IVGCVSW-1951 Remove type templating from ClConvolution2dWorkload
Change-Id: Iaa99500bfa8cea846f57636590698f9c8a8c2de0
diff --git a/src/backends/cl/ClLayerSupport.cpp b/src/backends/cl/ClLayerSupport.cpp
index a17997b..e23c70e 100644
--- a/src/backends/cl/ClLayerSupport.cpp
+++ b/src/backends/cl/ClLayerSupport.cpp
@@ -19,7 +19,7 @@
#include "workloads/ClBatchNormalizationFloatWorkload.hpp"
#include "workloads/ClConvertFp16ToFp32Workload.hpp"
#include "workloads/ClConvertFp32ToFp16Workload.hpp"
-#include "workloads/ClConvolution2dBaseWorkload.hpp"
+#include "workloads/ClConvolution2dWorkload.hpp"
#include "workloads/ClDepthwiseConvolutionBaseWorkload.hpp"
#include "workloads/ClDivisionFloatWorkload.hpp"
#include "workloads/ClL2NormalizationFloatWorkload.hpp"
diff --git a/src/backends/cl/ClWorkloadFactory.cpp b/src/backends/cl/ClWorkloadFactory.cpp
index bf17382..2e07445 100644
--- a/src/backends/cl/ClWorkloadFactory.cpp
+++ b/src/backends/cl/ClWorkloadFactory.cpp
@@ -144,8 +144,7 @@
std::unique_ptr<armnn::IWorkload> ClWorkloadFactory::CreateConvolution2d(const Convolution2dQueueDescriptor& descriptor,
const WorkloadInfo& info) const
{
- return MakeWorkload<ClConvolution2dFloatWorkload, ClConvolution2dUint8Workload>(descriptor, info,
- m_MemoryManager.GetIntraLayerManager());
+ return std::make_unique<ClConvolution2dWorkload>(descriptor, info, m_MemoryManager.GetIntraLayerManager());
}
std::unique_ptr<IWorkload> ClWorkloadFactory::CreateDepthwiseConvolution2d(
diff --git a/src/backends/cl/backend.mk b/src/backends/cl/backend.mk
index 81540cc..c86940c 100644
--- a/src/backends/cl/backend.mk
+++ b/src/backends/cl/backend.mk
@@ -21,9 +21,7 @@
workloads/ClConstantUint8Workload.cpp \
workloads/ClConvertFp16ToFp32Workload.cpp \
workloads/ClConvertFp32ToFp16Workload.cpp \
- workloads/ClConvolution2dBaseWorkload.cpp \
- workloads/ClConvolution2dFloatWorkload.cpp \
- workloads/ClConvolution2dUint8Workload.cpp \
+ workloads/ClConvolution2dWorkload.cpp \
workloads/ClDepthwiseConvolutionBaseWorkload.cpp \
workloads/ClDepthwiseConvolutionFloatWorkload.cpp \
workloads/ClDepthwiseConvolutionUint8Workload.cpp \
diff --git a/src/backends/cl/workloads/CMakeLists.txt b/src/backends/cl/workloads/CMakeLists.txt
index 9c48dc9..5a1653e 100644
--- a/src/backends/cl/workloads/CMakeLists.txt
+++ b/src/backends/cl/workloads/CMakeLists.txt
@@ -23,12 +23,8 @@
ClConvertFp16ToFp32Workload.hpp
ClConvertFp32ToFp16Workload.cpp
ClConvertFp32ToFp16Workload.hpp
- ClConvolution2dBaseWorkload.cpp
- ClConvolution2dBaseWorkload.hpp
- ClConvolution2dFloatWorkload.cpp
- ClConvolution2dFloatWorkload.hpp
- ClConvolution2dUint8Workload.cpp
- ClConvolution2dUint8Workload.hpp
+ ClConvolution2dWorkload.cpp
+ ClConvolution2dWorkload.hpp
ClDepthwiseConvolutionBaseWorkload.cpp
ClDepthwiseConvolutionBaseWorkload.hpp
ClDepthwiseConvolutionFloatWorkload.cpp
diff --git a/src/backends/cl/workloads/ClConvolution2dBaseWorkload.cpp b/src/backends/cl/workloads/ClConvolution2dBaseWorkload.cpp
deleted file mode 100644
index 58699a8..0000000
