From b4dd5cc86d4eb841de670f0f102ede599e0d9c40 Mon Sep 17 00:00:00 2001 From: Keith Davis Date: Thu, 7 Apr 2022 11:32:00 +0100 Subject: IVGCVSW-6124 ConstTensorsAsInput: Conv2d - FrontEnd * Update Front-end and Tools. * Updated Serializer, Deserializer and unit tests to reflect this. * Updated TfLiteDelegate, TfLiteParser and OnnxParser. * Updated Ref. * Fixed resulting Neon / CL tests * Unified optimizers for conv2d ops * Optimizer Fix - Fp32ToBf16 * Partial implementation for ACL backends to fix VTS failures !android-nn-driver:7477 Signed-off-by: Keith Davis Change-Id: I5fb18877f7ee32643e15a9818945356274bb401b --- src/backends/cl/ClBackend.cpp | 4 ++-- src/backends/cl/test/ClCreateWorkloadTests.cpp | 4 ++++ src/backends/cl/test/ClImportTensorHandleTests.cpp | 8 +++++++- src/backends/cl/workloads/ClConvolution2dWorkload.cpp | 19 ++++++++++++++++--- 4 files changed, 29 insertions(+), 6 deletions(-) (limited to 'src/backends/cl') diff --git a/src/backends/cl/ClBackend.cpp b/src/backends/cl/ClBackend.cpp index 47990d87dc..bd1b94e79f 100644 --- a/src/backends/cl/ClBackend.cpp +++ b/src/backends/cl/ClBackend.cpp @@ -341,14 +341,14 @@ OptimizationViews ClBackend::OptimizeSubgraphView(const SubgraphView& subgraph, if (baseLayer->GetParameters().m_BiasEnabled) { - biases = baseLayer->m_Bias->GetTensorInfo(); + biases = baseLayer->GetInputSlot(2).GetConnectedOutputSlot()->GetTensorInfo(); } arm_compute::Status status = ClConvolution2dWorkloadValidate( baseLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo(), activationLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo(), baseLayer->GetParameters(), - baseLayer->m_Weight->GetTensorInfo(), + baseLayer->GetInputSlot(1).GetConnectedOutputSlot()->GetTensorInfo(), biases, isFastMathEnabled, &activationDesc); diff --git a/src/backends/cl/test/ClCreateWorkloadTests.cpp b/src/backends/cl/test/ClCreateWorkloadTests.cpp index 4f53b921d0..3a757f8820 100644 --- a/src/backends/cl/test/ClCreateWorkloadTests.cpp +++ b/src/backends/cl/test/ClCreateWorkloadTests.cpp @@ -471,6 +471,8 @@ TEST_CASE_FIXTURE(ClContextControlFixture, "CreateConvolution2dClCompiledContext auto tensorHandleFactory = ClWorkloadFactoryHelper::GetTensorHandleFactory(memoryManager); std::unique_ptr inputHandle = tensorHandleFactory.CreateTensorHandle(inputInfo); + std::unique_ptr weightsHandle = tensorHandleFactory.CreateTensorHandle(kernelInfo); + std::unique_ptr biasHandle = tensorHandleFactory.CreateTensorHandle(biasInfo); std::unique_ptr outputHandle = tensorHandleFactory.CreateTensorHandle(outputInfo); @@ -487,6 +489,8 @@ TEST_CASE_FIXTURE(ClContextControlFixture, "CreateConvolution2dClCompiledContext queueDescriptor.m_Bias = &biasTensor; AddInputToWorkload(queueDescriptor, workloadInfo, inputInfo, inputHandle.get()); + AddInputToWorkload(queueDescriptor, workloadInfo, kernelInfo, weightsHandle.get()); + AddInputToWorkload(queueDescriptor, workloadInfo, biasInfo, biasHandle.get()); AddOutputToWorkload(queueDescriptor, workloadInfo, outputInfo, outputHandle.get()); // Initialize our m_CLCompileContext using default device and context diff --git a/src/backends/cl/test/ClImportTensorHandleTests.cpp b/src/backends/cl/test/ClImportTensorHandleTests.cpp index e10e81ac26..9bfd1fb46d 100644 --- a/src/backends/cl/test/ClImportTensorHandleTests.cpp +++ b/src/backends/cl/test/ClImportTensorHandleTests.cpp @@ -11,7 +11,6 @@ #include - #include #include #include "Network.hpp" @@ -320,10 +319,13 @@ TEST_CASE_FIXTURE(ClContextControlFixture, "ClForceImportConv2dEndToEnd") convDesc2d.m_PadTop = 1; convDesc2d.m_PadBottom = 1; convDesc2d.m_DataLayout = DataLayout::NHWC; + + ARMNN_NO_DEPRECATE_WARN_BEGIN