17 #include <arm_compute/runtime/CL/functions/CLConvolutionLayer.h> 21 using namespace armcomputetensorutils;
28 bool isFastMathEnabled,
31 const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.
m_DataLayout);
32 const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.
m_DataLayout);
33 const arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.
m_DataLayout);
35 const arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(descriptor.
m_DilationX,
38 arm_compute::TensorInfo aclBiasesInfo;
39 arm_compute::TensorInfo *optionalAclBiasesInfo =
nullptr;
45 aclBiasesInfo = BuildArmComputeTensorInfo(biases.
value(), descriptor.
m_DataLayout);
46 optionalAclBiasesInfo = &aclBiasesInfo;
49 arm_compute::PadStrideInfo layerInfo = BuildArmComputePadStrideInfo(descriptor);
52 activationDescriptor);
54 return arm_compute::CLConvolutionLayer::validate(&aclInputInfo,
56 optionalAclBiasesInfo,
59 arm_compute::WeightsInfo(),
67 std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager,
68 const arm_compute::CLCompileContext& clCompileContext,
69 const bool isFastMathEnabled)
71 , m_ConvolutionLayer(memoryManager)
76 m_KernelTensor = std::make_unique<arm_compute::CLTensor>();
84 m_BiasTensor = std::make_unique<arm_compute::CLTensor>();
94 input.info()->set_data_layout(aclDataLayout);
95 output.info()->set_data_layout(aclDataLayout);
97 arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(
m_Data.
m_Parameters);
101 m_ConvolutionLayer.configure(clCompileContext,
103 m_KernelTensor.get(),
107 arm_compute::WeightsInfo(),
112 m_ConvolutionMethod =
113 m_ConvolutionLayer.get_convolution_method(input.info(),
114 m_KernelTensor->info(),
117 arm_compute::WeightsInfo(),
119 arm_compute::CLScheduler::get().target(),
132 m_ConvolutionLayer.prepare();
144 return m_ConvolutionMethod;
147 void ClConvolution2dWorkload::FreeUnusedTensors()
149 FreeTensorIfUnused(m_KernelTensor);
150 FreeTensorIfUnused(m_BiasTensor);
bool m_BiasEnabled
Enable/disable bias.
const ConstCpuTensorHandle * m_Bias
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
void InitializeArmComputeClTensorData(arm_compute::CLTensor &clTensor, const ConstCpuTensorHandle *handle)
#define ARMNN_SCOPED_PROFILING_EVENT_CL(name)
void RunClFunction(arm_compute::IFunction &function, const CheckLocation &location)
A Convolution2dDescriptor for the Convolution2dLayer.
const Convolution2dQueueDescriptor m_Data
arm_compute::ActivationLayerInfo ConvertAdditionalInfoToAclActivationLayerInfo(const QueueDescriptor &queueDescriptor)
void ValidateInputsOutputs(const std::string &descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const
Copyright (c) 2021 ARM Limited and Contributors.
arm_compute::Status ClConvolution2dWorkloadValidate(const TensorInfo &input, const TensorInfo &output, const Convolution2dDescriptor &descriptor, const TensorInfo &weights, const Optional< TensorInfo > &biases, bool isFastMathEnabled, const ActivationDescriptor *activationDescriptor)
uint32_t m_DilationY
Dilation along y axis.
LayerDescriptor m_Parameters
arm_compute::ConvolutionMethod GetConvolutionMethod() const
ClConvolution2dWorkload(const Convolution2dQueueDescriptor &descriptor, const WorkloadInfo &info, std::shared_ptr< arm_compute::MemoryManagerOnDemand > &memoryManager, const arm_compute::CLCompileContext &clCompileContext, const bool isFastMathEnabled=false)
const ConstCpuTensorHandle * m_Weight
bool has_value() const noexcept
#define ARMNN_ASSERT(COND)
An ActivationDescriptor for the ActivationLayer.
uint32_t m_DilationX
Dilation along x axis.
std::vector< ITensorHandle * > m_Outputs
void Execute() const override
Contains information about inputs and outputs to a layer.
std::vector< ITensorHandle * > m_Inputs
const TensorInfo & GetTensorInfo() const
arm_compute::ActivationLayerInfo ConvertActivationDescriptorToAclActivationLayerInfo(const ActivationDescriptor &actDesc)