--- a/src/backends/cl/workloads/ClConvolution2dBaseWorkload.cpp
+++ /dev/null
@@ -1,48 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#include "ClConvolution2dBaseWorkload.hpp"
-#include <backends/cl/ClLayerSupport.hpp>
-#include <backends/cl/ClTensorHandle.hpp>
-#include <backends/aclCommon/ArmComputeUtils.hpp>
-#include <backends/aclCommon/ArmComputeTensorUtils.hpp>
-
-#include <arm_compute/runtime/CL/functions/CLConvolutionLayer.h>
-
-namespace armnn
-{
-using namespace armcomputetensorutils;
-
-arm_compute::Status ClConvolution2dWorkloadValidate(const TensorInfo& input,
- const TensorInfo& output,
- const Convolution2dDescriptor& descriptor,
- const TensorInfo& weights,
- const boost::optional<TensorInfo>& biases)
-{
- 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);
-
- arm_compute::TensorInfo aclBiasesInfo;
- arm_compute::TensorInfo *optionalAclBiasesInfo = nullptr;
-
- if (descriptor.m_BiasEnabled)
- {
- BOOST_ASSERT(biases.is_initialized());
-
- aclBiasesInfo = BuildArmComputeTensorInfo(biases.get(), descriptor.m_DataLayout);
- optionalAclBiasesInfo = &aclBiasesInfo;
- }
-
- arm_compute::PadStrideInfo layerInfo = BuildArmComputePadStrideInfo(descriptor);
-
- return arm_compute::CLConvolutionLayer::validate(&aclInputInfo,
- &aclWeightsInfo,
- optionalAclBiasesInfo,
- &aclOutputInfo,
- layerInfo);
-}
-
-}
diff --git a/src/backends/cl/workloads/ClConvolution2dBaseWorkload.hpp b/src/backends/cl/workloads/ClConvolution2dBaseWorkload.hpp
deleted file mode 100644
index a983dba..0000000
--- a/src/backends/cl/workloads/ClConvolution2dBaseWorkload.hpp
+++ /dev/null
@@ -1,24 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#pragma once
-
-#include <armnn/Tensor.hpp>
-#include <armnn/Descriptors.hpp>
-
-#include <boost/optional.hpp>
-
-#include <arm_compute/core/Error.h>
-
-namespace armnn
-{
-
-arm_compute::Status ClConvolution2dWorkloadValidate(const TensorInfo& input,
- const TensorInfo& output,
- const Convolution2dDescriptor& descriptor,
- const TensorInfo& weights,
- const boost::optional<TensorInfo>& biases);
-
-} //namespace armnn
diff --git a/src/backends/cl/workloads/ClConvolution2dFloatWorkload.cpp b/src/backends/cl/workloads/ClConvolution2dFloatWorkload.cpp
deleted file mode 100644
index 0d70ddb..0000000
--- a/src/backends/cl/workloads/ClConvolution2dFloatWorkload.cpp
+++ /dev/null
@@ -1,85 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#include "ClConvolution2dFloatWorkload.hpp"
-#include <backends/cl/ClTensorHandle.hpp>
-#include <backends/CpuTensorHandle.hpp>
-#include <backends/aclCommon/ArmComputeTensorUtils.hpp>
-#include <backends/cl/ClLayerSupport.hpp>
-
-#include "ClWorkloadUtils.hpp"
-
-namespace armnn
-{
-using namespace armcomputetensorutils;
-
-ClConvolution2dFloatWorkload::ClConvolution2dFloatWorkload(const Convolution2dQueueDescriptor& descriptor,
- const WorkloadInfo& info, std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager)
- : FloatWorkload<Convolution2dQueueDescriptor>(descriptor, info)
- , m_ConvolutionLayer(memoryManager)
-{
-
- // todo: check tensor shapes match.
