IVGCVSW-5328-5329 Fuse Activation
* Added Fused Activation Optimization to both CL and Neon backends.
* Added Fused Activation support to all the CL and Neon workloads
that support it.
* Changed ProfilingTest network to be a Convolution layer
followed by an Abs layer rather than an Activation layer.
* Added IBackendInternal::OptimizeSubgraphView function that can accept a
ModelOptions.
* Network will now call OptimizeSubgraphView passing in the ModelOptions.
Signed-off-by: Keith Davis <keith.davis@arm.com>
Signed-off-by: Mike Kelly <mike.kelly@arm.com>
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: Ib536ac3cbafc7d9b35c139ad9a65b7735262cd9d
diff --git a/src/backends/cl/workloads/ClAdditionWorkload.cpp b/src/backends/cl/workloads/ClAdditionWorkload.cpp
index 18e2400..7e75a04 100644
--- a/src/backends/cl/workloads/ClAdditionWorkload.cpp
+++ b/src/backends/cl/workloads/ClAdditionWorkload.cpp
@@ -8,6 +8,7 @@
#include <cl/ClTensorHandle.hpp>
#include <backendsCommon/CpuTensorHandle.hpp>
#include <aclCommon/ArmComputeTensorUtils.hpp>
+#include <aclCommon/ArmComputeUtils.hpp>
#include "ClWorkloadUtils.hpp"
@@ -26,7 +27,10 @@
arm_compute::ICLTensor& input0 = static_cast<IClTensorHandle*>(this->m_Data.m_Inputs[0])->GetTensor();
arm_compute::ICLTensor& input1 = static_cast<IClTensorHandle*>(this->m_Data.m_Inputs[1])->GetTensor();
arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(this->m_Data.m_Outputs[0])->GetTensor();
- m_Layer.configure(&input0, &input1, &output, g_AclConvertPolicy);
+
+ const arm_compute::ActivationLayerInfo activationInfo = ConvertAdditionalInfoToAclActivationLayerInfo(descriptor);
+
+ m_Layer.configure(&input0, &input1, &output, g_AclConvertPolicy, activationInfo);
}
void ClAdditionWorkload::Execute() const
@@ -37,16 +41,21 @@
arm_compute::Status ClAdditionValidate(const TensorInfo& input0,
const TensorInfo& input1,
- const TensorInfo& output)
+ const TensorInfo& output,
+ const ActivationDescriptor* activationDescriptor)
{
const arm_compute::TensorInfo aclInput0Info = BuildArmComputeTensorInfo(input0);
const arm_compute::TensorInfo aclInput1Info = BuildArmComputeTensorInfo(input1);
const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output);
+ const arm_compute::ActivationLayerInfo activationInfo = ConvertActivationDescriptorToAclActivationLayerInfo(
+ activationDescriptor);
+
const arm_compute::Status aclStatus = arm_compute::CLArithmeticAddition::validate(&aclInput0Info,
&aclInput1Info,
&aclOutputInfo,
- g_AclConvertPolicy);
+ g_AclConvertPolicy,
+ activationInfo);
return aclStatus;
}