14 #include <arm_compute/runtime/NEON/functions/NEConvolutionLayer.h>
22 using namespace armcomputetensorutils;
29 bool isFastMathEnabled,
32 const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.
m_DataLayout);
33 const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.
m_DataLayout);
34 arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.
m_DataLayout);
35 aclWeightsInfo.set_are_values_constant(weights.
IsConstant());
37 const arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(descriptor.
m_DilationX,
40 arm_compute::TensorInfo aclBiasesInfo;
41 arm_compute::TensorInfo *optionalAclBiasesInfo =
nullptr;
47 if (!biases.
value().IsConstant())
50 "ArmNN NeonConvolution2dWorkload does not support non constant bias."};
52 aclBiasesInfo = BuildArmComputeTensorInfo(biases.
value(), descriptor.
m_DataLayout);
53 aclBiasesInfo.set_are_values_constant(biases.
value().IsConstant());
54 optionalAclBiasesInfo = &aclBiasesInfo;
57 arm_compute::PadStrideInfo layerInfo = BuildArmComputePadStrideInfo(descriptor);
60 activationDescriptor);
62 return arm_compute::NEConvolutionLayer::validate(&aclInputInfo,
64 optionalAclBiasesInfo,
67 arm_compute::WeightsInfo(),
76 std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager,
77 const bool isFastMathEnabled)
80 using arm_compute::NEConvolutionLayer;
85 arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(
m_Data.
m_Inputs[0])->GetTensor();
86 arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(
m_Data.
m_Outputs[0])->GetTensor();
89 input.info()->set_data_layout(aclDataLayout);
90 output.info()->set_data_layout(aclDataLayout);
92 m_KernelTensor = std::make_unique<arm_compute::Tensor>();
96 m_BiasTensor = std::make_unique<arm_compute::Tensor>();
100 arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(
m_Data.
m_Parameters);
107 auto convolutionLayer = std::make_unique<arm_compute::NEConvolutionLayer>(memoryManager);
108 convolutionLayer->configure(&input,
109 m_KernelTensor.get(),
113 arm_compute::WeightsInfo(),
118 m_ConvolutionMethod =
119 convolutionLayer->get_convolution_method(input.info(),
120 m_KernelTensor->info(),
123 arm_compute::WeightsInfo(),
147 m_ConvolutionLayer.reset(convolutionLayer.release());
150 m_KernelTensorInfo =
info.m_InputTensorInfos[1];
154 m_BiasTensorInfo =
info.m_InputTensorInfos[2];
170 m_ConvolutionLayer->prepare();
171 FreeTensorIfUnused(m_KernelTensor);
172 FreeTensorIfUnused(m_BiasTensor);
175 m_ConvolutionLayer->run();
180 return m_ConvolutionMethod;