- const TensorInfo& weightInfo = m_Data.m_Weight->GetTensorInfo();
-
- m_KernelTensor = std::make_unique<arm_compute::CLTensor>();
- BuildArmComputeTensor(*m_KernelTensor, weightInfo, m_Data.m_Parameters.m_DataLayout);
-
- arm_compute::PadStrideInfo padStrideInfo(m_Data.m_Parameters.m_StrideX,
- m_Data.m_Parameters.m_StrideY,
- m_Data.m_Parameters.m_PadLeft,
- m_Data.m_Parameters.m_PadRight,
- m_Data.m_Parameters.m_PadTop,
- m_Data.m_Parameters.m_PadBottom,
- arm_compute::DimensionRoundingType::FLOOR);
-
- if (m_Data.m_Parameters.m_BiasEnabled)
- {
- m_BiasTensor = std::make_unique<arm_compute::CLTensor>();
- BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo(), m_Data.m_Parameters.m_DataLayout);
- }
-
- m_Data.ValidateInputsOutputs("ClConvolution2dFloat32Workload", 1, 1);
-
- arm_compute::ICLTensor& input = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->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);
- output.info()->set_data_layout(aclDataLayout);
-
- m_ConvolutionLayer.configure(&input,
- m_KernelTensor.get(),
- m_BiasTensor.get(),
- &output,
- padStrideInfo);
-
- InitializeArmComputeClTensorData(*m_KernelTensor, m_Data.m_Weight);
-
- if (m_BiasTensor)
- {
- InitializeArmComputeClTensorData(*m_BiasTensor, m_Data.m_Bias);
- }
-
- // 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();
- FreeUnusedTensors();
-}
-
-void ClConvolution2dFloatWorkload::Execute() const
-{
- ARMNN_SCOPED_PROFILING_EVENT_CL("ClConvolution2dFloat32Workload_Execute");
-
- m_ConvolutionLayer.run();
-}
-
-void ClConvolution2dFloatWorkload::FreeUnusedTensors()
-{
- FreeTensorIfUnused(m_KernelTensor);
- FreeTensorIfUnused(m_BiasTensor);
-}
-
-} //namespace armnn
diff --git a/src/backends/cl/workloads/ClConvolution2dFloatWorkload.hpp b/src/backends/cl/workloads/ClConvolution2dFloatWorkload.hpp
deleted file mode 100644
index 1f9710e..0000000
--- a/src/backends/cl/workloads/ClConvolution2dFloatWorkload.hpp
+++ /dev/null
@@ -1,35 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#pragma once
-
-#include <backends/Workload.hpp>
-
-#include <arm_compute/runtime/CL/CLFunctions.h>
-#include <arm_compute/runtime/MemoryManagerOnDemand.h>
-
-#include <memory>
-
-namespace armnn
-{
-
-class ClConvolution2dFloatWorkload : public FloatWorkload<Convolution2dQueueDescriptor>
-{
-public:
- ClConvolution2dFloatWorkload(const Convolution2dQueueDescriptor& descriptor, const WorkloadInfo& info,
- std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager);
- void Execute() const override;
-
-private:
- mutable arm_compute::CLConvolutionLayer m_ConvolutionLayer;
-
- std::unique_ptr<arm_compute::CLTensor> m_KernelTensor;
- std::unique_ptr<arm_compute::CLTensor> m_BiasTensor;
-
- void FreeUnusedTensors();
-};
-
-} //namespace armnn
-
diff --git a/src/backends/cl/workloads/ClConvolution2dUint8Workload.cpp b/src/backends/cl/workloads/ClConvolution2dUint8Workload.cpp
deleted file mode 100644
index 4f8da34..0000000
--- a/src/backends/cl/workloads/ClConvolution2dUint8Workload.cpp
+++ /dev/null
@@ -1,85 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#include "ClConvolution2dUint8Workload.hpp"
-#include <backends/cl/ClTensorHandle.hpp>
-#include <backends/CpuTensorHandle.hpp>
-#include <backends/aclCommon/ArmComputeTensorUtils.hpp>
-#include <backends/cl/ClLayerSupport.hpp>
-
-#include "ClWorkloadUtils.hpp"
-
-namespace armnn
-{
-using namespace armcomputetensorutils;
-
-ClConvolution2dUint8Workload::ClConvolution2dUint8Workload(const Convolution2dQueueDescriptor& descriptor,
- const WorkloadInfo& info, std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager)
- : Uint8Workload<Convolution2dQueueDescriptor>(descriptor, info)
- , m_ConvolutionLayer(memoryManager)
-{
- // todo: check tensor shapes match
- const TensorInfo& weightInfo = m_Data.m_Weight->GetTensorInfo();
-
- m_KernelTensor = std::make_unique<arm_compute::CLTensor>();
- BuildArmComputeTensor(*m_KernelTensor, weightInfo, m_Data.m_Parameters.m_DataLayout);
-
- arm_compute::PadStrideInfo padStrideInfo(m_Data.m_Parameters.m_StrideX,
- m_Data.m_Parameters.m_StrideY,
- m_Data.m_Parameters.m_PadLeft,
- m_Data.m_Parameters.m_PadRight,
- m_Data.m_Parameters.m_PadTop,
- m_Data.m_Parameters.m_PadBottom,
