[IE][VPU]: Enable new tests for adjust_data_batch pass (#1219)
* New tests for adjust_data_batch pass
This commit is contained in:
Daria Mityagina
GitHub
parent
00630127e7
commit
e38106239c
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// Copyright (C) 2020 Intel Corporation
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// SPDX-License-Identifier: Apache-2.0
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//
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#include <vpu/stages/mx_stage.hpp>
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#include <vpu/utils/numeric.hpp>
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#include "graph_transformer_tests.hpp"
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using namespace vpu;
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class VPU_AdjustDataBatchTest : public GraphTransformerTest {
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protected:
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const int batchSize = 4;
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TestModel testModel;
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public:
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void SetUp() override {
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ASSERT_NO_FATAL_FAILURE(GraphTransformerTest::SetUp());
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ASSERT_NO_FATAL_FAILURE(InitCompileEnv());
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testModel = CreateTestModel();
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}
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void RunPass() {
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PassSet pipeline;
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pipeline.addPass(passManager->dumpModel("initial"));
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pipeline.addPass(passManager->adjustDataBatch());
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pipeline.addPass(passManager->dumpModel("adjustDataBatch"));
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pipeline.run(testModel.getBaseModel());
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}
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DataVector checkSingleLoopStart(const Data& data) {
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EXPECT_EQ(data->desc().dim(Dim::N), 4);
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EXPECT_EQ(data->numConsumers(), 2);
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DataVector outputs;
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for (const auto& consumer : data->consumers()) {
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EXPECT_TRUE(consumer->type() == StageType::LoopStart || consumer->type() == StageType::LoopEnd);
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if (consumer->type() == StageType::LoopStart) {
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for (const auto& output : consumer->outputs()) {
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EXPECT_EQ(output->desc().dim(Dim::N), 1);
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outputs.push_back(output);
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}
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}
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}
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return outputs;
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}
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DataVector checkBranches(const Data& root, const std::vector<StageType>& consumersTypes) {
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auto successors = DataVector{};
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const auto& consumers = root->consumers() | asVector();
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EXPECT_EQ(consumers.size(), consumersTypes.size());
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for (std::size_t i = 0; i < consumers.size(); ++i) {
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const auto& consumer = consumers[i];
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const auto& expected = consumersTypes[i];
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EXPECT_EQ(consumer->type(), expected);
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EXPECT_EQ(consumer->numOutputs(), 1);
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const auto& output = consumer->output(0);
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successors.push_back(output);
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if (expected == StageType::LoopStart) {
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EXPECT_EQ(consumer->numOutputs(), 1);
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EXPECT_EQ(output->desc().dim(Dim::N), 1);
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} else if (expected == StageType::LoopEnd) {
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EXPECT_EQ(output->desc().dim(Dim::N), 4);
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}
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}
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return successors;
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}
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DataVector checkSingleLoopEnd(const Data& data) {
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EXPECT_EQ(data->numConsumers(), 1);
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const auto& consumer = data->singleConsumer();
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EXPECT_EQ(consumer->type(), StageType::LoopEnd);
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DataVector outputs;
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for (const auto& output : consumer->outputs()) {
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EXPECT_EQ(output->desc().dim(Dim::N), 4);
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outputs.push_back(output);
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}
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return outputs;
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}
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static Data CheckSingleConnection(const Data& data, int testInd, int batch = 1) {
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EXPECT_EQ(data->numConsumers(), 1);
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const auto& consumer = data->singleConsumer();
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EXPECT_EQ(consumer->type(), StageType::None);
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EXPECT_EQ(consumer->attrs().get<int>("test_ind"), testInd);
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EXPECT_EQ(consumer->numOutputs(), 1);
