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-rw-r--r--src/backends/cl/workloads/ClConvolution2dWorkload.cpp34
-rw-r--r--src/backends/cl/workloads/ClConvolution2dWorkload.hpp1
-rw-r--r--src/backends/neon/workloads/NeonConvolution2dWorkload.cpp36
-rw-r--r--src/backends/neon/workloads/NeonConvolution2dWorkload.hpp1
-rw-r--r--src/backends/reference/workloads/RefConvolution2dWorkload.cpp33
5 files changed, 95 insertions, 10 deletions
diff --git a/src/backends/cl/workloads/ClConvolution2dWorkload.cpp b/src/backends/cl/workloads/ClConvolution2dWorkload.cpp
index 5c731aa0a1..b3df7ce0b1 100644
--- a/src/backends/cl/workloads/ClConvolution2dWorkload.cpp
+++ b/src/backends/cl/workloads/ClConvolution2dWorkload.cpp
@@ -120,6 +120,23 @@ ClConvolution2dWorkload::ClConvolution2dWorkload(const Convolution2dQueueDescrip
aclDilationInfo,
isFastMathEnabled);
+ // Add details for profiling output
+ std::string workloadName = "ClConvolution2dWorkload_Execute_Guid" + std::to_string(this->GetGuid());
+
+ WorkloadInfo detailsInfo;
+
+ detailsInfo.m_InputTensorInfos = info.m_InputTensorInfos;
+ detailsInfo.m_OutputTensorInfos = info.m_OutputTensorInfos;
+ detailsInfo.m_WeightsTensorInfo = armnn::Optional<armnn::TensorInfo>(descriptor.m_Weight->GetTensorInfo());
+ detailsInfo.m_ConvolutionMethod = armnn::Optional<std::string>(GetConvolutionMethodString());
+ if (descriptor.m_Parameters.m_BiasEnabled)
+ {
+ detailsInfo.m_BiasTensorInfo = armnn::Optional<armnn::TensorInfo>(descriptor.m_Bias->GetTensorInfo());
+ }
+
+ // Report Profiling Details
+ ARMNN_REPORT_PROFILING_WORKLOAD_DESC(workloadName, descriptor.m_Parameters, detailsInfo);
+
InitializeArmComputeClTensorData(*m_KernelTensor, m_Data.m_Weight);
if (m_BiasTensor)
@@ -144,6 +161,23 @@ arm_compute::ConvolutionMethod ClConvolution2dWorkload::GetConvolutionMethod() c
return m_ConvolutionMethod;
}
+std::string ClConvolution2dWorkload::GetConvolutionMethodString()
+{
+ switch ( m_ConvolutionMethod )
+ {
+ case arm_compute::ConvolutionMethod::FFT:
+ return "FFT";
+ case arm_compute::ConvolutionMethod::DIRECT:
+ return "Direct";
+ case arm_compute::ConvolutionMethod::GEMM:
+ return "GEMM";
+ case arm_compute::ConvolutionMethod::WINOGRAD:
+ return "Winograd";
+ default:
+ return "Unknown";
+ }
+}
+
void ClConvolution2dWorkload::FreeUnusedTensors()
{
FreeTensorIfUnused(m_KernelTensor);
diff --git a/src/backends/cl/workloads/ClConvolution2dWorkload.hpp b/src/backends/cl/workloads/ClConvolution2dWorkload.hpp
index d0f7a5b251..49d7f773df 100644
--- a/src/backends/cl/workloads/ClConvolution2dWorkload.hpp
+++ b/src/backends/cl/workloads/ClConvolution2dWorkload.hpp
@@ -37,6 +37,7 @@ public:
void Execute() const override;
arm_compute::ConvolutionMethod GetConvolutionMethod() const;
+ std::string GetConvolutionMethodString();
private:
mutable arm_compute::CLConvolutionLayer m_ConvolutionLayer;
diff --git a/src/backends/neon/workloads/NeonConvolution2dWorkload.cpp b/src/backends/neon/workloads/NeonConvolution2dWorkload.cpp
index 32af3f853a..1e12e13357 100644
--- a/src/backends/neon/workloads/NeonConvolution2dWorkload.cpp
+++ b/src/backends/neon/workloads/NeonConvolution2dWorkload.cpp
@@ -74,8 +74,6 @@ NeonConvolution2dWorkload::NeonConvolution2dWorkload(
m_Data.ValidateInputsOutputs("NeonConvolution2dWorkload", 1, 1);
- // todo: check tensor shapes match.