- arm_compute::DimensionRoundingType::FLOOR);
-
- if (m_Data.m_Parameters.m_BiasEnabled)
- {
- m_BiasTensor = std::make_unique<arm_compute::CLTensor>();
- BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo(), m_Data.m_Parameters.m_DataLayout);
- }
-
- m_Data.ValidateInputsOutputs("ClConvolution2dUint8Workload", 1, 1);
-
- arm_compute::ICLTensor& input = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->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);
- output.info()->set_data_layout(aclDataLayout);
-
- m_ConvolutionLayer.configure(&input,
- m_KernelTensor.get(),
- m_BiasTensor.get(),
- &output,
- padStrideInfo);
-
- InitializeArmComputeClTensorData(*m_KernelTensor, m_Data.m_Weight);
-
- if (m_BiasTensor)
- {
- InitializeArmComputeClTensorData(*m_BiasTensor, m_Data.m_Bias);
- }
-
- // 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();
- FreeUnusedTensors();
-}
-
-void ClConvolution2dUint8Workload::Execute() const
-{
- ARMNN_SCOPED_PROFILING_EVENT_CL("ClConvolution2dUint8Workload_Execute");
-
- m_ConvolutionLayer.run();
-}
-
-void ClConvolution2dUint8Workload::FreeUnusedTensors()
-{
- FreeTensorIfUnused(m_KernelTensor);
- FreeTensorIfUnused(m_BiasTensor);
-}
-
-} //namespace armnn
-
diff --git a/src/backends/cl/workloads/ClConvolution2dUint8Workload.hpp b/src/backends/cl/workloads/ClConvolution2dUint8Workload.hpp
deleted file mode 100644
index 1720ec9..0000000
--- a/src/backends/cl/workloads/ClConvolution2dUint8Workload.hpp
+++ /dev/null
@@ -1,35 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#pragma once
-
-#include <backends/Workload.hpp>
-
-#include <arm_compute/runtime/CL/CLFunctions.h>
-#include <arm_compute/runtime/MemoryManagerOnDemand.h>
-
-#include <memory>
-
-namespace armnn
-{
-
-class ClConvolution2dUint8Workload : public Uint8Workload<Convolution2dQueueDescriptor>
-{
-public:
- ClConvolution2dUint8Workload(const Convolution2dQueueDescriptor& descriptor, const WorkloadInfo& info,
- std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager);
- void Execute() const override;
-
-private:
- mutable arm_compute::CLConvolutionLayer m_ConvolutionLayer;
-
- std::unique_ptr<arm_compute::CLTensor> m_KernelTensor;
- std::unique_ptr<arm_compute::CLTensor> m_BiasTensor;
-
- void FreeUnusedTensors();
-};
-
-} //namespace armnn
-
diff --git a/src/backends/cl/workloads/ClConvolution2dWorkload.cpp b/src/backends/cl/workloads/ClConvolution2dWorkload.cpp
new file mode 100644
index 0000000..521711b
--- /dev/null
+++ b/src/backends/cl/workloads/ClConvolution2dWorkload.cpp
@@ -0,0 +1,119 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "ClConvolution2dWorkload.hpp"
+
+#include "ClWorkloadUtils.hpp"
+
+#include <backends/cl/ClLayerSupport.hpp>
+#include <backends/cl/ClTensorHandle.hpp>
+#include <backends/cl/ClLayerSupport.hpp>
+#include <backends/aclCommon/ArmComputeUtils.hpp>
+#include <backends/aclCommon/ArmComputeTensorUtils.hpp>
+#include <backends/CpuTensorHandle.hpp>
+
+#include <arm_compute/runtime/CL/functions/CLConvolutionLayer.h>
+
+namespace armnn
+{
+using namespace armcomputetensorutils;
+
+arm_compute::Status ClConvolution2dWorkloadValidate(const TensorInfo& input,
+ const TensorInfo& output,
+ const Convolution2dDescriptor& descriptor,
+ const TensorInfo& weights,
+ const boost::optional<TensorInfo>& biases)
+{
+ 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);
+
+ arm_compute::TensorInfo aclBiasesInfo;
+ arm_compute::TensorInfo *optionalAclBiasesInfo = nullptr;
+
+ if (descriptor.m_BiasEnabled)
+ {
+ BOOST_ASSERT(biases.is_initialized());
+
+ aclBiasesInfo = BuildArmComputeTensorInfo(biases.get(), descriptor.m_DataLayout);
+ optionalAclBiasesInfo = &aclBiasesInfo;
+ }
+
+ arm_compute::PadStrideInfo layerInfo = BuildArmComputePadStrideInfo(descriptor);
+
+ return arm_compute::CLConvolutionLayer::validate(&aclInputInfo,
+ &aclWeightsInfo,
+ optionalAclBiasesInfo,
+ &aclOutputInfo,
+ layerInfo);
+}
+
+ClConvolution2dWorkload::ClConvolution2dWorkload(const Convolution2dQueueDescriptor& descriptor,
+ const WorkloadInfo& info, std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager)
+ : BaseWorkload<Convolution2dQueueDescriptor>(descriptor, info)
+ , m_ConvolutionLayer(memoryManager)
+{
+ // todo: check tensor shapes match.
