| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "../TestUtils.hpp" |
| |
| #include <Optimizer.hpp> |
| |
| #include <boost/test/unit_test.hpp> |
| |
| BOOST_AUTO_TEST_SUITE(Optimizer) |
| using namespace armnn::optimizations; |
| |
| BOOST_AUTO_TEST_CASE(OptimizeConsecutiveReshapesTest) |
| { |
| armnn::Graph graph; |
| |
| const armnn::TensorInfo info0({ 1, 2, 3, 5 }, armnn::DataType::Float32); |
| |
| auto output = graph.AddLayer<armnn::OutputLayer>(0, "output"); |
| auto input = graph.InsertNewLayer<armnn::InputLayer>(output->GetInputSlot(0), 0, "input"); |
| |
| input->GetOutputHandler().SetTensorInfo(info0); |
| |
| { |
| // Inserts two reshapes. |
| const armnn::TensorInfo info1({ 1, 30, 1, 1 }, armnn::DataType::Float32); |
| const armnn::TensorInfo info2({ 1, 2, 1, 15 }, armnn::DataType::Float32); |
| |
| std::string reshape1Name = "reshape1"; |
| std::string reshape2Name = "reshape2"; |
| |
| auto reshape1 = graph.InsertNewLayer<armnn::ReshapeLayer>( |
| output->GetInputSlot(0), armnn::ReshapeDescriptor{ info1.GetShape() }, reshape1Name.c_str()); |
| auto reshape2 = graph.InsertNewLayer<armnn::ReshapeLayer>( |
| output->GetInputSlot(0), armnn::ReshapeDescriptor{ info2.GetShape() }, reshape2Name.c_str()); |
| |
| reshape1->GetOutputHandler().SetTensorInfo(info1); |
| reshape2->GetOutputHandler().SetTensorInfo(info2); |
| |
| BOOST_TEST(CheckSequence(graph.cbegin(), graph.cend(), &IsLayerOfType<armnn::InputLayer>, |
| &IsLayerOfType<armnn::ReshapeLayer>, &IsLayerOfType<armnn::ReshapeLayer>, |
| &IsLayerOfType<armnn::OutputLayer>)); |
| |
| armnn::Optimizer::Pass(graph, armnn::MakeOptimizations(OptimizeConsecutiveReshapes())); |
| |
| auto checkReshape = [&info2](const armnn::Layer* const layer) -> bool { |
| const auto reshapeLayer = static_cast<const armnn::ReshapeLayer*>(layer); |
| return IsLayerOfType<armnn::ReshapeLayer>(layer) && |
| (reshapeLayer->GetParameters().m_TargetShape == info2.GetShape()) && |
| (reshapeLayer->GetOutputHandler().GetTensorInfo().GetShape() == info2.GetShape()); |
| }; |
| |
| // The two reshapes are replaced by a single equivalent reshape. |
| BOOST_TEST(CheckSequence(graph.cbegin(), graph.cend(), &IsLayerOfType<armnn::InputLayer>, checkReshape, |
| &IsLayerOfType<armnn::OutputLayer>)); |
| |
| // Check the new reshape layer has the other two reshapes as related layers |
| std::list<std::string> testRelatedLayers = { reshape2Name, reshape1Name }; |
| |
| BOOST_TEST(CheckRelatedLayers<armnn::ReshapeLayer>(graph, testRelatedLayers)); |
| } |
| |
| { |
| // Inserts a reshape to the input shape. |
| auto reshapeToIn = graph.InsertNewLayer<armnn::ReshapeLayer>( |
| output->GetInputSlot(0), armnn::ReshapeDescriptor{ info0.GetShape() }, "reshapeToIn"); |
| |
| reshapeToIn->GetOutputHandler().SetTensorInfo(info0); |
| |
| armnn::Optimizer::Pass(graph, armnn::MakeOptimizations(OptimizeConsecutiveReshapes())); |
| |
| // The two reshapes are removed. |
| BOOST_TEST(CheckSequence(graph.cbegin(), graph.cend(), &IsLayerOfType<armnn::InputLayer>, |
| &IsLayerOfType<armnn::OutputLayer>)); |
| } |
| } |
| |
| BOOST_AUTO_TEST_SUITE_END() |