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const auto& output = consumer->output(0);
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EXPECT_EQ(output->desc().dim(Dim::N), batch);
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return output;
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}
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static Data singleElement(const DataVector& dataObjects) {
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EXPECT_EQ(dataObjects.size(), 1);
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return dataObjects.front();
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}
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};
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TEST_F(VPU_AdjustDataBatchTest, LinearWithBatchedInTheEnd) {
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//
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// [Input] -> (Split) -> (Split) -> (Split) -> (Split) -> (Split) -> (Split) -> (Batched) -> [Output]
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//
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const DataDesc desc{16, 16, 3, batchSize};
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testModel.createInputs({desc});
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testModel.createOutputs({desc});
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for (int i = 0; i < 6; i++) {
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if (i > 0)
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testModel.addStage({InputInfo::fromPrevStage(i - 1)}, {OutputInfo::intermediate(desc)});
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else
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testModel.addStage({InputInfo::fromNetwork()}, {OutputInfo::intermediate(desc)});
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testModel.setStageBatchInfo(i, {{0, BatchSupport::Split}});
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}
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testModel.addStage({InputInfo::fromPrevStage(5)}, {OutputInfo::fromNetwork(0)});
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RunPass();
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const auto& data0 = singleElement(checkSingleLoopStart(testModel.getInputs().at(0)));
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const auto& data1 = CheckSingleConnection(data0, 0);
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const auto& data2 = CheckSingleConnection(data1, 1);
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const auto& data3 = CheckSingleConnection(data2, 2);
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const auto& data4 = CheckSingleConnection(data3, 3);
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const auto& data5 = CheckSingleConnection(data4, 4);
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const auto& data6 = CheckSingleConnection(data5, 5);
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const auto& data7 = singleElement(checkSingleLoopEnd(data6));
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const auto& data8 = CheckSingleConnection(data7, 6, batchSize);
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ASSERT_EQ(data8, testModel.getOutputs().at(0));
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}
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TEST_F(VPU_AdjustDataBatchTest, BranchedWithBatchSplitItems) {
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// -> (Batched) -> [Output]
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// [Input] -> (Split) -> (Split) -> (Split) -> (Split) -> (Split) -> (Split) -> (Split)
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// -> (Batched) -> [Output]
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const DataDesc desc{16, 16, 3, batchSize};
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testModel.createInputs({desc});
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testModel.createOutputs({desc, desc});
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for (int i = 0; i < 7; i++) {
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if (i > 0)
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testModel.addStage({InputInfo::fromPrevStage(i - 1)}, {OutputInfo::intermediate(desc)});
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else
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testModel.addStage({InputInfo::fromNetwork()}, {OutputInfo::intermediate(desc)});
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testModel.setStageBatchInfo(i, {{0, BatchSupport::Split}});
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}
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testModel.addStage({InputInfo::fromPrevStage(6)}, {OutputInfo::fromNetwork(0)});
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testModel.addStage({InputInfo::fromPrevStage(6)}, {OutputInfo::fromNetwork(1)});
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RunPass();
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const auto& data0 = singleElement(checkSingleLoopStart(testModel.getInputs().at(0)));
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const auto& data1 = CheckSingleConnection(data0, 0);
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const auto& data2 = CheckSingleConnection(data1, 1);
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const auto& data3 = CheckSingleConnection(data2, 2);
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const auto& data4 = CheckSingleConnection(data3, 3);
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const auto& data5 = CheckSingleConnection(data4, 4);
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const auto& data6 = CheckSingleConnection(data5, 5);
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const auto& data7 = CheckSingleConnection(data6, 6);
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const auto& data8 = singleElement(checkSingleLoopEnd(data7));
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const auto& branches = checkBranches(data8, {StageType::None, StageType::None});
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const auto& withBatch = branches[0];
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const auto& withBatch_1 = branches[1];
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ASSERT_EQ(withBatch->producer()->attrs().get<int>("test_ind"), 7);
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ASSERT_EQ(withBatch->desc().dim(Dim::N), batchSize);
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ASSERT_EQ(withBatch, testModel.getOutputs().at(0));
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ASSERT_EQ(withBatch_1->producer()->attrs().get<int>("test_ind"), 8);
