// // Copyright © 2017 Arm Ltd. All rights reserved. // SPDX-License-Identifier: MIT // #include #include #include #include #include #include using namespace armnn; namespace { // // this helper only works if all layers where the inputs connect to are not selected // SubGraph::InputSlots CreateInputsFrom(const std::vector & layers) { SubGraph::InputSlots result; for (auto&& layer : layers) { for (auto&& it = layer->BeginInputSlots(); it != layer->EndInputSlots(); ++it) { result.push_back(&(*it)); } } return result; } // // this helper only works if all layers where the outputs connect to are not selected // SubGraph::OutputSlots CreateOutputsFrom(const std::vector & layers) { SubGraph::OutputSlots result; for (auto && layer : layers) { for (auto&& it = layer->BeginOutputSlots(); it != layer->EndOutputSlots(); ++it) { result.push_back(&(*it)); } } return result; } // // this takes the inputs, outputs and layers as a copy and the move these copies into the // resulting subgraph, so the pass bay value is intentional // SubGraphSelector::SubGraphPtr CreateSubGraphFrom(SubGraph::InputSlots inputs, SubGraph::OutputSlots outputs, SubGraph::Layers layers) { return std::make_unique(std::move(inputs), std::move(outputs), std::move(layers)); } template std::vector ToSortedArray(Iterator begin, Iterator end) { std::vector result(begin, end); std::sort(result.begin(), result.end()); return result; } template void CompareVectors(const std::vector & result, const std::vector & expected) { BOOST_CHECK_EQUAL_COLLECTIONS(result.begin(), result.end(), expected.begin(), expected.end()); } void CompareSubGraphs(SubGraphSelector::SubGraphPtr & result, SubGraphSelector::SubGraphPtr & expected) { // expect both to be valid subgraphs BOOST_TEST((result.get() != nullptr)); BOOST_TEST((expected.get() != nullptr)); if (result.get() != nullptr && expected.get() != nullptr) { // try to detect all other obvious errors too, mainly because here // we can get a nicer error message from boost, the collection test // also report error for these BOOST_TEST(result->GetInputSlots().size() == expected->GetInputSlots().size()); BOOST_TEST(result->GetOutputSlots().size() == expected->GetOutputSlots().size()); BOOST_TEST(result->GetLayers().size() == expected->GetLayers().size()); auto resultLayers = ToSortedArray(result->GetLayers().begin(), result->GetLayers().end()); auto expectedLayers = ToSortedArray(expected->GetLayers().begin(), expected->GetLayers().end()); CompareVectors(resultLayers, expectedLayers); auto resultInputs = ToSortedArray(result->GetInputSlots().begin(), result->GetInputSlots().end()); auto expectedInputs = ToSortedArray(expected->GetInputSlots().begin(), expected->GetInputSlots().end()); CompareVectors(resultInputs, expectedInputs); auto resultOutputs = ToSortedArray(result->GetOutputSlots().begin(), result->GetOutputSlots().end()); auto expectedOutputs = ToSortedArray(expected->GetOutputSlots().begin(), expected->GetOutputSlots().end()); CompareVectors(resultOutputs, expectedOutputs); } } } // namespace BOOST_AUTO_TEST_SUITE(SubGraphSelection) BOOST_AUTO_TEST_CASE(NoSubGraphsForNoMatch) { Graph graph; auto output = graph.AddLayer(0, "output"); graph.InsertNewLayer(output->GetInputSlot(0), 0, "input"); SubGraphSelector::SubGraphs subGraphs = SubGraphSelector::SelectSubGraphs(graph, [](const Layer &) { return false; }); BOOST_TEST(subGraphs.empty()); } BOOST_AUTO_TEST_CASE(OneSubGraphsSelectedASingleMatch) { Graph graph; auto output = graph.AddLayer(0, "output"); graph.InsertNewLayer(output->GetInputSlot(0), 0, "input"); SubGraphSelector::SubGraphs subGraphs = SubGraphSelector::SelectSubGraphs( graph, // select the output layer only [](const Layer & l) { bool isOutput = l.GetNameStr().compare("output") == 0; return isOutput; }); BOOST_TEST(subGraphs.size() == 