| // |
| // Copyright © 2017 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "ClMultiplicationWorkload.hpp" |
| |
| #include <aclCommon/ArmComputeUtils.hpp> |
| #include <armnn/backends/TensorHandle.hpp> |
| |
| #include <cl/ClTensorHandle.hpp> |
| |
| #include "ClWorkloadUtils.hpp" |
| |
| namespace armnn |
| { |
| |
| arm_compute::Status ClMultiplicationWorkloadValidate(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| const ActivationDescriptor* activationDescriptor) |
| { |
| const arm_compute::TensorInfo aclInput1 = armcomputetensorutils::BuildArmComputeTensorInfo(input0); |
| const arm_compute::TensorInfo aclInput2 = armcomputetensorutils::BuildArmComputeTensorInfo(input1); |
| const arm_compute::TensorInfo aclOutput = armcomputetensorutils::BuildArmComputeTensorInfo(output); |
| |
| auto convertPolicy = (IsQuantizedType(input0.GetDataType()) || IsQuantizedType(input1.GetDataType())) ? |
| arm_compute::ConvertPolicy::SATURATE : |
| arm_compute::ConvertPolicy::WRAP; |
| |
| const arm_compute::ActivationLayerInfo activationInfo = ConvertActivationDescriptorToAclActivationLayerInfo( |
| activationDescriptor); |
| |
| // At the time of writing, configure() will fail if a rounding policy other than TO_ZERO is supplied to it, |
| // when providing a scale of 1.0 for F32 tensors, even though the provided rounding policy appears to be |
| // ignored for F32 tensors. |
| return arm_compute::CLPixelWiseMultiplication::validate(&aclInput1, |
| &aclInput2, |
| &aclOutput, |
| 1.0f, |
| convertPolicy, |
| arm_compute::RoundingPolicy::TO_ZERO, |
| activationInfo); |
| } |
| |
| |
| ClMultiplicationWorkload::ClMultiplicationWorkload(const MultiplicationQueueDescriptor& descriptor, |
| const WorkloadInfo& info, |
| const arm_compute::CLCompileContext& clCompileContext) |
| : ClBaseWorkload<MultiplicationQueueDescriptor>(descriptor, info) |
| { |
| m_Data.ValidateInputsOutputs("ClMultiplicationWorkload", 2, 1); |
| |
| arm_compute::ICLTensor& input0 = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); |
| arm_compute::ICLTensor& input1 = static_cast<IClTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); |
| arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); |
| |
| auto convertPolicy = (IsQuantizedType(info.m_InputTensorInfos[0].GetDataType()) || |
| IsQuantizedType(info.m_InputTensorInfos[1].GetDataType())) ? |
| arm_compute::ConvertPolicy::SATURATE : |
| arm_compute::ConvertPolicy::WRAP; |
| |
| const arm_compute::ActivationLayerInfo activationInfo = ConvertAdditionalInfoToAclActivationLayerInfo(descriptor); |
| |
| { |
| ARMNN_SCOPED_PROFILING_EVENT(Compute::Undefined, "ClMultiplicationWorkload_configure"); |
| // Construct |
| m_PixelWiseMultiplication.configure(clCompileContext, |
| &input0, |
| &input1, |
| &output, |
| 1.0f, |
| convertPolicy, |
| arm_compute::RoundingPolicy::TO_NEAREST_EVEN, |
| activationInfo); |
| } |
| } |
| |
| void ClMultiplicationWorkload::Execute() const |
| { |
| ARMNN_SCOPED_PROFILING_EVENT_CL_GUID("ClMultiplicationWorkload_Execute", this->GetGuid()); |
| RunClFunction(m_PixelWiseMultiplication, CHECK_LOCATION()); |
| } |
| |
| } //namespace armnn |