-
arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
@@ -120,6 +118,23 @@ NeonConvolution2dWorkload::NeonConvolution2dWorkload(
activationInfo,
isFastMathEnabled);
+ // Add details for profiling output
+ std::string workloadName = "NeonConvolution2dWorkload_Execute_Guid" + std::to_string(this->GetGuid());
+
+ WorkloadInfo detailsInfo;
+
+ detailsInfo.m_InputTensorInfos = info.m_InputTensorInfos;
+ detailsInfo.m_OutputTensorInfos = info.m_OutputTensorInfos;
+ detailsInfo.m_WeightsTensorInfo = armnn::Optional<armnn::TensorInfo>(descriptor.m_Weight->GetTensorInfo());
+ detailsInfo.m_ConvolutionMethod = armnn::Optional<std::string>(GetConvolutionMethodString());
+ if (descriptor.m_Parameters.m_BiasEnabled)
+ {
+ detailsInfo.m_BiasTensorInfo = armnn::Optional<armnn::TensorInfo>(descriptor.m_Bias->GetTensorInfo());
+ }
+
+ // Report Profiling Details
+ ARMNN_REPORT_PROFILING_WORKLOAD_DESC(workloadName, descriptor.m_Parameters, detailsInfo);
+
m_ConvolutionLayer.reset(convolutionLayer.release());
ARMNN_ASSERT(m_ConvolutionLayer);
@@ -146,6 +161,23 @@ arm_compute::ConvolutionMethod NeonConvolution2dWorkload::GetConvolutionMethod()
return m_ConvolutionMethod;
}
+std::string NeonConvolution2dWorkload::GetConvolutionMethodString()
+{
+ switch ( m_ConvolutionMethod )
+ {
+ case arm_compute::ConvolutionMethod::FFT:
+ return "FFT";
+ case arm_compute::ConvolutionMethod::DIRECT:
+ return "Direct";
+ case arm_compute::ConvolutionMethod::GEMM:
+ return "GEMM";
+ case arm_compute::ConvolutionMethod::WINOGRAD:
+ return "Winograd";
+ default:
+ return "Unknown";
+ }
+}
+
void NeonConvolution2dWorkload::FreeUnusedTensors()
{
FreeTensorIfUnused(m_KernelTensor);
diff --git a/src/backends/neon/workloads/NeonConvolution2dWorkload.hpp b/src/backends/neon/workloads/NeonConvolution2dWorkload.hpp
index 4b6e58ce41..4b4c07ae87 100644
--- a/src/backends/neon/workloads/NeonConvolution2dWorkload.hpp
+++ b/src/backends/neon/workloads/NeonConvolution2dWorkload.hpp
@@ -37,6 +37,7 @@ public:
void Execute() const override;
arm_compute::ConvolutionMethod GetConvolutionMethod() const;
+ std::string GetConvolutionMethodString();
private:
std::unique_ptr<arm_compute::IFunction> m_ConvolutionLayer;
diff --git a/src/backends/reference/workloads/RefConvolution2dWorkload.cpp b/src/backends/reference/workloads/RefConvolution2dWorkload.cpp
index 5ae1af8967..7c331715d8 100644
--- a/src/backends/reference/workloads/RefConvolution2dWorkload.cpp
+++ b/src/backends/reference/workloads/RefConvolution2dWorkload.cpp
@@ -13,18 +13,33 @@
namespace armnn
{
RefConvolution2dWorkload::RefConvolution2dWorkload(
- const Convolution2dQueueDescriptor& descriptor, const WorkloadInfo& info)
- : BaseWorkload<Convolution2dQueueDescriptor>(descriptor, info)
