diff options
Diffstat (limited to 'src/armnn/test/CreateWorkload.hpp')
| -rw-r--r-- | src/armnn/test/CreateWorkload.hpp | 12 |
1 files changed, 8 insertions, 4 deletions
diff --git a/src/armnn/test/CreateWorkload.hpp b/src/armnn/test/CreateWorkload.hpp index 51820a425f..21385d7a99 100644 --- a/src/armnn/test/CreateWorkload.hpp +++ b/src/armnn/test/CreateWorkload.hpp @@ -133,11 +133,12 @@ std::unique_ptr<WorkloadType> CreateArithmeticWorkloadTest(armnn::IWorkloadFacto template <typename BatchNormalizationFloat32Workload, armnn::DataType DataType> std::unique_ptr<BatchNormalizationFloat32Workload> CreateBatchNormalizationWorkloadTest( - armnn::IWorkloadFactory& factory, armnn::Graph& graph) + armnn::IWorkloadFactory& factory, armnn::Graph& graph, DataLayout dataLayout = DataLayout::NCHW) { // Creates the layer we're testing. BatchNormalizationDescriptor layerDesc; layerDesc.m_Eps = 0.05f; + layerDesc.m_DataLayout = dataLayout; BatchNormalizationLayer* const layer = graph.AddLayer<BatchNormalizationLayer>(layerDesc, "layer"); @@ -155,16 +156,19 @@ std::unique_ptr<BatchNormalizationFloat32Workload> CreateBatchNormalizationWorkl Layer* const input = graph.AddLayer<InputLayer>(0, "input"); Layer* const output = graph.AddLayer<OutputLayer>(0, "output"); + TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{ 2, 3, 1, 1 } : TensorShape{ 2, 1, 1, 3 }; + TensorShape outputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{ 2, 3, 1, 1 } : TensorShape{ 2, 1, 1, 3 }; + // Connects up. - armnn::TensorInfo tensorInfo({2, 3, 1, 1}, DataType); - Connect(input, layer, tensorInfo); - Connect(layer, output, tensorInfo); + Connect(input, layer, TensorInfo(inputShape, DataType)); + Connect(layer, output, TensorInfo(outputShape, DataType)); CreateTensorHandles(graph, factory); // Makes the workload and checks it. auto workload = MakeAndCheckWorkload<BatchNormalizationFloat32Workload>(*layer, graph, factory); BatchNormalizationQueueDescriptor queueDescriptor = workload->GetData(); BOOST_TEST(queueDescriptor.m_Parameters.m_Eps == 0.05f); + 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_Mean->GetTensorInfo() == TensorInfo({3}, DataType))); |