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ASSERT_EQ(withBatch_1->desc().dim(Dim::N), batchSize);
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ASSERT_EQ(withBatch_1, testModel.getOutputs().at(1));
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}
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TEST_F(VPU_AdjustDataBatchTest, LinearWithBatchedInTheBeginning) {
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//
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// [Input] -> (Batched) -> (Split) -> (Split) -> (Split) -> (Split) -> (Split) -> (Split) -> [Output]
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//
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const DataDesc desc{16, 16, 3, batchSize};
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testModel.createInputs({desc});
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testModel.createOutputs({desc});
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for (int i = 0; i < 6; i++) {
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if (i > 0)
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testModel.addStage({InputInfo::fromPrevStage(i - 1)}, {OutputInfo::intermediate(desc)});
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else
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testModel.addStage({InputInfo::fromNetwork()}, {OutputInfo::intermediate(desc)});
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if (i > 0)
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testModel.setStageBatchInfo(i, {{0, BatchSupport::Split}});
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}
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testModel.addStage({InputInfo::fromPrevStage(5)}, {OutputInfo::fromNetwork()});
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testModel.setStageBatchInfo(6, {{0, BatchSupport::Split}});
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RunPass();
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const auto& data0 = CheckSingleConnection(testModel.getInputs().at(0), 0, batchSize);
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const auto& data7 = singleElement(checkSingleLoopStart(data0));
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const auto& data3 = CheckSingleConnection(data7, 1);
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const auto& data4 = CheckSingleConnection(data3, 2);
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const auto& data5 = CheckSingleConnection(data4, 3);
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const auto& data6 = CheckSingleConnection(data5, 4);
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const auto& data8 = CheckSingleConnection(data6, 5);
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const auto& data10 = CheckSingleConnection(data8, 6);
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const auto& data11 = checkSingleLoopEnd(data10);
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ASSERT_EQ(data11, testModel.getOutputs());
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}
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TEST_F(VPU_AdjustDataBatchTest, BranchedWithBatchItemsInTheEnd) {
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// -> (Batched) -> [Output]
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// [Input] -> (Split) -> (Split) -> (Split) -> (Split) -> (Split) -> (Split) -> (Batch)
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// -> (Batched) -> [Output]
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const DataDesc desc{16, 16, 3, batchSize};
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testModel.createInputs({desc});
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testModel.createOutputs({desc, desc});
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for (int i = 0; i < 6; i++) {
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if (i > 0)
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testModel.addStage({InputInfo::fromPrevStage(i - 1)}, {OutputInfo::intermediate(desc)});
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else
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testModel.addStage({InputInfo::fromNetwork()}, {OutputInfo::intermediate(desc)});
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testModel.setStageBatchInfo(i, {{0, BatchSupport::Split}});
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}
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testModel.addStage({InputInfo::fromPrevStage(5)}, {OutputInfo::intermediate(desc)});
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testModel.addStage({InputInfo::fromPrevStage(6)}, {OutputInfo::fromNetwork(0)});
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testModel.addStage({InputInfo::fromPrevStage(6)}, {OutputInfo::fromNetwork(1)});
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RunPass();
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const auto& data0 = singleElement(checkSingleLoopStart(testModel.getInputs().at(0)));
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const auto& data1 = CheckSingleConnection(data0, 0);
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const auto& data2 = CheckSingleConnection(data1, 1);
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const auto& data3 = CheckSingleConnection(data2, 2);
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const auto& data4 = CheckSingleConnection(data3, 3);
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const auto& data5 = CheckSingleConnection(data4, 4);
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const auto& data6 = CheckSingleConnection(data5, 5);
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const auto& data7 = singleElement(checkSingleLoopEnd(data6));
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const auto& data8 = CheckSingleConnection(data7, 6, batchSize);
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const auto& branches = checkBranches(data8, {StageType::None, StageType::None});
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const auto& withBatch = branches[0];
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const auto& withBatch_1 = branches[1];
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ASSERT_EQ(withBatch->producer()->attrs().get<int>("test_ind"), 7);
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ASSERT_EQ(withBatch->desc().dim(Dim::N), batchSize);
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ASSERT_EQ(withBatch, testModel.getOutputs().at(0));
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ASSERT_EQ(withBatch_1->producer()->attrs().get<int>("test_ind"), 8);
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ASSERT_EQ(withBatch_1->desc().dim(Dim::N), batchSize);
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ASSERT_EQ(withBatch_1, testModel.getOutputs().at(1));