+ const Convolution2dQueueDescriptor& descriptor, const WorkloadInfo& info)
+ : BaseWorkload<Convolution2dQueueDescriptor>(descriptor, info)
{
- m_Weight = std::make_unique<ScopedTensorHandle>(*(descriptor.m_Weight));
+ // Construct params for reporting operator details
+ std::string workloadName = "RefConvolution2dWorkload_Execute_Guid" + std::to_string(this->GetGuid());
+
+ WorkloadInfo detailsInfo;
+ detailsInfo.m_InputTensorInfos = info.m_InputTensorInfos;
+ detailsInfo.m_OutputTensorInfos = info.m_OutputTensorInfos;
+ detailsInfo.m_WeightsTensorInfo = armnn::Optional<armnn::TensorInfo>(descriptor.m_Weight->GetTensorInfo());
+ if (descriptor.m_Parameters.m_BiasEnabled)
+ {
+ detailsInfo.m_BiasTensorInfo = armnn::Optional<armnn::TensorInfo>(descriptor.m_Bias->GetTensorInfo());
+ }
+
+ // Report Profiling Details
+ ARMNN_REPORT_PROFILING_WORKLOAD_DESC(workloadName, descriptor.m_Parameters, detailsInfo);
+
+ m_Weight = std::make_unique<ScopedTensorHandle>(*( descriptor.m_Weight ));
const TensorInfo& rFilterInfo = m_Weight->GetTensorInfo();
m_FilterShape = rFilterInfo.GetShape();
m_FilterDecoder = MakeDecoder<float>(rFilterInfo, m_Weight.get()->Map(true));
- if (descriptor.m_Parameters.m_BiasEnabled)
+ if ( descriptor.m_Parameters.m_BiasEnabled )
{
- m_Bias = std::make_unique<ScopedTensorHandle>(*(descriptor.m_Bias));
+ m_Bias = std::make_unique<ScopedTensorHandle>(*( descriptor.m_Bias ));
const TensorInfo& biasInfo = m_Bias->GetTensorInfo();
m_BiasDecoder = MakeDecoder<float>(biasInfo, m_Bias->Map(true));
}
@@ -35,13 +50,15 @@ void RefConvolution2dWorkload::Execute() const
Execute(m_Data.m_Inputs, m_Data.m_Outputs);
}
-void RefConvolution2dWorkload::ExecuteAsync(WorkingMemDescriptor &workingMemDescriptor)
+void RefConvolution2dWorkload::ExecuteAsync(WorkingMemDescriptor& workingMemDescriptor)
{
Execute(workingMemDescriptor.m_Inputs, workingMemDescriptor.m_Outputs);
}
-void RefConvolution2dWorkload::Execute(std::vector<ITensorHandle*> inputs, std::vector<ITensorHandle*> outputs) const {
- ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefConvolution2dWorkload_Execute");
+void RefConvolution2dWorkload::Execute(std::vector<ITensorHandle*> inputs, std::vector<ITensorHandle*> outputs) const
+{
+ std::string workloadName = "RefConvolutionWorkload_Execute_Guid" + std::to_string(this->GetGuid());
+ ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, workloadName);
std::unique_ptr<Decoder<float>> inputDecoder = MakeDecoder<float>(GetTensorInfo(inputs[0]), inputs[0]->Map());
std::unique_ptr<Encoder<float>> outputEncoder = MakeEncoder<float>(GetTensorInfo(outputs[0]), outputs[0]->Map());
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-08 08:44:21 +0000