diff options
Diffstat (limited to 'src/backends/neon')
| -rw-r--r-- | src/backends/neon/test/NeonCreateWorkloadTests.cpp | 31 | ||||
| -rw-r--r-- | src/backends/neon/test/NeonLayerTests.cpp | 1 | ||||
| -rw-r--r-- | src/backends/neon/workloads/NeonBatchNormalizationFloatWorkload.cpp | 24 |
3 files changed, 42 insertions, 14 deletions
diff --git a/src/backends/neon/test/NeonCreateWorkloadTests.cpp b/src/backends/neon/test/NeonCreateWorkloadTests.cpp index a588a3ecc8..8d5574c6a7 100644 --- a/src/backends/neon/test/NeonCreateWorkloadTests.cpp +++ b/src/backends/neon/test/NeonCreateWorkloadTests.cpp @@ -153,30 +153,45 @@ BOOST_AUTO_TEST_CASE(CreateMultiplicationFloatWorkload) } template <typename BatchNormalizationWorkloadType, typename armnn::DataType DataType> -static void NeonCreateBatchNormalizationWorkloadTest() +static void NeonCreateBatchNormalizationWorkloadTest(DataLayout dataLayout) { Graph graph; NeonWorkloadFactory factory; - auto workload = CreateBatchNormalizationWorkloadTest<BatchNormalizationWorkloadType, DataType>(factory, graph); + auto workload = CreateBatchNormalizationWorkloadTest<BatchNormalizationWorkloadType, DataType> + (factory, graph, dataLayout); // Checks that outputs and inputs are as we expect them (see definition of CreateBatchNormalizationWorkloadTest). BatchNormalizationQueueDescriptor queueDescriptor = workload->GetData(); auto inputHandle = boost::polymorphic_downcast<INeonTensorHandle*>(queueDescriptor.m_Inputs[0]); auto outputHandle = boost::polymorphic_downcast<INeonTensorHandle*>(queueDescriptor.m_Outputs[0]); - BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, TensorInfo({2, 3, 1, 1}, DataType))); - BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, TensorInfo({2, 3, 1, 1}, DataType))); + + TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{2, 3, 4, 4} : TensorShape{2, 4, 4, 3}; + TensorShape outputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{2, 3, 4, 4} : TensorShape{2, 4, 4, 3}; + + BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, TensorInfo(inputShape, DataType))); + BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, TensorInfo(outputShape, DataType))); } #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC -BOOST_AUTO_TEST_CASE(CreateBatchNormalizationFloat16Workload) +BOOST_AUTO_TEST_CASE(CreateBatchNormalizationFloat16NchwWorkload) +{ + NeonCreateBatchNormalizationWorkloadTest<NeonBatchNormalizationFloatWorkload, DataType::Float16>(DataLayout::NCHW); +} + +BOOST_AUTO_TEST_CASE(CreateBatchNormalizationFloat16NhwcWorkload) { - NeonCreateBatchNormalizationWorkloadTest<NeonBatchNormalizationFloatWorkload, DataType::Float16>(); + NeonCreateBatchNormalizationWorkloadTest<NeonBatchNormalizationFloatWorkload, DataType::Float16>(DataLayout::NHWC); } #endif -BOOST_AUTO_TEST_CASE(CreateBatchNormalizationFloatWorkload) +BOOST_AUTO_TEST_CASE(CreateBatchNormalizationFloatNchwWorkload) +{ + NeonCreateBatchNormalizationWorkloadTest<NeonBatchNormalizationFloatWorkload, DataType::Float32>(DataLayout::NCHW); +} + +BOOST_AUTO_TEST_CASE(CreateBatchNormalizationFloatNhwcWorkload) { - NeonCreateBatchNormalizationWorkloadTest<NeonBatchNormalizationFloatWorkload, DataType::Float32>(); + NeonCreateBatchNormalizationWorkloadTest<NeonBatchNormalizationFloatWorkload, DataType::Float32>(DataLayout::NHWC); } template <typename armnn::DataType DataType> diff --git a/src/backends/neon/test/NeonLayerTests.cpp b/src/backends/neon/test/NeonLayerTests.cpp index 31ee7d87c1..568a2367c6 100644 --- a/src/backends/neon/test/NeonLayerTests.cpp +++ b/src/backends/neon/test/NeonLayerTests.cpp @@ -338,6 +338,7 @@ ARMNN_AUTO_TEST_CASE(MultiplicationBroadcast1DVector, MultiplicationBroadcast1DV // Batch Norm ARMNN_AUTO_TEST_CASE(BatchNorm, BatchNormTest) +ARMNN_AUTO_TEST_CASE(BatchNormNhwc, BatchNormNhwcTest) // Constant ARMNN_AUTO_TEST_CASE(Constant, ConstantTest) diff --git a/src/backends/neon/workloads/NeonBatchNormalizationFloatWorkload.cpp b/src/backends/neon/workloads/NeonBatchNormalizationFloatWorkload.cpp index f7056a515b..95cfdce9b4 100644 --- a/src/backends/neon/workloads/NeonBatchNormalizationFloatWorkload.cpp +++ b/src/backends/neon/workloads/NeonBatchNormalizationFloatWorkload.cpp @@ -21,12 +21,20 @@ arm_compute::Status NeonBatchNormalizationValidate(const TensorInfo& input, const TensorInfo& gamma, const BatchNormalizationDescriptor& descriptor) { - const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input); - const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output); - const arm_compute::TensorInfo aclMeanInfo = BuildArmComputeTensorInfo(mean); - const arm_compute::TensorInfo aclVarInfo = BuildArmComputeTensorInfo(var); - const arm_compute::TensorInfo aclBetaInfo = BuildArmComputeTensorInfo(beta); - const arm_compute::TensorInfo aclGammaInfo = BuildArmComputeTensorInfo(gamma); + const DataLayout dataLayout = descriptor.m_DataLayout.GetDataLayout(); + + const arm_compute::TensorInfo aclInputInfo = + armcomputetensorutils::BuildArmComputeTensorInfo(input, dataLayout); + const arm_compute::TensorInfo aclOutputInfo = + armcomputetensorutils::BuildArmComputeTensorInfo(output, dataLayout); + const arm_compute::TensorInfo aclMeanInfo = + armcomputetensorutils::BuildArmComputeTensorInfo(mean, dataLayout); + const arm_compute::TensorInfo aclVarInfo = + armcomputetensorutils::BuildArmComputeTensorInfo(var, dataLayout); + const arm_compute::TensorInfo aclBetaInfo = + armcomputetensorutils::BuildArmComputeTensorInfo(beta, dataLayout); + const arm_compute::TensorInfo aclGammaInfo = + armcomputetensorutils::BuildArmComputeTensorInfo(gamma, dataLayout); return arm_compute::NEBatchNormalizationLayer::validate(&aclInputInfo, &aclOutputInfo, @@ -46,6 +54,10 @@ NeonBatchNormalizationFloatWorkload::NeonBatchNormalizationFloatWorkload( arm_compute::ITensor& input = boost::polymorphic_downcast<INeonTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); arm_compute::ITensor& output = boost::polymorphic_downcast<INeonTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout.GetDataLayout()); + input.info()->set_data_layout(aclDataLayout); + output.info()->set_data_layout(aclDataLayout); + m_Mean = std::make_unique<arm_compute::Tensor>(); BuildArmComputeTensor(*m_Mean, m_Data.m_Mean->GetTensorInfo()); |