patch/20.02/_optimize_consecutive_reshapes_tests_8cpp_source.xhtml

 //
 // 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()
BOOST_AUTO_TEST_SUITE
BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)

+armnn::MakeOptimizations
Optimizer::Optimizations MakeOptimizations(Args &&... args)
Definition: Optimizer.hpp:43

+armnn::ReshapeDescriptor
A ReshapeDescriptor for the ReshapeLayer.
Definition: Descriptors.hpp:758

+armnn::TensorInfo
Definition: Tensor.hpp:53

+armnn::optimizations
Definition: AddDebug.hpp:12

+armnn::Graph::AddLayer
LayerT * AddLayer(Args &&... args)
Adds a new layer, of type LayerType, to the graph constructed with the arguments passed.
Definition: Graph.hpp:397

+armnn::Graph::cbegin
ConstIterator cbegin() const
Returns const iterator pointing to the beginning of the list. Lowercase for range-based for loops...
Definition: Graph.hpp:168

+armnn::Optimizer::Pass
static void Pass(Graph &graph, const Optimizations &optimizations)
Definition: Optimizer.cpp:16

+armnn::ReshapeLayer
This layer represents a reshape operation.
Definition: ReshapeLayer.hpp:13

+armnn::optimizations::OptimizeConsecutiveReshapes
OptimizeForConnection< ReshapeLayer, ReshapeLayer, OptimizeConsecutiveReshapesImpl > OptimizeConsecutiveReshapes
Definition: OptimizeConsecutiveReshapes.hpp:63

+Optimizer.hpp

+armnn::OutputLayer
A layer user-provided data can be bound to (e.g. inputs, outputs).
Definition: OutputLayer.hpp:13

+armnn::BOOST_AUTO_TEST_CASE
BOOST_AUTO_TEST_CASE(CheckConvolution2dLayer)
Definition: ConstTensorLayerVisitor.cpp:170

+armnn::Graph
Definition: Graph.hpp:29

+armnn::OutputHandler::SetTensorInfo
void SetTensorInfo(const TensorInfo &tensorInfo)
Sets the TensorInfo used by this output handler.
Definition: OutputHandler.cpp:17

+BOOST_AUTO_TEST_SUITE_END
BOOST_AUTO_TEST_SUITE_END()

+armnn::Layer::GetOutputHandler
const OutputHandler & GetOutputHandler(unsigned int i=0) const
Definition: Layer.hpp:221

+armnn::InputLayer
A layer user-provided data can be bound to (e.g. inputs, outputs).
Definition: InputLayer.hpp:13

+CheckSequence
bool CheckSequence(const armnn::Graph::ConstIterator first, const armnn::Graph::ConstIterator last)
Definition: TestUtils.hpp:20

+armnn::DataType::Float32

+armnn::Graph::cend
ConstIterator cend() const
Returns const iterator pointing to the end of the list. Lowercase for range-based for loops...
Definition: Graph.hpp:170

+armnn::Graph::InsertNewLayer
LayerT * InsertNewLayer(InputSlot &insertBefore, Args &&... args)
Inserts a new layer between the output slot currently connected to insertBefore and insertBefore itse...
Definition: Graph.hpp:409

+armnn::Layer
Definition: Layer.hpp:209

+