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}
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TEST_F(VPU_AdjustDataBatchTest, DISABLED_BranchedWithSplitAndBatchItemsInTheEnd) {
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//
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// -> (Split) -> (Batched) -> [Output]
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// [Input] -> (Split) -> (Split) -> (Split)
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// -> (Split) -> [Output]
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//
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const DataDesc desc{16, 16, 3, batchSize};
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testModel.createInputs({desc});
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testModel.createOutputs({desc, desc});
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for (int i = 0; i < 5; i++) {
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if (i > 0)
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testModel.addStage({InputInfo::fromPrevStage(i - 1)}, {OutputInfo::intermediate(desc)});
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else
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testModel.addStage({InputInfo::fromNetwork()}, {OutputInfo::intermediate(desc)});
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if (i != 3)
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testModel.setStageBatchInfo(i, {{0, BatchSupport::Split}});
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}
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testModel.addStage({InputInfo::fromPrevStage(2)}, {OutputInfo::fromNetwork(1)});
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testModel.setStageBatchInfo(5, {{0, BatchSupport::Split}});
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RunPass();
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const auto& data0 = singleElement(checkSingleLoopStart(testModel.getInputs().at(0)));
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const auto& data1 = CheckSingleConnection(data0, 0);
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const auto& data2 = CheckSingleConnection(data1, 1);
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const auto& data3 = CheckSingleConnection(data2, 2);
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const auto& branches = checkBranches(data3, {StageType::None, StageType::LoopEnd});
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const auto& branch1 = branches[0];
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const auto& branch2 = branches[1];
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const auto& data4 = CheckSingleConnection(branch1, 3);
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const auto& data7 = singleElement(checkSingleLoopEnd(data4));
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const auto& data5 = CheckSingleConnection(data7, 4, batchSize);
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ASSERT_EQ(data5, testModel.getOutputs().at(0));
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const auto& data6 = CheckSingleConnection(branch2, 5);
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ASSERT_EQ(data6, testModel.getOutputs().at(1));
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}
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TEST_F(VPU_AdjustDataBatchTest, DISABLED_BranchedWithBatchAndSplitItemsInTheEnd) {
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//
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// -> (Split) -> [Output]
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// [Input] -> (Split) -> (Split) -> (Split)
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// -> (Split) -> [Output]
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//
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const DataDesc desc{16, 16, 3, batchSize};
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testModel.createInputs({desc});
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testModel.createOutputs({desc, desc});
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for (int i = 0; i < 3; i++) {
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if (i > 0)
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testModel.addStage({InputInfo::fromPrevStage(i - 1)}, {OutputInfo::intermediate(desc)});
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else
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testModel.addStage({InputInfo::fromNetwork()}, {OutputInfo::intermediate(desc)});
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testModel.setStageBatchInfo(i, {{0, BatchSupport::Split}});
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}
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for (int i = 0; i < 2; i++) {
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testModel.addStage({InputInfo::fromNetwork(2)}, {OutputInfo::intermediate(desc)});
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testModel.setStageBatchInfo(3 + i, {{0, BatchSupport::Split}});
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}
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testModel.addStage({InputInfo::fromPrevStage(2)}, {OutputInfo::fromNetwork(0)});
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testModel.setStageBatchInfo(3, {{0, BatchSupport::Split}});
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testModel.addStage({InputInfo::fromPrevStage(2)}, {OutputInfo::fromNetwork(1)});
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testModel.setStageBatchInfo(4, {{0, BatchSupport::Split}});
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RunPass();
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const auto& data1 = singleElement(checkSingleLoopStart(testModel.getInputs().at(0)));
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const auto& data2 = CheckSingleConnection(data1, 1);
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const auto& data3 = CheckSingleConnection(data2, 2);
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const auto& branches = checkBranches(data3, {StageType::None, StageType::LoopEnd});
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const auto& branch1 = branches[0];
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const auto& branch2 = branches[1];
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const auto& data4 = CheckSingleConnection(branch1, 3);
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const auto& data5 = CheckSingleConnection(branch2, 4);
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const auto& data6 = checkSingleLoopEnd(data5);
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}
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