1); if (subGraphs.size() == 1) { auto expected = CreateSubGraphFrom(CreateInputsFrom({output}), // outputs of 'output' will be empty CreateOutputsFrom({output}), {output}); CompareSubGraphs(subGraphs[0], expected); } } BOOST_AUTO_TEST_CASE(MultipleLayersSelectedInTheMiddle) { Graph graph; auto output = graph.AddLayer(0, "output"); auto mid0 = graph.InsertNewLayer(output->GetInputSlot(0), ActivationDescriptor{}, "mid0"); auto mid1 = graph.InsertNewLayer(mid0->GetInputSlot(0), ActivationDescriptor{}, "mid1"); graph.InsertNewLayer(mid1->GetInputSlot(0), 0, "input"); SubGraphSelector::SubGraphs subGraphs = SubGraphSelector::SelectSubGraphs( graph, // select the middle layers only [](const Layer & l) { bool toSelect = (l.GetType() == LayerType::Activation); return toSelect; }); BOOST_TEST(subGraphs.size() == 1); if (subGraphs.size() == 1) { auto expected = CreateSubGraphFrom(CreateInputsFrom({mid1}), CreateOutputsFrom({mid0}), {mid1, mid0}); CompareSubGraphs(subGraphs[0], expected); } } BOOST_AUTO_TEST_CASE(IslandInTheMiddle) { // This case represent the scenario when a non-selected X1 node placed in the middle // of the selected M* nodes: // // X0 -> M1 -> M2 -> M3 -> X2 // X0 -> M4 -> X1 -> M5 -> X2 // /* X0 / \ M1 M4 | | M2 X1 < the island in the middle ! | | M3 M5 \ / X2 */ // The expected result for this is that M1,M2,M3,M4 will be part of one subgraph and // M5 will be part of another subgraph and the input and output slots in the subgraphs // will be set accordingly. // Graph graph; OriginsDescriptor mergerDescriptor(2); auto x2 = graph.AddLayer(mergerDescriptor, "x2"); auto m3 = graph.InsertNewLayer(x2->GetInputSlot(0), ActivationDescriptor{}, "m3"); auto m2 = graph.InsertNewLayer(m3->GetInputSlot(0), ActivationDescriptor{}, "m2"); auto m1 = graph.InsertNewLayer(m2->GetInputSlot(0), ActivationDescriptor{}, "m1"); auto x0 = graph.InsertNewLayer(m1->GetInputSlot(0), 0, "x0"); auto m5 = graph.InsertNewLayer(x2->GetInputSlot(1), ActivationDescriptor{}, "m5"); auto x1 = graph.InsertNewLayer(m5->GetInputSlot(0), Convolution2dDescriptor{}, "x1"); auto m4 = graph.InsertNewLayer(x1->GetInputSlot(0), ActivationDescriptor{}, "m4"); // Connect the other branch to the input layer x0->GetOutputSlot(0).Connect(m4->GetInputSlot(0)); // All selected 'M*' layers will be of Activation type SubGraphSelector::SubGraphs subGraphs = SubGraphSelector::SelectSubGraphs( graph, // select the middle layers only [](const Layer & l) { bool toSelect = (l.GetType() == LayerType::Activation); return toSelect; }); // expected results to test against auto largerSubGraph = CreateSubGraphFrom(CreateInputsFrom({m1, m4}), CreateOutputsFrom({m3, m4}), {m1, m4, m2, m3}); auto smallerSubGraph = CreateSubGraphFrom(CreateInputsFrom({m5}), CreateOutputsFrom({m5}), {m5}); BOOST_TEST(subGraphs.size() == 2); if (subGraphs.size() == 2) { // we need to have valid subgraph pointers here BOOST_TEST((subGraphs[0] != nullptr)); BOOST_TEST((subGraphs[1] != nullptr)); if (subGraphs[0].get() != nullptr && subGraphs[1].get() != nullptr) { // sort the subgraphs by layer size, so it is simpler to test std::sort(subGraphs.begin(), subGraphs.end(), [](SubGraphSelector::SubGraphPtr & lhs, SubGraphSelector::SubGraphPtr & rhs) { return (lhs->GetLayers().size() < rhs->GetLayers().size()); } ); // one subgraph needs to be size=1 and the other one is 4 BOOST_TEST(subGraphs[0]->GetLayers().size() == 1); BOOST_TEST(subGraphs[1]->GetLayers().size() == 4); CompareSubGraphs(subGraphs[0], smallerSubGraph); CompareSubGraphs(subGraphs[1], largerSubGraph); } } } BOOST_AUTO_TEST_CASE(MultipleSimpleSubGraphs) { // This test case represents the scenario when we have two distinct subgraphs // in a simple linear network. The selected nodes are the M* and the // non-selected ones are the