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- /**
- * 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/utils.h"
- #include "common/common.h"
- #include "dataset/core/client.h"
- #include "dataset/core/global_context.h"
- #include "dataset/engine/datasetops/source/mnist_op.h"
- #include "dataset/engine/datasetops/source/sampler/distributed_sampler.h"
- #include "dataset/engine/datasetops/source/sampler/pk_sampler.h"
- #include "dataset/engine/datasetops/source/sampler/random_sampler.h"
- #include "dataset/engine/datasetops/source/sampler/sampler.h"
- #include "dataset/engine/datasetops/source/sampler/sequential_sampler.h"
- #include "dataset/engine/datasetops/source/sampler/subset_random_sampler.h"
- #include "dataset/engine/datasetops/source/sampler/weighted_random_sampler.h"
- #include "dataset/util/de_error.h"
- #include "dataset/util/path.h"
- #include "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);
-
- Status Create1DTensor(std::shared_ptr<Tensor> *sample_ids, int64_t num_elements, unsigned char *data = nullptr,
- DataType::Type data_type = DataType::DE_UINT32);
-
- std::shared_ptr<MnistOp> CreateMnist(int64_t num_wrks, int64_t rows, int64_t conns, std::string path,
- bool shuf = false, std::unique_ptr<Sampler> sampler = nullptr,
- int64_t num_samples = 0) {
- std::shared_ptr<MnistOp> so;
- MnistOp::Builder builder;
- Status rc = builder.SetNumWorkers(num_wrks).SetDir(path).SetRowsPerBuffer(rows)
- .SetOpConnectorSize(conns).SetSampler(std::move(sampler))
- .SetNumSamples(num_samples).Build(&so);
- return so;
- }
-
- class MindDataTestMnistSampler : public UT::DatasetOpTesting {
- protected:
- };
-
- TEST_F(MindDataTestMnistSampler, TestSequentialMnistWithRepeat) {
- // Note: Mnist datasets are not included
- // as part of the build tree.
- // Download datasets and rebuild if data doesn't
- // appear in this dataset
- // Example: python tests/dataset/data/prep_data.py
- std::string folder_path = datasets_root_path_ + "/testMnistData/";
- auto tree = Build({CreateMnist(16, 2, 32, folder_path, false, nullptr, 10), Repeat(2)});
- tree->Prepare();
- uint32_t res[] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0};
- Status rc = tree->Launch();
- if (rc.IsError()) {
- MS_LOG(ERROR) << "Return code error detected during tree launch: " << rc.ToString() << ".";
- EXPECT_TRUE(false);
- } else {
- DatasetIterator di(tree);
- TensorMap tensor_map;
- di.GetNextAsMap(&tensor_map);
- EXPECT_TRUE(rc.IsOk());
- uint64_t i = 0;
- uint32_t label = 0;
- while (tensor_map.size() != 0) {
- tensor_map["label"]->GetItemAt<uint32_t>(&label, {});
- EXPECT_TRUE(res[i % 10] == label);
- MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "\n";
- i++;
- di.GetNextAsMap(&tensor_map);
- }
- EXPECT_TRUE(i == 20);
- }
- }
-
- TEST_F(MindDataTestMnistSampler, TestSequentialImageFolderWithRepeatBatch) {
- std::string folder_path = datasets_root_path_ + "/testMnistData/";
- auto tree = Build({CreateMnist(16, 2, 32, folder_path, false, nullptr, 10), Repeat(2), Batch(5)});
- tree->Prepare();
- uint32_t res[4][5] = { {0, 0, 0, 0, 0 },
- {0, 0, 0, 0, 0 },
- {0, 0, 0, 0, 0 },
- {0, 0, 0, 0, 0 } };
- Status rc = tree->Launch();
- if (rc.IsError()) {
- MS_LOG(ERROR) << "Return code error detected during tree launch: " << rc.ToString() << ".";
- EXPECT_TRUE(false);
- } else {
- DatasetIterator di(tree);
- TensorMap tensor_map;
- di.GetNextAsMap(&tensor_map);
- EXPECT_TRUE(rc.IsOk());
- uint64_t i = 0;
- while (tensor_map.size() != 0) {
- std::shared_ptr<Tensor> label;
- Create1DTensor(&label, 5, reinterpret_cast<unsigned char *>(res[i % 4]));
- EXPECT_TRUE((*label) == (*tensor_map["label"]));
- MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << *tensor_map["label"] << "\n";
- i++;
- di.GetNextAsMap(&tensor_map);
- }
- EXPECT_TRUE(i == 4);
- }
- }
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