diff options
Diffstat (limited to 'src/backends/reference/workloads/RefLogicalBinaryWorkload.cpp')
| -rw-r--r-- | src/backends/reference/workloads/RefLogicalBinaryWorkload.cpp | 31 |
1 files changed, 15 insertions, 16 deletions
diff --git a/src/backends/reference/workloads/RefLogicalBinaryWorkload.cpp b/src/backends/reference/workloads/RefLogicalBinaryWorkload.cpp index 1b4e8f9aa0..f187e0ca31 100644 --- a/src/backends/reference/workloads/RefLogicalBinaryWorkload.cpp +++ b/src/backends/reference/workloads/RefLogicalBinaryWorkload.cpp @@ -22,32 +22,31 @@ RefLogicalBinaryWorkload::RefLogicalBinaryWorkload(const LogicalBinaryQueueDescr : BaseWorkload<LogicalBinaryQueueDescriptor>(desc, info) {} -void RefLogicalBinaryWorkload::PostAllocationConfigure() +void RefLogicalBinaryWorkload::Execute() const { - const TensorInfo& inputInfo0 = GetTensorInfo(m_Data.m_Inputs[0]); - const TensorInfo& inputInfo1 = GetTensorInfo(m_Data.m_Inputs[1]); - const TensorInfo& outputInfo = GetTensorInfo(m_Data.m_Outputs[0]); + Execute(m_Data.m_Inputs, m_Data.m_Outputs); +} - m_Input0 = MakeDecoder<InType>(inputInfo0); - m_Input1 = MakeDecoder<InType>(inputInfo1); - m_Output = MakeEncoder<OutType>(outputInfo); +void RefLogicalBinaryWorkload::ExecuteAsync(WorkingMemDescriptor &workingMemDescriptor) +{ + Execute(workingMemDescriptor.m_Inputs, workingMemDescriptor.m_Outputs); } -void RefLogicalBinaryWorkload::Execute() const +void RefLogicalBinaryWorkload::Execute(std::vector<ITensorHandle*> inputs, std::vector<ITensorHandle*> outputs) const { ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefLogicalBinaryWorkload_Execute"); - const TensorInfo& inputInfo0 = GetTensorInfo(m_Data.m_Inputs[0]); - const TensorInfo& inputInfo1 = GetTensorInfo(m_Data.m_Inputs[1]); - const TensorInfo& outputInfo = GetTensorInfo(m_Data.m_Outputs[0]); + const TensorInfo& inputInfo0 = GetTensorInfo(inputs[0]); + const TensorInfo& inputInfo1 = GetTensorInfo(inputs[1]); + const TensorInfo& outputInfo = GetTensorInfo(outputs[0]); const TensorShape& inShape0 = inputInfo0.GetShape(); const TensorShape& inShape1 = inputInfo1.GetShape(); const TensorShape& outShape = outputInfo.GetShape(); - m_Input0->Reset(m_Data.m_Inputs[0]->Map()); - m_Input1->Reset(m_Data.m_Inputs[1]->Map()); - m_Output->Reset(m_Data.m_Outputs[0]->Map()); + std::unique_ptr<Decoder<InType>> input0 = MakeDecoder<InType>(inputInfo0, inputs[0]->Map()); + std::unique_ptr<Decoder<InType>> input1 = MakeDecoder<InType>(inputInfo1, inputs[1]->Map()); + std::unique_ptr<Encoder<OutType>> output = MakeEncoder<OutType>(outputInfo, outputs[0]->Map()); using AndFunction = LogicalBinaryFunction<std::logical_and<bool>>; using OrFunction = LogicalBinaryFunction<std::logical_or<bool>>; @@ -56,12 +55,12 @@ void RefLogicalBinaryWorkload::Execute() const { case LogicalBinaryOperation::LogicalAnd: { - AndFunction(inShape0, inShape1, outShape, *m_Input0, *m_Input1, *m_Output); + AndFunction(inShape0, inShape1, outShape, *input0, *input1, *output); break; } case LogicalBinaryOperation::LogicalOr: { - OrFunction(inShape0, inShape1, outShape, *m_Input0, *m_Input1, *m_Output); + OrFunction(inShape0, inShape1, outShape, *input0, *input1, *output); break; } default: |