+ const TensorInfo& weightInfo = m_Data.m_Weight->GetTensorInfo();
+
+ m_KernelTensor = std::make_unique<arm_compute::CLTensor>();
+ BuildArmComputeTensor(*m_KernelTensor, weightInfo, m_Data.m_Parameters.m_DataLayout);
+
+ arm_compute::PadStrideInfo padStrideInfo(m_Data.m_Parameters.m_StrideX,
+ m_Data.m_Parameters.m_StrideY,
+ m_Data.m_Parameters.m_PadLeft,
+ m_Data.m_Parameters.m_PadRight,
+ m_Data.m_Parameters.m_PadTop,
+ m_Data.m_Parameters.m_PadBottom,
+ arm_compute::DimensionRoundingType::FLOOR);
+
+ if (m_Data.m_Parameters.m_BiasEnabled)
+ {
+ m_BiasTensor = std::make_unique<arm_compute::CLTensor>();
+ 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<IClTensorHandle*>(m_Data.m_Inputs[0])->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);
+ output.info()->set_data_layout(aclDataLayout);
+
+ m_ConvolutionLayer.configure(&input,
+ m_KernelTensor.get(),
+ m_BiasTensor.get(),
+ &output,
+ padStrideInfo);
+
+ InitializeArmComputeClTensorData(*m_KernelTensor, m_Data.m_Weight);
+
+ if (m_BiasTensor)
+ {
+ InitializeArmComputeClTensorData(*m_BiasTensor, m_Data.m_Bias);
+ }
+
+ // 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();
+ FreeUnusedTensors();
+}
+
+void ClConvolution2dWorkload::Execute() const
+{
+ ARMNN_SCOPED_PROFILING_EVENT_CL("ClConvolution2dWorkload_Execute");
+
+ m_ConvolutionLayer.run();
+}
+
+void ClConvolution2dWorkload::FreeUnusedTensors()
+{
+ FreeTensorIfUnused(m_KernelTensor);
+ FreeTensorIfUnused(m_BiasTensor);
+}
+
+} //namespace armnn
diff --git a/src/backends/cl/workloads/ClConvolution2dWorkload.hpp b/src/backends/cl/workloads/ClConvolution2dWorkload.hpp
new file mode 100644
index 0000000..14a39f3
--- /dev/null
+++ b/src/backends/cl/workloads/ClConvolution2dWorkload.hpp
@@ -0,0 +1,46 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include <armnn/Tensor.hpp>
+#include <armnn/Descriptors.hpp>
+
+#include <backends/Workload.hpp>
+
+#include <arm_compute/runtime/CL/functions/CLConvolutionLayer.h>
+#include <arm_compute/runtime/MemoryManagerOnDemand.h>
+
+#include <boost/optional.hpp>
+
+#include <memory>
+
+namespace armnn
+{
+
+arm_compute::Status ClConvolution2dWorkloadValidate(const TensorInfo& input,
+ const TensorInfo& output,
+ const Convolution2dDescriptor& descriptor,
+ const TensorInfo& weights,
+ const boost::optional<TensorInfo>& biases);
+
+class ClConvolution2dWorkload : public BaseWorkload<Convolution2dQueueDescriptor>
+{
+public:
+ ClConvolution2dWorkload(const Convolution2dQueueDescriptor& descriptor, const WorkloadInfo& info,
+ std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager);
+ void Execute() const override;
+
+private:
+ mutable arm_compute::CLConvolutionLayer m_ConvolutionLayer;
+
+ std::unique_ptr<arm_compute::CLTensor> m_KernelTensor;
+ std::unique_ptr<arm_compute::CLTensor> m_BiasTensor;
+
+ void FreeUnusedTensors();
+};
+
+} //namespace armnn
+
diff --git a/src/backends/cl/workloads/ClWorkloads.hpp b/src/backends/cl/workloads/ClWorkloads.hpp
index 439ad2d..0ef8fd3 100644
--- a/src/backends/cl/workloads/ClWorkloads.hpp
+++ b/src/backends/cl/workloads/ClWorkloads.hpp
@@ -12,8 +12,7 @@
#include "ClBatchNormalizationFloatWorkload.hpp"
