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Diffstat (limited to 'src/armnn/test/CreateWorkload.hpp')
| -rw-r--r-- | src/armnn/test/CreateWorkload.hpp | 58 |
1 files changed, 58 insertions, 0 deletions
diff --git a/src/armnn/test/CreateWorkload.hpp b/src/armnn/test/CreateWorkload.hpp index 3f3cdc3986..60beb51c32 100644 --- a/src/armnn/test/CreateWorkload.hpp +++ b/src/armnn/test/CreateWorkload.hpp @@ -279,6 +279,64 @@ std::unique_ptr<Convolution2dWorkload> CreateConvolution2dWorkloadTest(armnn::IW return workload; } +template <typename Convolution2dWorkload, armnn::DataType DataType> +std::unique_ptr<Convolution2dWorkload> CreateConvolution2dWorkloadFastMathTest(armnn::IWorkloadFactory& factory, + armnn::Graph& graph, + DataLayout dataLayout = DataLayout::NCHW, + const ModelOptions& modelOptions = {}) +{ + // Creates the layer we're testing. + Convolution2dDescriptor layerDesc; + layerDesc.m_PadLeft = 0; + layerDesc.m_PadRight = 0; + layerDesc.m_PadTop = 0; + layerDesc.m_PadBottom = 0; + layerDesc.m_StrideX = 1; + layerDesc.m_StrideY = 1; + layerDesc.m_BiasEnabled = false; + layerDesc.m_DataLayout = dataLayout; + + Convolution2dLayer* const layer = graph.AddLayer<Convolution2dLayer>(layerDesc, "layer"); + + TensorShape weightShape = TensorShape{32, 32, 3, 3}; + TensorShape inputShape = TensorShape{1, 32, 149, 149}; + TensorShape outputShape = TensorShape{1, 32, 147, 147}; + + layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(TensorInfo(weightShape, DataType)); + layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>(TensorInfo({2}, GetBiasDataType(DataType))); + + layer->m_Weight->Allocate(); + layer->m_Bias->Allocate(); + + // Creates extra layers. + Layer* const input = graph.AddLayer<InputLayer>(0, "input"); + Layer* const output = graph.AddLayer<OutputLayer>(0, "output"); + + // Connects up. + Connect(input, layer, TensorInfo(inputShape, DataType)); + Connect(layer, output, TensorInfo(outputShape, DataType)); + CreateTensorHandles(graph, factory); + + // Makes the workload and checks it. + auto workload = MakeAndCheckWorkload<Convolution2dWorkload>(*layer, factory, modelOptions); + + Convolution2dQueueDescriptor queueDescriptor = workload->GetData(); + BOOST_TEST(queueDescriptor.m_Parameters.m_StrideX == 1); + BOOST_TEST(queueDescriptor.m_Parameters.m_StrideY == 1); + BOOST_TEST(queueDescriptor.m_Parameters.m_PadLeft == 0); + BOOST_TEST(queueDescriptor.m_Parameters.m_PadRight == 0); + BOOST_TEST(queueDescriptor.m_Parameters.m_PadTop == 0); + BOOST_TEST(queueDescriptor.m_Parameters.m_PadBottom == 0); + BOOST_TEST((queueDescriptor.m_Parameters.m_DataLayout == dataLayout)); + + BOOST_TEST(queueDescriptor.m_Inputs.size() == 1); + BOOST_TEST(queueDescriptor.m_Outputs.size() == 1); + BOOST_TEST((queueDescriptor.m_Weight->GetTensorInfo() == TensorInfo(weightShape, DataType))); + + // Returns so we can do extra, backend-specific tests. + return workload; +} + template <typename LstmWorkload> std::unique_ptr<LstmWorkload> CreateLstmWorkloadTest(armnn::IWorkloadFactory& factory, armnn::Graph& graph) { |