IVGCVSW-6169 Add GpuAcc Conv3d Workload
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: I8b73dccc14ef71cc083896102e24afb2e56e72e2
diff --git a/src/backends/cl/workloads/ClConvolution3dWorkload.cpp b/src/backends/cl/workloads/ClConvolution3dWorkload.cpp
new file mode 100644
index 0000000..18a2c31
--- /dev/null
+++ b/src/backends/cl/workloads/ClConvolution3dWorkload.cpp
@@ -0,0 +1,116 @@
+//
+// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "ClConvolution3dWorkload.hpp"
+
+#include "ClWorkloadUtils.hpp"
+
+#include <cl/ClLayerSupport.hpp>
+#include <cl/ClTensorHandle.hpp>
+#include <cl/ClLayerSupport.hpp>
+#include <aclCommon/ArmComputeUtils.hpp>
+#include <aclCommon/ArmComputeTensorUtils.hpp>
+#include <backendsCommon/TensorHandle.hpp>
+
+#include <arm_compute/runtime/CL/functions/CLConv3D.h>
+
+namespace armnn
+{
+using namespace armcomputetensorutils;
+
+arm_compute::Status ClConvolution3dWorkloadValidate(const TensorInfo& input,
+ const TensorInfo& output,
+ const Convolution3dDescriptor& descriptor,
+ const TensorInfo& weights,
+ const Optional<TensorInfo>& biases,
+ bool isFastMathEnabled,
+ const ActivationDescriptor* activationDescriptor)
+{
+ const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout);
+ const arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.m_DataLayout);
+
+ arm_compute::TensorInfo aclBiasesInfo;
+ arm_compute::TensorInfo* optionalAclBiasesInfo = nullptr;
+ if (descriptor.m_BiasEnabled)
+ {
+ ARMNN_ASSERT(biases.has_value());
+ aclBiasesInfo = BuildArmComputeTensorInfo(biases.value(), descriptor.m_DataLayout);
+ optionalAclBiasesInfo = &aclBiasesInfo;
+ }
+
+ const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout);
+
+ const arm_compute::Conv3dInfo aclConv3DInfo = ComputeConv3DInfo(descriptor,
+ isFastMathEnabled,
+ activationDescriptor);
+
+ return arm_compute::CLConv3D::validate(&aclInputInfo,
+ &aclWeightsInfo,
+ optionalAclBiasesInfo,
+ &aclOutputInfo,
+ aclConv3DInfo);
+}
+
+ClConvolution3dWorkload::ClConvolution3dWorkload(const Convolution3dQueueDescriptor& descriptor,
+ const WorkloadInfo& info,
+ std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager,
+ const arm_compute::CLCompileContext& clCompileContext,
+ const bool isFastMathEnabled)
+ : BaseWorkload<Convolution3dQueueDescriptor>(descriptor, info)
+ , m_ConvolutionLayer()
+{
+ IgnoreUnused(memoryManager);
+
+ uint32_t numInputs = m_Data.m_Parameters.m_BiasEnabled ? 3: 2;
+ m_Data.ValidateInputsOutputs("ClConvolution3dWorkload", numInputs, 1);
+
+ arm_compute::ICLTensor& input = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
+ arm_compute::ICLTensor& weights = static_cast<IClTensorHandle*>(m_Data.m_Inputs[1])->GetTensor();
+ arm_compute::ICLTensor* biasesPtr = nullptr;
+ if (m_Data.m_Parameters.m_BiasEnabled)
+ {
+ biasesPtr = &static_cast<IClTensorHandle*>(m_Data.m_Inputs[2])->GetTensor();
+ }
+ arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
+
+ arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout);
+ input.info()->set_data_layout(aclDataLayout);
+ weights.info()->set_data_layout(aclDataLayout);
+ output.info()->set_data_layout(aclDataLayout);
+
+ const arm_compute::Conv3dInfo aclConv3DInfo = ComputeConv3DInfo(descriptor,
+ isFastMathEnabled);
+
+ m_ConvolutionLayer.configure(clCompileContext,
+ &input,
+ &weights,
+ biasesPtr,
+ &output,
+ aclConv3DInfo);
+
+ // Add details for profiling output
+ WorkloadInfo detailsInfo;
+
+ detailsInfo.m_InputTensorInfos = info.m_InputTensorInfos;
+ detailsInfo.m_OutputTensorInfos = info.m_OutputTensorInfos;
+
+ // Report Profiling Details
+ ARMNN_REPORT_PROFILING_WORKLOAD_DESC("ClConvolution3dWorkload_Construct",
+ descriptor.m_Parameters,
+ detailsInfo,
+ this->GetGuid());
+
+ // Force Compute Library to perform the necessary copying and reshaping, after which
+ // delete all the input tensors that will no longer be needed
+ m_ConvolutionLayer.prepare();
+}
+
+void ClConvolution3dWorkload::Execute() const
+{
+ ARMNN_SCOPED_PROFILING_EVENT_CL_GUID("ClConvolution3dWorkload_Execute", this->GetGuid());
+ RunClFunction(m_ConvolutionLayer, CHECK_LOCATION());
+}
+
+} //namespace armnn