#include "ClConstantFloatWorkload.hpp"
#include "ClConstantUint8Workload.hpp"
-#include "ClConvolution2dFloatWorkload.hpp"
-#include "ClConvolution2dUint8Workload.hpp"
+#include "ClConvolution2dWorkload.hpp"
#include "ClDepthwiseConvolutionFloatWorkload.hpp"
#include "ClDepthwiseConvolutionUint8Workload.hpp"
#include "ClDivisionFloatWorkload.hpp"
diff --git a/src/backends/test/CreateWorkloadCl.cpp b/src/backends/test/CreateWorkloadCl.cpp
index fb28ce1..e81f844 100644
--- a/src/backends/test/CreateWorkloadCl.cpp
+++ b/src/backends/test/CreateWorkloadCl.cpp
@@ -199,13 +199,12 @@
BOOST_TEST((outputHandle->GetTensor().info()->data_type() == arm_compute::DataType::F16));
}
-template <typename Convolution2dWorkloadType, typename armnn::DataType DataType>
+template <typename armnn::DataType DataType>
static void ClConvolution2dWorkloadTest()
{
Graph graph;
ClWorkloadFactory factory;
- auto workload = CreateConvolution2dWorkloadTest<Convolution2dWorkloadType, DataType>
- (factory, graph);
+ auto workload = CreateConvolution2dWorkloadTest<ClConvolution2dWorkload, DataType>(factory, graph);
// Checks that outputs and inputs are as we expect them (see definition of CreateConvolution2dWorkloadTest).
Convolution2dQueueDescriptor queueDescriptor = workload->GetData();
@@ -217,22 +216,20 @@
BOOST_AUTO_TEST_CASE(CreateConvolution2dFloatWorkload)
{
- ClConvolution2dWorkloadTest<ClConvolution2dFloatWorkload, armnn::DataType::Float32>();
+ ClConvolution2dWorkloadTest<armnn::DataType::Float32>();
}
BOOST_AUTO_TEST_CASE(CreateConvolution2dFloat16Workload)
{
- ClConvolution2dWorkloadTest<ClConvolution2dFloatWorkload, armnn::DataType::Float16>();
+ ClConvolution2dWorkloadTest<armnn::DataType::Float16>();
}
-
-template <typename Convolution2dWorkloadType, typename armnn::DataType DataType>
+template <typename armnn::DataType DataType>
static void ClDirectConvolution2dWorkloadTest()
{
Graph graph;
ClWorkloadFactory factory;
- auto workload = CreateDirectConvolution2dWorkloadTest<Convolution2dWorkloadType, DataType>(
- factory, graph);
+ auto workload = CreateDirectConvolution2dWorkloadTest<ClConvolution2dWorkload, DataType>(factory, graph);
// Checks that outputs and inputs are as we expect them (see definition of CreateDirectConvolution2dWorkloadTest).
Convolution2dQueueDescriptor queueDescriptor = workload->GetData();
@@ -244,17 +241,17 @@
BOOST_AUTO_TEST_CASE(CreateDirectConvolution2dFloatWorkload)
{
- ClDirectConvolution2dWorkloadTest<ClConvolution2dFloatWorkload, armnn::DataType::Float32>();
+ ClDirectConvolution2dWorkloadTest<armnn::DataType::Float32>();
}
BOOST_AUTO_TEST_CASE(CreateDirectConvolution2dFloat16Workload)
{
- ClDirectConvolution2dWorkloadTest<ClConvolution2dFloatWorkload, armnn::DataType::Float16>();
+ ClDirectConvolution2dWorkloadTest<armnn::DataType::Float16>();
}
BOOST_AUTO_TEST_CASE(CreateDirectConvolution2dUint8Workload)
{
- ClDirectConvolution2dWorkloadTest<ClConvolution2dUint8Workload, armnn::DataType::QuantisedAsymm8>();
+ ClDirectConvolution2dWorkloadTest<armnn::DataType::QuantisedAsymm8>();
}
template <typename FullyConnectedWorkloadType, typename armnn::DataType DataType>