1 /**
2 * Copyright 2019 Huawei Technologies Co., Ltd
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16
17 #include "common/common.h"
18 #include "minddata/dataset/core/client.h"
19 #include "minddata/dataset/core/global_context.h"
20 #include "minddata/dataset/engine/datasetops/source/sampler/distributed_sampler.h"
21 #include "minddata/dataset/engine/datasetops/source/sampler/random_sampler.h"
22 #include "minddata/dataset/engine/datasetops/source/sampler/sampler.h"
23 #include "minddata/dataset/engine/datasetops/source/sampler/sequential_sampler.h"
24 #include "minddata/dataset/util/status.h"
25 #include "gtest/gtest.h"
26 #include "utils/log_adapter.h"
27 #include "securec.h"
28
29 using namespace mindspore::dataset;
30
CreateINT64Tensor(std::shared_ptr<Tensor> * sample_ids,int64_t num_elements,unsigned char * data=nullptr)31 Status CreateINT64Tensor(std::shared_ptr<Tensor> *sample_ids, int64_t num_elements, unsigned char *data = nullptr) {
32 TensorShape shape(std::vector<int64_t>(1, num_elements));
33 RETURN_IF_NOT_OK(Tensor::CreateFromMemory(shape, DataType(DataType::DE_INT64), data, sample_ids));
34
35 return Status::OK();
36 }
37
38 class MindDataTestStandAloneSampler : public UT::DatasetOpTesting {
39 protected:
40 class MockStorageOp : public RandomAccessOp {
41 public:
MockStorageOp(int64_t val)42 MockStorageOp(int64_t val) {
43 // row count is in base class as protected member
44 // GetNumRowsInDataset does not need an override, the default from base class is fine.
45 num_rows_ = val;
46 }
47 };
48 };
49
TEST_F(MindDataTestStandAloneSampler,TestDistributedSampler)50 TEST_F(MindDataTestStandAloneSampler, TestDistributedSampler) {
51 std::vector<std::shared_ptr<Tensor>> row;
52 uint64_t res[6][7] = {{0, 3, 6, 9, 12, 15, 18}, {1, 4, 7, 10, 13, 16, 19}, {2, 5, 8, 11, 14, 17, 0},
53 {0, 17, 4, 10, 14, 8, 15}, {13, 9, 16, 3, 2, 19, 12}, {1, 11, 6, 18, 7, 5, 0}};
54 for (int i = 0; i < 6; i++) {
55 std::shared_ptr<Tensor> t;
56 Tensor::CreateFromMemory(TensorShape({7}), DataType(DataType::DE_INT64), (unsigned char *)(res[i]), &t);
57 row.push_back(t);
58 }
59 MockStorageOp mock(20);
60 std::shared_ptr<Tensor> tensor;
61 int64_t num_samples = 0;
62 TensorRow sample_row;
63 for (int i = 0; i < 6; i++) {
64 std::shared_ptr<SamplerRT> sampler =
65 std::make_shared<DistributedSamplerRT>(3, i % 3, (i < 3 ? false : true), num_samples);
66 sampler->HandshakeRandomAccessOp(&mock);
67 sampler->GetNextSample(&sample_row);
68 tensor = sample_row[0];
69 MS_LOG(DEBUG) << (*tensor);
70 if (i < 3) { // This is added due to std::shuffle()
71 EXPECT_TRUE((*tensor) == (*row[i]));
72 }
73 }
74 }
75
TEST_F(MindDataTestStandAloneSampler,TestStandAoneSequentialSampler)76 TEST_F(MindDataTestStandAloneSampler, TestStandAoneSequentialSampler) {
77 std::vector<std::shared_ptr<Tensor>> row;
78 MockStorageOp mock(5);
79 uint64_t res[5] = {0, 1, 2, 3, 4};
80 std::shared_ptr<Tensor> label1, label2;
81 CreateINT64Tensor(&label1, 3, reinterpret_cast<unsigned char *>(res));
82 CreateINT64Tensor(&label2, 2, reinterpret_cast<unsigned char *>(res + 3));
83 int64_t num_samples = 0;
84 int64_t start_index = 0;
85 std::shared_ptr<SamplerRT> sampler = std::make_shared<SequentialSamplerRT>(start_index, num_samples, 3);
86
87 std::shared_ptr<Tensor> tensor;
88 TensorRow sample_row;
89 sampler->HandshakeRandomAccessOp(&mock);
90 sampler->GetNextSample(&sample_row);
91 tensor = sample_row[0];
92 EXPECT_TRUE((*tensor) == (*label1));
93 sampler->GetNextSample(&sample_row);
94 tensor = sample_row[0];
95 EXPECT_TRUE((*tensor) == (*label2));
96 sampler->ResetSampler();
97 sampler->GetNextSample(&sample_row);
98 tensor = sample_row[0];
99 EXPECT_TRUE((*tensor) == (*label1));
100 sampler->GetNextSample(&sample_row);
101 tensor = sample_row[0];
102 EXPECT_TRUE((*tensor) == (*label2));
103 }
104