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124 lines
3.8 KiB
124 lines
3.8 KiB
/**
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* Copyright 2020 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 "common/common.h"
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#include "gtest/gtest.h"
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#include "minddata/dataset/core/constants.h"
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#include "minddata/dataset/core/tensor.h"
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#include "minddata/dataset/engine/data_buffer.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/distributed_sampler.h"
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#include "utils/log_adapter.h"
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#include <vector>
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#include <unordered_set>
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using namespace mindspore::dataset;
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using mindspore::MsLogLevel::INFO;
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using mindspore::ExceptionType::NoExceptionType;
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using mindspore::LogStream;
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class MindDataTestDistributedSampler : public UT::Common {
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public:
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class DummyRandomAccessOp : public RandomAccessOp {
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public:
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DummyRandomAccessOp(uint64_t num_rows) {
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// row count is in base class as protected member
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// GetNumRowsInDataset does not need an override, the default from base class is fine.
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num_rows_ = num_rows;
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}
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};
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};
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TEST_F(MindDataTestDistributedSampler, TestTwoShardsOne) {
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// num samples to draw.
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uint64_t num_samples = 7;
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// create sampler with replacement = true
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DistributedSamplerRT m_sampler(num_samples, 2, 0, false, 0, -1, false);
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DummyRandomAccessOp dummyRandomAccessOp(num_samples);
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m_sampler.HandshakeRandomAccessOp(&dummyRandomAccessOp);
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std::unique_ptr<DataBuffer> db;
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TensorRow row;
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std::vector<uint64_t> out;
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ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
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db->PopRow(&row);
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for (const auto &t : row) {
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for (auto it = t->begin<uint64_t>(); it != t->end<uint64_t>(); it++) {
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out.push_back(*it);
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}
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}
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ASSERT_EQ(4, out.size());
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ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
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ASSERT_EQ(db->eoe(), true);
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}
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TEST_F(MindDataTestDistributedSampler, TestTwoShardsTwo) {
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// num samples to draw.
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uint64_t num_samples = 7;
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// create sampler with replacement = true
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DistributedSamplerRT m_sampler(num_samples, 2, 1, false, 0, -1, false);
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DummyRandomAccessOp dummyRandomAccessOp(num_samples);
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m_sampler.HandshakeRandomAccessOp(&dummyRandomAccessOp);
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std::unique_ptr<DataBuffer> db;
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TensorRow row;
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std::vector<uint64_t> out;
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ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
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db->PopRow(&row);
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for (const auto &t : row) {
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for (auto it = t->begin<uint64_t>(); it != t->end<uint64_t>(); it++) {
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out.push_back(*it);
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}
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}
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ASSERT_EQ(3, out.size());
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ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
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ASSERT_EQ(db->eoe(), true);
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}
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TEST_F(MindDataTestDistributedSampler, TestThreeShards) {
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// num samples to draw.
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uint64_t num_samples = 2;
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// create sampler with replacement = true
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DistributedSamplerRT m_sampler(num_samples, 3, 2, false, 0, -1, false);
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DummyRandomAccessOp dummyRandomAccessOp(num_samples);
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m_sampler.HandshakeRandomAccessOp(&dummyRandomAccessOp);
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std::unique_ptr<DataBuffer> db;
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TensorRow row;
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std::vector<uint64_t> out;
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ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
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db->PopRow(&row);
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for (const auto &t : row) {
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for (auto it = t->begin<uint64_t>(); it != t->end<uint64_t>(); it++) {
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out.push_back(*it);
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}
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}
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ASSERT_EQ(0, out.size());
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ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
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ASSERT_EQ(db->eoe(), true);
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}
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