forked from mindspore-Ecosystem/mindspore
134 lines
5.3 KiB
C++
134 lines
5.3 KiB
C++
/**
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* Copyright 2019 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include <fstream>
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#include <iostream>
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#include <memory>
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#include <string>
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#include "common/utils.h"
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#include "common/common.h"
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#include "minddata/dataset/core/client.h"
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#include "minddata/dataset/core/global_context.h"
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#include "minddata/dataset/engine/datasetops/source/mnist_op.h"
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#include "minddata/dataset/engine/datasetops/source/sampler/distributed_sampler.h"
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#include "minddata/dataset/engine/datasetops/source/sampler/pk_sampler.h"
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#include "minddata/dataset/engine/datasetops/source/sampler/random_sampler.h"
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#include "minddata/dataset/engine/datasetops/source/sampler/sampler.h"
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#include "minddata/dataset/engine/datasetops/source/sampler/sequential_sampler.h"
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#include "minddata/dataset/engine/datasetops/source/sampler/subset_random_sampler.h"
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#include "minddata/dataset/engine/datasetops/source/sampler/weighted_random_sampler.h"
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#include "minddata/dataset/util/path.h"
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#include "minddata/dataset/util/status.h"
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#include "gtest/gtest.h"
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#include "utils/log_adapter.h"
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#include "securec.h"
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namespace common = mindspore::common;
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using namespace mindspore::dataset;
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using mindspore::MsLogLevel::ERROR;
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using mindspore::ExceptionType::NoExceptionType;
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using mindspore::LogStream;
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std::shared_ptr<BatchOp> Batch(int batch_size = 1, bool drop = false, int rows_per_buf = 2);
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std::shared_ptr<RepeatOp> Repeat(int repeat_cnt);
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std::shared_ptr<ExecutionTree> Build(std::vector<std::shared_ptr<DatasetOp>> ops);
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Status Create1DTensor(std::shared_ptr<Tensor> *sample_ids, int64_t num_elements, unsigned char *data = nullptr,
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DataType::Type data_type = DataType::DE_UINT32);
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std::shared_ptr<MnistOp> CreateMnist(int64_t num_wrks, int64_t rows, int64_t conns, std::string path,
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bool shuf = false, std::shared_ptr<Sampler> sampler = nullptr) {
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std::shared_ptr<MnistOp> so;
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MnistOp::Builder builder;
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Status rc = builder.SetNumWorkers(num_wrks).SetDir(path).SetRowsPerBuffer(rows)
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.SetOpConnectorSize(conns).SetSampler(std::move(sampler)).Build(&so);
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return so;
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}
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class MindDataTestMnistSampler : public UT::DatasetOpTesting {
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protected:
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};
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TEST_F(MindDataTestMnistSampler, TestSequentialMnistWithRepeat) {
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// Note: Mnist datasets are not included
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// as part of the build tree.
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// Download datasets and rebuild if data doesn't
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// appear in this dataset
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// Example: python tests/dataset/data/prep_data.py
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std::string folder_path = datasets_root_path_ + "/testMnistData/";
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int64_t num_samples = 10;
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int64_t start_index = 0;
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auto seq_sampler = std::make_shared<SequentialSampler>(num_samples, start_index);
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auto tree = Build({CreateMnist(16, 2, 32, folder_path, false, std::move(seq_sampler)), Repeat(2)});
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tree->Prepare();
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uint32_t res[] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0};
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Status rc = tree->Launch();
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if (rc.IsError()) {
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MS_LOG(ERROR) << "Return code error detected during tree launch: " << rc.ToString() << ".";
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EXPECT_TRUE(false);
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} else {
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DatasetIterator di(tree);
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TensorMap tensor_map;
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di.GetNextAsMap(&tensor_map);
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EXPECT_TRUE(rc.IsOk());
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uint64_t i = 0;
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uint32_t label = 0;
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while (tensor_map.size() != 0) {
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tensor_map["label"]->GetItemAt<uint32_t>(&label, {});
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EXPECT_TRUE(res[i % 10] == label);
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MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "\n";
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i++;
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di.GetNextAsMap(&tensor_map);
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}
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EXPECT_TRUE(i == 20);
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}
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}
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TEST_F(MindDataTestMnistSampler, TestSequentialImageFolderWithRepeatBatch) {
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std::string folder_path = datasets_root_path_ + "/testMnistData/";
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int64_t num_samples = 10;
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int64_t start_index = 0;
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auto seq_sampler = std::make_shared<SequentialSampler>(num_samples, start_index);
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auto tree = Build({CreateMnist(16, 2, 32, folder_path, false, std::move(seq_sampler)), Repeat(2), Batch(5)});
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tree->Prepare();
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uint32_t res[4][5] = { {0, 0, 0, 0, 0 },
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{0, 0, 0, 0, 0 },
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{0, 0, 0, 0, 0 },
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{0, 0, 0, 0, 0 } };
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Status rc = tree->Launch();
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if (rc.IsError()) {
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MS_LOG(ERROR) << "Return code error detected during tree launch: " << rc.ToString() << ".";
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EXPECT_TRUE(false);
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} else {
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DatasetIterator di(tree);
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TensorMap tensor_map;
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di.GetNextAsMap(&tensor_map);
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EXPECT_TRUE(rc.IsOk());
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uint64_t i = 0;
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while (tensor_map.size() != 0) {
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std::shared_ptr<Tensor> label;
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Create1DTensor(&label, 5, reinterpret_cast<unsigned char *>(res[i % 4]));
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EXPECT_TRUE((*label) == (*tensor_map["label"]));
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MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << *tensor_map["label"] << "\n";
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i++;
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di.GetNextAsMap(&tensor_map);
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}
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EXPECT_TRUE(i == 4);
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}
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}
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