armnn::IConnectableLayer* const convLayer = network->AddConvolution2dLayer(convDesc2d, weights, armnn::EmptyOptional(), "conv"); + ARMNN_NO_DEPRECATE_WARN_END ARMNN_ASSERT(convLayer); inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0)); @@ -876,10 +878,12 @@ TEST_CASE_FIXTURE(ClContextControlFixture, "ClForceImportRepeatedInferencesEndTo convDesc2d.m_PadTop = 1; convDesc2d.m_PadBottom = 1; convDesc2d.m_DataLayout = DataLayout::NHWC; + ARMNN_NO_DEPRECATE_WARN_BEGIN armnn::IConnectableLayer* const convLayer = network->AddConvolution2dLayer(convDesc2d, weights, armnn::EmptyOptional(), "conv"); + ARMNN_NO_DEPRECATE_WARN_END ARMNN_ASSERT(convLayer); inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0)); @@ -1094,10 +1098,12 @@ TEST_CASE_FIXTURE(ClContextControlFixture, "ClForceImportRepeatedInferencesInver convDesc2d.m_PadTop = 1; convDesc2d.m_PadBottom = 1; convDesc2d.m_DataLayout = DataLayout::NHWC; + ARMNN_NO_DEPRECATE_WARN_BEGIN armnn::IConnectableLayer* const convLayer = network->AddConvolution2dLayer(convDesc2d, weights, armnn::EmptyOptional(), "conv"); + ARMNN_NO_DEPRECATE_WARN_END ARMNN_ASSERT(convLayer); inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0)); diff --git a/src/backends/cl/workloads/ClConvolution2dWorkload.cpp b/src/backends/cl/workloads/ClConvolution2dWorkload.cpp index bf82fbf255..e3d679a773 100644 --- a/src/backends/cl/workloads/ClConvolution2dWorkload.cpp +++ b/src/backends/cl/workloads/ClConvolution2dWorkload.cpp @@ -28,6 +28,15 @@ arm_compute::Status ClConvolution2dWorkloadValidate(const TensorInfo& input, bool isFastMathEnabled, const ActivationDescriptor* activationDescriptor) { + // The implemented workload does support both const and non const + // weights. However, in the case of non const weights we'd have to call + // prepare or configure for each inference which we're not setup to do just yet. + if (!weights.IsConstant()) + { + return arm_compute::Status{arm_compute::ErrorCode::RUNTIME_ERROR, + "ArmNN ClConvolution2dWorkload does not support non constant weights."}; + } + const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout); const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout); const arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.m_DataLayout); @@ -41,7 +50,12 @@ arm_compute::Status ClConvolution2dWorkloadValidate(const TensorInfo& input, if (descriptor.m_BiasEnabled) { ARMNN_ASSERT(biases.has_value()); - + // Same for bias as weights. We don't currently support non const. + if (!biases.value().IsConstant()) + { + return arm_compute::Status{arm_compute::ErrorCode::RUNTIME_ERROR, + "ArmNN ClConvolution2dWorkload does not support non constant bias."}; + } aclBiasesInfo = BuildArmComputeTensorInfo(biases.value(), descriptor.m_DataLayout); optionalAclBiasesInfo = &aclBiasesInfo; } @@ -72,6 +86,7 @@ ClConvolution2dWorkload::ClConvolution2dWorkload(const Convolution2dQueueDescrip { ARMNN_SCOPED_PROFILING_EVENT(Compute::Undefined, "ClConvolution2dWorkload"); const TensorInfo& weightInfo = m_Data.m_Weight->GetTensorInfo(); + m_Data.ValidateInputsOutputs("ClConvolution2dWorkload", 1, 1); m_KernelTensor = std::make_unique(); BuildArmComputeTensor(*m_KernelTensor, weightInfo, m_Data.m_Parameters.m_DataLayout); @@ -85,8 +100,6 @@ ClConvolution2dWorkload::ClConvolution2dWorkload(const Convolution2dQueueDescrip BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo(), m_Data.m_Parameters.m_DataLayout); } - m_Data.ValidateInputsOutputs("ClConvolution2dWorkload", 1, 1); - arm_compute::ICLTensor& input = static_cast(m_Data.m_Inputs[0])->GetTensor(); arm_compute::ICLTensor& output = static_cast(m_Data.m_Outputs[0])->GetTensor(); -- cgit v1.2.1