X* // // X1 -> M1 -> M2 -> X2 -> M3 -> X3 // // The expected results is two subgraphs, one with {M1, M2} and another one // with {M3} // Graph graph; // the graph is constructed in reverse order auto x3 = graph.AddLayer(0, "output"); auto m3 = graph.InsertNewLayer(x3->GetInputSlot(0), ActivationDescriptor{}, "m3"); auto x2 = graph.InsertNewLayer(m3->GetInputSlot(0), Convolution2dDescriptor{}, "x2"); auto m2 = graph.InsertNewLayer(x2->GetInputSlot(0), ActivationDescriptor{}, "m2"); auto m1 = graph.InsertNewLayer(m2->GetInputSlot(0), ActivationDescriptor{}, "m1"); graph.InsertNewLayer(m1->GetInputSlot(0), 0, "x1"); // All selected 'M*' layers will be of Activation type SubGraphSelector::SubGraphs subGraphs = SubGraphSelector::SelectSubGraphs( graph, // select the middle layers only [](const Layer & l) { bool toSelect = (l.GetType() == LayerType::Activation); return toSelect; }); // expected results to test against auto largerSubGraph = CreateSubGraphFrom(CreateInputsFrom({m1}), CreateOutputsFrom({m2}), {m1, m2}); auto smallerSubGraph = CreateSubGraphFrom(CreateInputsFrom({m3}), CreateOutputsFrom({m3}), {m3}); BOOST_TEST(subGraphs.size() == 2); if (subGraphs.size() == 2) { // we need to have valid subgraph pointers here BOOST_TEST((subGraphs[0] != nullptr)); BOOST_TEST((subGraphs[1] != nullptr)); if (subGraphs[0].get() != nullptr && subGraphs[1].get() != nullptr) { // sort the subgraphs by layer size, so it is simpler to test std::sort(subGraphs.begin(), subGraphs.end(), [](SubGraphSelector::SubGraphPtr & lhs, SubGraphSelector::SubGraphPtr & rhs) { return (lhs->GetLayers().size() < rhs->GetLayers().size()); } ); BOOST_TEST(subGraphs[0]->GetLayers().size() == 1); BOOST_TEST(subGraphs[1]->GetLayers().size() == 2); CompareSubGraphs(subGraphs[0], smallerSubGraph); CompareSubGraphs(subGraphs[1], largerSubGraph); } } } BOOST_AUTO_TEST_CASE(SimpleLinearTest) { //X1 -> M1 -> M2 -> X2 //Where the input slots of M1 and the output slots of M2 are to be the sub graph boundaries. Graph graph; ActivationDescriptor activationDefaults; auto layerX1 = graph.AddLayer(0, "layerX1"); auto layerX2 = graph.AddLayer(0, "layerX2"); auto layerM1 = graph.AddLayer(activationDefaults, "layerM1"); auto layerM2 = graph.AddLayer(activationDefaults, "layerM2"); // X1 // | // M1 // | // M2 // | // X2 layerX1->GetOutputSlot(0).Connect(layerM1->GetInputSlot(0)); layerM1->GetOutputSlot(0).Connect(layerM2->GetInputSlot(0)); layerM2->GetOutputSlot(0).Connect(layerX2->GetInputSlot(0)); SubGraphSelector::SubGraphs subGraphs = SubGraphSelector::SelectSubGraphs( graph, // select the activation layers M1 and M2 [](const Layer & l) { bool toSelect = (l.GetType() == LayerType::Activation); return toSelect; }); BOOST_CHECK(subGraphs.size() == 1); if(subGraphs.size() == 1) { auto expected = CreateSubGraphFrom(CreateInputsFrom({layerM1}), CreateOutputsFrom({layerM2}), {layerM1, layerM2}); CompareSubGraphs(subGraphs[0], expected); } } BOOST_AUTO_TEST_CASE(MultiInputSingleOutput) { //X1 -> M1 -> M3 -> X3 //X2 -> M2 -> M3 -> X3 //Where the input slots of {M1, M2} and the output slots of M3 are to be the subgraph boundaries. Graph graph; ActivationDescriptor activationDefaults; auto layerX1 = graph.AddLayer(0, "layerX1"); auto layerX2 = graph.AddLayer(1, "layerX2"); auto layerM1 = graph.AddLayer(activationDefaults, "layerM1"); auto layerM2 = graph.AddLayer(activationDefaults, "layerM2"); auto layerM3 = graph.AddLayer("layerM3"); auto layerX3 = graph.AddLayer(0, "layerX3"); // X1 X2 // | | // M1 M2 // \ | // \ | // \| // M3 // | // | // X3 layerX1->GetOutputSlot(0).Connect(layerM1->GetInputSlot(0)); layerX2->GetOutputSlot(0).Connect(layerM2->GetInputSlot(0)); layerM1->GetOutputSlot(0).Connect(layerM3->GetInputSlot(0)); layerM2->GetOutputSlot(0).Connect(layerM3->GetInputSlot(1)); layerM3->GetOutputSlot(0).Connect(layerX3->GetInputSlot(0)); SubGraphSelector::SubGraphs