diff options
Diffstat (limited to 'src/armnn/test/OptimizerTests.cpp')
| -rw-r--r-- | src/armnn/test/OptimizerTests.cpp | 85 |
1 files changed, 84 insertions, 1 deletions
diff --git a/src/armnn/test/OptimizerTests.cpp b/src/armnn/test/OptimizerTests.cpp index fa860abb64..f0d132a561 100644 --- a/src/armnn/test/OptimizerTests.cpp +++ b/src/armnn/test/OptimizerTests.cpp @@ -624,6 +624,89 @@ BOOST_AUTO_TEST_CASE(FoldPadLayerIntoConvolution2dLayer) &IsLayerOfType<armnn::OutputLayer>)); } +BOOST_AUTO_TEST_CASE(FoldPadLayerIntoPooling2dLayer) +{ + Graph graph; + const unsigned int inputShape[] = { 1, 2, 2, 3 }; + const unsigned int paddedShape[] = { 1, 3, 3, 3 }; + const unsigned int outputShape[] = { 1, 2, 2, 3 }; + + armnn::TensorInfo inputInfo(4, inputShape, DataType::Float32); + armnn::TensorInfo paddedInfo(4, paddedShape, DataType::Float32); + armnn::TensorInfo outputInfo(4, outputShape, DataType::Float32); + + Layer* input = graph.AddLayer<InputLayer>(0, "input"); + input->GetOutputSlot().SetTensorInfo(inputInfo); + + PadDescriptor padDescriptor({{ 0, 0 }, { 1, 1 }, { 1, 1 }, { 0, 0 }}); + + PadLayer* padLayer = graph.AddLayer<PadLayer>(padDescriptor, "pad"); + padLayer->GetOutputSlot().SetTensorInfo(paddedInfo); + + Pooling2dDescriptor pooling2dDescriptor; + pooling2dDescriptor.m_PoolWidth = 3; + pooling2dDescriptor.m_PoolHeight = 3; + pooling2dDescriptor.m_StrideX = 1; + pooling2dDescriptor.m_StrideY = 1; + pooling2dDescriptor.m_DataLayout = DataLayout::NHWC; + + Pooling2dLayer* pool2dLayer = graph.AddLayer<Pooling2dLayer>(pooling2dDescriptor, "pool2d"); + pool2dLayer->GetOutputSlot().SetTensorInfo(outputInfo); + + Layer* output = graph.AddLayer<OutputLayer>(0, "output"); + + // Connect up layers - input -> pad -> pool2d -> output + input->GetOutputSlot().Connect(padLayer->GetInputSlot(0)); + padLayer->GetOutputSlot().Connect(pool2dLayer->GetInputSlot(0)); + pool2dLayer->GetOutputSlot().Connect(output->GetInputSlot(0)); + + auto checkSimplePool2d = [&](const armnn::Layer* const layer) + { + const auto pool2dLayer = static_cast<const armnn::Pooling2dLayer*>(layer); + return IsLayerOfType<armnn::Pooling2dLayer>(layer) && + (layer->GetNameStr() == "pool2d") && + (pool2dLayer->GetParameters() == pooling2dDescriptor); + }; + + BOOST_TEST(CheckSequence(graph.cbegin(), + graph.cend(), + &IsLayerOfType<armnn::InputLayer>, + &IsLayerOfType<armnn::PadLayer>, + checkSimplePool2d, + &IsLayerOfType<armnn::OutputLayer>)); + + armnn::Optimizer::Pass(graph, armnn::MakeOptimizations(FoldPadIntoPooling2d())); + + auto checkPadFoldedIntoPool2d = [&](const armnn::Layer* const layer) + { + if (!IsLayerOfType<armnn::Pooling2dLayer>(layer) || (layer->GetNameStr() != "folded-pad-into-pool2d")) + { + return false; + } + + const auto pool2dLayer = static_cast<const armnn::Pooling2dLayer*>(layer); + const Pooling2dDescriptor pool2dLayerParams = pool2dLayer->GetParameters(); + + Pooling2dDescriptor pool2dLayerParamsNoPad = pool2dLayerParams; + pool2dLayerParamsNoPad.m_PadLeft = 0; + pool2dLayerParamsNoPad.m_PadRight = 0; + pool2dLayerParamsNoPad.m_PadTop = 0; + pool2dLayerParamsNoPad.m_PadBottom = 0; + + return (pool2dLayerParamsNoPad == pooling2dDescriptor) && + (pool2dLayerParams.m_PadLeft == 1) && + (pool2dLayerParams.m_PadRight == 1) && + (pool2dLayerParams.m_PadTop == 1) && + (pool2dLayerParams.m_PadBottom == 1); + }; + + BOOST_TEST(CheckSequence(graph.cbegin(), + graph.cend(), + &IsLayerOfType<armnn::InputLayer>, + checkPadFoldedIntoPool2d, + &IsLayerOfType<armnn::OutputLayer>)); +} + class MockLayerSupport : public LayerSupportBase { public: bool IsInputSupported(const TensorInfo& /*input*/, @@ -912,4 +995,4 @@ BOOST_AUTO_TEST_CASE(OptimizeForExclusiveConnectionsWithoutFuseTest) &IsLayerOfType<armnn::OutputLayer>, &IsLayerOfType<armnn::OutputLayer>)); } -BOOST_AUTO_TEST_SUITE_END()
\ No newline at end of file +BOOST_AUTO_TEST_SUITE_END() |