  std::shared_ptr<DatasetOp> rootNode = my_tree->root();

  DatasetIterator di(my_tree);
  TensorRow tensor_list;
  rc = di.FetchNextTensorRow(&tensor_list);
  EXPECT_TRUE(rc.IsOk());

  int row_count = 0;
  while (!tensor_list.empty()) {
    MS_LOG(INFO) << "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(INFO) << "Tensor print: " << common::SafeCStr(ss.str()) << ".";
    }
    rc = di.FetchNextTensorRow(&tensor_list);
    EXPECT_TRUE(rc.IsOk());
    row_count++;
  }
  ASSERT_EQ(row_count, 9);  // Should be 9 rows fetched
}