mindspore2022/tests/ut/cpp/dataset/mnist_op_test.cc

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

#include "utils/ms_utils.h"
#include "common/common.h"
#include "minddata/dataset/core/client.h"
#include "minddata/dataset/core/global_context.h"
#include "minddata/dataset/engine/datasetops/source/mnist_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/include/dataset/datasets.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::LogStream;
using mindspore::ExceptionType::NoExceptionType;
using mindspore::MsLogLevel::ERROR;

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

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

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

TEST_F(MindDataTestMnistSampler, TestSequentialMnistWithRepeat) {
  std::string folder_path = datasets_root_path_ + "/testMnistData/";
  int64_t num_samples = 10;
  int64_t start_index = 0;
  std::shared_ptr<Dataset> ds =
    Mnist(folder_path, "all", std::make_shared<SequentialSampler>(start_index, num_samples));
  EXPECT_NE(ds, nullptr);
  ds = ds->Repeat(2);
  EXPECT_NE(ds, nullptr);
  std::shared_ptr<Iterator> iter = ds->CreateIterator();
  EXPECT_NE(iter, nullptr);
  uint32_t res[] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0};
  std::unordered_map<std::string, mindspore::MSTensor> row;
  ASSERT_OK(iter->GetNextRow(&row));
  uint32_t label_idx;
  uint64_t i = 0;
  while (row.size() != 0) {
    auto image = row["image"];
    auto label = row["label"];
    MS_LOG(INFO) << "Tensor image shape: " << image.Shape();
    std::shared_ptr<Tensor> de_label;
    ASSERT_OK(Tensor::CreateFromMSTensor(label, &de_label));
    ASSERT_OK(de_label->GetItemAt<uint32_t>(&label_idx, {}));
    MS_LOG(INFO) << "Tensor label value: " << label_idx;
    EXPECT_EQ(label_idx, res[i % 10]);
    ASSERT_OK(iter->GetNextRow(&row));
    i++;
  }

  EXPECT_EQ(i, 20);
  iter->Stop();
}

TEST_F(MindDataTestMnistSampler, TestSequentialImageFolderWithRepeatBatch) {
  std::string folder_path = datasets_root_path_ + "/testMnistData/";
  int64_t num_samples = 10;
  int64_t start_index = 0;
  std::shared_ptr<Dataset> ds =
    Mnist(folder_path, "all", std::make_shared<SequentialSampler>(start_index, num_samples));
  EXPECT_NE(ds, nullptr);
  ds = ds->Repeat(2);
  EXPECT_NE(ds, nullptr);
  ds = ds->Batch(5);
  EXPECT_NE(ds, nullptr);
  std::shared_ptr<Iterator> iter = ds->CreateIterator();
  EXPECT_NE(iter, nullptr);
  std::vector<std::vector<uint32_t>> expected = {{0, 0, 0, 0, 0}, {0, 0, 0, 0, 0}, {0, 0, 0, 0, 0}, {0, 0, 0, 0, 0}};
  std::unordered_map<std::string, mindspore::MSTensor> row;
  ASSERT_OK(iter->GetNextRow(&row));
  uint64_t i = 0;
  while (row.size() != 0) {
    auto image = row["image"];
    auto label = row["label"];
    MS_LOG(INFO) << "Tensor image shape: " << image.Shape();
    TEST_MS_LOG_MSTENSOR(INFO, "Tensor label: ", label);
    std::shared_ptr<Tensor> de_expected_label;
    ASSERT_OK(Tensor::CreateFromVector(expected[i % 4], &de_expected_label));
    mindspore::MSTensor expected_label =
      mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_label));
    EXPECT_MSTENSOR_EQ(label, expected_label);
    ASSERT_OK(iter->GetNextRow(&row));
    i++;
  }
  EXPECT_EQ(i, 4);
  iter->Stop();
}