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author | Mike Kelly <mike.kelly@arm.com> | 2020-11-12 10:58:48 +0000 |
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committer | Jim Flynn <jim.flynn@arm.com> | 2020-11-13 14:25:30 +0000 |
commit | 07810fc2fcdd34db74222d90cc73ef12a88e7b78 (patch) | |
tree | 8becef8453674822d079815b06ae37310b97d2cf /src/backends/neon/workloads/NeonBatchNormalizationWorkload.cpp | |
parent | 8502adeafbbb1db0acefa62560d93453e38dcadb (diff) | |
download | armnn-07810fc2fcdd34db74222d90cc73ef12a88e7b78.tar.gz |
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
Diffstat (limited to 'src/backends/neon/workloads/NeonBatchNormalizationWorkload.cpp')
-rw-r--r-- | src/backends/neon/workloads/NeonBatchNormalizationWorkload.cpp | 17 |
1 files changed, 14 insertions, 3 deletions
diff --git a/src/backends/neon/workloads/NeonBatchNormalizationWorkload.cpp b/src/backends/neon/workloads/NeonBatchNormalizationWorkload.cpp index ff777dbf9b..33480faf69 100644 --- a/src/backends/neon/workloads/NeonBatchNormalizationWorkload.cpp +++ b/src/backends/neon/workloads/NeonBatchNormalizationWorkload.cpp @@ -8,7 +8,10 @@ #include "NeonWorkloadUtils.hpp" #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <aclCommon/ArmComputeUtils.hpp> + #include <armnn/utility/PolymorphicDowncast.hpp> + #include <backendsCommon/CpuTensorHandle.hpp> #include <arm_compute/runtime/NEON/functions/NEBatchNormalizationLayer.h> @@ -24,7 +27,8 @@ arm_compute::Status NeonBatchNormalizationValidate(const TensorInfo& input, const TensorInfo& var, const TensorInfo& beta, const TensorInfo& gamma, - const BatchNormalizationDescriptor& descriptor) + const BatchNormalizationDescriptor& descriptor, + const ActivationDescriptor* activationDescriptor) { const arm_compute::TensorInfo aclInputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(input, descriptor.m_DataLayout); @@ -39,13 +43,17 @@ arm_compute::Status NeonBatchNormalizationValidate(const TensorInfo& input, const arm_compute::TensorInfo aclGammaInfo = armcomputetensorutils::BuildArmComputeTensorInfo(gamma, descriptor.m_DataLayout); + const arm_compute::ActivationLayerInfo activationInfo = ConvertActivationDescriptorToAclActivationLayerInfo( + activationDescriptor); + return arm_compute::NEBatchNormalizationLayer::validate(&aclInputInfo, &aclOutputInfo, &aclMeanInfo, &aclVarInfo, &aclBetaInfo, &aclGammaInfo, - descriptor.m_Eps); + descriptor.m_Eps, + activationInfo); } NeonBatchNormalizationWorkload::NeonBatchNormalizationWorkload( @@ -73,6 +81,8 @@ NeonBatchNormalizationWorkload::NeonBatchNormalizationWorkload( m_Beta = std::make_unique<arm_compute::Tensor>(); BuildArmComputeTensor(*m_Beta, m_Data.m_Beta->GetTensorInfo()); + const arm_compute::ActivationLayerInfo activationInfo = ConvertAdditionalInfoToAclActivationLayerInfo(descriptor); + auto layer = std::make_unique<arm_compute::NEBatchNormalizationLayer>(); layer->configure(&input, &output, @@ -80,7 +90,8 @@ NeonBatchNormalizationWorkload::NeonBatchNormalizationWorkload( m_Variance.get(), m_Beta.get(), m_Gamma.get(), - m_Data.m_Parameters.m_Eps); + m_Data.m_Parameters.m_Eps, + activationInfo); m_Layer.reset(layer.release()); InitializeArmComputeTensorData(*m_Mean, m_Data.m_Mean); |