subGraphs = SubGraphSelector::SelectSubGraphs( graph, // select Activation and Addition Layers M1, M2 and M3 [](const Layer & l) { bool toSelect = (l.GetType() == LayerType::Activation || l.GetType() == LayerType::Addition); return toSelect; }); BOOST_CHECK(subGraphs.size() == 1); if (subGraphs.size() == 1) { auto expected = CreateSubGraphFrom(CreateInputsFrom({layerM1, layerM2}), CreateOutputsFrom({layerM3}), {layerM1, layerM2, layerM3}); CompareSubGraphs(subGraphs[0], expected); } } BOOST_AUTO_TEST_CASE(SingleInputMultiOutput) { //X1 -> M1 -> M2 -> X2 //X1 -> M1 -> M3 -> X3 //Where the input slots of M1 and the output slots of {M2, M3} are to be the subgraph boundaries. Graph graph; ActivationDescriptor activationDefaults; ViewsDescriptor viewDefaults(2,4); Layer* layerX1 = graph.AddLayer(0, "layerX1"); Layer* layerM1 = graph.AddLayer(viewDefaults, "layerM1"); Layer* layerM2 = graph.AddLayer(activationDefaults, "layerM2"); Layer* layerM3 = graph.AddLayer(activationDefaults, "layerM3"); Layer* layerX2 = graph.AddLayer(0, "layerX2"); Layer* layerX3 = graph.AddLayer(1, "layerX3"); // X2 // | // M1 // /| // / | // / | // M2 M3 // | | // | | // X2 X3 layerX1->GetOutputSlot(0).Connect(layerM1->GetInputSlot(0)); layerM1->GetOutputSlot(0).Connect(layerM2->GetInputSlot(0)); layerM1->GetOutputSlot(1).Connect(layerM3->GetInputSlot(0)); layerM2->GetOutputSlot(0).Connect(layerX2->GetInputSlot(0)); layerM3->GetOutputSlot(0).Connect(layerX3->GetInputSlot(0)); SubGraphSelector::SubGraphs subGraphs = SubGraphSelector::SelectSubGraphs( graph, // select Activation and Splitter Layers M1, M2 and M3 [](const Layer & l) { bool toSelect = (l.GetType() == LayerType::Activation || l.GetType() == LayerType::Splitter); return toSelect; }); BOOST_CHECK(subGraphs.size() == 1); if(subGraphs.size() == 1) { auto expected = CreateSubGraphFrom(CreateInputsFrom({layerM1}), CreateOutputsFrom({layerM2, layerM3}), {layerM1, layerM2, layerM3}); CompareSubGraphs(subGraphs[0], expected); } } BOOST_AUTO_TEST_CASE(MultiInputMultiOutput) { // This case represents the scenario with multiple inputs and multiple outputs // // X1 -> M1 -> M3 -> M4 -> X3 // X2 -> M2 -> M3 -> M5 -> X4 // // Where the input slots of {M1, M2} and the output slots of {M4, M5} are to be the subgraph // boundaries. Graph graph; ActivationDescriptor activationDefaults; OriginsDescriptor mergerDescriptor(2); auto x1 = graph.AddLayer(0, "x1"); auto x2 = graph.AddLayer(1, "x2"); auto m1 = graph.AddLayer(activationDefaults, "m1"); auto m2 = graph.AddLayer(activationDefaults, "m2"); auto m3 = graph.AddLayer(mergerDescriptor, "m3"); auto m4 = graph.AddLayer(activationDefaults, "m4"); auto m5 = graph.AddLayer(activationDefaults, "m5"); auto x3 = graph.AddLayer(0, "x3"); auto x4 = graph.AddLayer(1, "x4"); x1->GetOutputSlot(0).Connect(m1->GetInputSlot(0)); x2->GetOutputSlot(0).Connect(m2->GetInputSlot(0)); m1->GetOutputSlot(0).Connect(m3->GetInputSlot(0)); m2->GetOutputSlot(0).Connect(m3->GetInputSlot(1)); m3->GetOutputSlot(0).Connect(m4->GetInputSlot(0)); m3->GetOutputSlot(0).Connect(m5->GetInputSlot(0)); m4->GetOutputSlot(0).Connect(x3->GetInputSlot(0)); m5->GetOutputSlot(0).Connect(x4->GetInputSlot(0)); SubGraphSelector::SubGraphs subGraphs = SubGraphSelector::SelectSubGraphs( graph, // select Activation and Merger Layers M1, M2, M3, M4, M5 [](const Layer & l) { bool toSelect = (l.GetType() == LayerType::Activation || l.GetType() == LayerType::Merger); return toSelect; }); BOOST_CHECK(subGraphs.size() == 1); if (subGraphs.size() == 1) { auto expected = CreateSubGraphFrom(CreateInputsFrom({m1, m2}), CreateOutputsFrom({m4, m5}), {m1, m2, m3, m4, m5}); CompareSubGraphs(subGraphs[0], expected); } } BOOST_AUTO_TEST_SUITE_END()