diff options
Diffstat (limited to 'src/backends/cl/workloads/ClLstmFloatWorkload.cpp')
| -rw-r--r-- | src/backends/cl/workloads/ClLstmFloatWorkload.cpp | 435 |
1 files changed, 0 insertions, 435 deletions
diff --git a/src/backends/cl/workloads/ClLstmFloatWorkload.cpp b/src/backends/cl/workloads/ClLstmFloatWorkload.cpp deleted file mode 100644 index 2f3ba75275..0000000000 --- a/src/backends/cl/workloads/ClLstmFloatWorkload.cpp +++ /dev/null @@ -1,435 +0,0 @@ -// -// Copyright © 2017 Arm Ltd. All rights reserved. -// SPDX-License-Identifier: MIT -// - -#include "ClLstmFloatWorkload.hpp" -#include <cl/ClTensorHandle.hpp> -#include <backendsCommon/CpuTensorHandle.hpp> -#include <cl/ClLayerSupport.hpp> -#include <aclCommon/ArmComputeTensorUtils.hpp> - -#include <arm_compute/runtime/CL/functions/CLLSTMLayer.h> - -#include "ClWorkloadUtils.hpp" - -namespace armnn -{ -using namespace armcomputetensorutils; - -ClLstmFloatWorkload::ClLstmFloatWorkload(const LstmQueueDescriptor &descriptor, const WorkloadInfo &info) - : FloatWorkload<LstmQueueDescriptor>(descriptor, info) -{ - arm_compute::LSTMParams<arm_compute::ICLTensor> lstm_param; - - // Basic parameters - m_InputToForgetWeightsTensor = std::make_unique<arm_compute::CLTensor>(); - BuildArmComputeTensor(*m_InputToForgetWeightsTensor, m_Data.m_InputToForgetWeights->GetTensorInfo()); - - m_InputToCellWeightsTensor = std::make_unique<arm_compute::CLTensor>(); - BuildArmComputeTensor(*m_InputToCellWeightsTensor, m_Data.m_InputToCellWeights->GetTensorInfo()); - - m_InputToOutputWeightsTensor = std::make_unique<arm_compute::CLTensor>(); - BuildArmComputeTensor(*m_InputToOutputWeightsTensor, m_Data.m_InputToOutputWeights->GetTensorInfo()); - - m_RecurrentToForgetWeightsTensor = std::make_unique<arm_compute::CLTensor>(); - BuildArmComputeTensor(*m_RecurrentToForgetWeightsTensor, m_Data.m_RecurrentToForgetWeights->GetTensorInfo()); - - m_RecurrentToCellWeightsTensor = std::make_unique<arm_compute::CLTensor>(); - BuildArmComputeTensor(*m_RecurrentToCellWeightsTensor, m_Data.m_RecurrentToCellWeights->GetTensorInfo()); - - m_RecurrentToOutputWeightsTensor = std::make_unique<arm_compute::CLTensor>(); - BuildArmComputeTensor(*m_RecurrentToOutputWeightsTensor, m_Data.m_RecurrentToOutputWeights->GetTensorInfo()); - - m_ForgetGateBiasTensor = std::make_unique<arm_compute::CLTensor>(); - BuildArmComputeTensor(*m_ForgetGateBiasTensor, m_Data.m_ForgetGateBias->GetTensorInfo()); - - m_CellBiasTensor = std::make_unique<arm_compute::CLTensor>(); - BuildArmComputeTensor(*m_CellBiasTensor, m_Data.m_CellBias->GetTensorInfo()); - - m_OutputGateBiasTensor = std::make_unique<arm_compute::CLTensor>(); - BuildArmComputeTensor(*m_OutputGateBiasTensor, m_Data.m_OutputGateBias->GetTensorInfo()); - - // for future reference: check the AndroidNN API for the logic here - if (!m_Data.m_Parameters.m_CifgEnabled) - { - m_InputToInputWeightsTensor = std::make_unique<arm_compute::CLTensor>(); - BuildArmComputeTensor(*m_InputToInputWeightsTensor, m_Data.m_InputToInputWeights->GetTensorInfo()); - - m_RecurrentToInputWeightsTensor = std::make_unique<arm_compute::CLTensor>(); - BuildArmComputeTensor(*m_RecurrentToInputWeightsTensor, m_Data.m_RecurrentToInputWeights->GetTensorInfo()); - - m_CellToInputWeightsTensor = std::make_unique<arm_compute::CLTensor>(); - if (m_Data.m_CellToInputWeights != nullptr) - { - BuildArmComputeTensor(*m_CellToInputWeightsTensor, m_Data.m_CellToInputWeights->GetTensorInfo()); - } - - m_InputGateBiasTensor = std::make_unique<arm_compute::CLTensor>(); - BuildArmComputeTensor(*m_InputGateBiasTensor, m_Data.m_InputGateBias->GetTensorInfo()); - - lstm_param.set_cifg_params(m_InputToInputWeightsTensor.get(), - m_RecurrentToInputWeightsTensor.get(), - m_Data.m_CellToInputWeights != nullptr ? m_CellToInputWeightsTensor.get() : nullptr, - m_InputGateBiasTensor.get()); - } - - if (m_Data.m_Parameters.m_ProjectionEnabled) - { - m_ProjectionWeightsTensor = std::make_unique<arm_compute::CLTensor>(); - BuildArmComputeTensor(*m_ProjectionWeightsTensor, m_Data.m_ProjectionWeights->GetTensorInfo()); - - m_ProjectionBiasTensor = std::make_unique<arm_compute::CLTensor>(); - if (m_Data.m_ProjectionBias != nullptr) - { - BuildArmComputeTensor(*m_ProjectionBiasTensor, m_Data.m_ProjectionBias->GetTensorInfo()); - } - - lstm_param.set_projection_params(m_ProjectionWeightsTensor.get(), - m_Data.m_ProjectionBias != nullptr ? m_ProjectionBiasTensor.get() : nullptr); - } - - if (m_Data.m_Parameters.m_PeepholeEnabled) - { - m_CellToForgetWeightsTensor = std::make_unique<arm_compute::CLTensor>(); - BuildArmComputeTensor(*m_CellToForgetWeightsTensor, m_Data.m_CellToForgetWeights->GetTensorInfo()); - - m_CellToOutputWeightsTensor = std::make_unique<arm_compute::CLTensor>(); - BuildArmComputeTensor(*m_CellToOutputWeightsTensor, m_Data.m_CellToOutputWeights->GetTensorInfo()); - - lstm_param.set_peephole_params(m_CellToForgetWeightsTensor.get(), m_CellToOutputWeightsTensor.get()); - } - - if (m_Data.m_Parameters.m_LayerNormEnabled) - { - m_InputLayerNormWeightsTensor = std::make_unique<arm_compute::CLTensor>(); - m_ForgetLayerNormWeightsTensor = std::make_unique<arm_compute::CLTensor>(); - m_CellLayerNormWeightsTensor = std::make_unique<arm_compute::CLTensor>(); - m_OutputLayerNormWeightsTensor = std::make_unique<arm_compute::CLTensor>(); - - if (!m_Data.m_Parameters.m_CifgEnabled) - { - BuildArmComputeTensor(*m_InputLayerNormWeightsTensor, m_Data.m_InputLayerNormWeights->GetTensorInfo()); - } - BuildArmComputeTensor(*m_ForgetLayerNormWeightsTensor, m_Data.m_ForgetLayerNormWeights->GetTensorInfo()); - BuildArmComputeTensor(*m_CellLayerNormWeightsTensor, m_Data.m_CellLayerNormWeights->GetTensorInfo()); - BuildArmComputeTensor(*m_OutputLayerNormWeightsTensor, m_Data.m_OutputLayerNormWeights->GetTensorInfo()); - - lstm_param.set_layer_normalization_params(m_Data.m_Parameters.m_CifgEnabled ? nullptr : - m_InputLayerNormWeightsTensor.get(), - m_ForgetLayerNormWeightsTensor.get(), - m_CellLayerNormWeightsTensor.get(), - m_OutputLayerNormWeightsTensor.get()); - } - - const arm_compute::ICLTensor& input = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - const arm_compute::ICLTensor& output_state_in = static_cast<IClTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); - const arm_compute::ICLTensor& cell_state_in = static_cast<IClTensorHandle*>(m_Data.m_Inputs[2])->GetTensor(); - - arm_compute::ICLTensor& output_state_out = static_cast<IClTensorHandle*>(m_Data.m_Outputs[1])->GetTensor(); - arm_compute::ICLTensor& cell_state_out = static_cast<IClTensorHandle*>(m_Data.m_Outputs[2])->GetTensor(); - arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(m_Data.m_Outputs[3])->GetTensor(); - - // Get the batch_size and the num_units from the cellStateIn dimensions - const TensorInfo& inputTensorInfo = info.m_InputTensorInfos[2]; - const unsigned int batch_size = boost::numeric_cast<unsigned int>(inputTensorInfo.GetShape()[0]); - const unsigned int num_units = boost::numeric_cast<unsigned int>(inputTensorInfo.GetShape()[1]); - - m_ScratchBuffer = std::make_unique<arm_compute::CLTensor>(); - if (m_Data.m_Parameters.m_CifgEnabled) - { - // 2D tensor with dimensions [num_units * 3, batch_size] with CIFG - armnn::TensorInfo scratchBuffer1({ batch_size, num_units * 3 }, DataType::Float32); - BuildArmComputeTensor(*m_ScratchBuffer, scratchBuffer1); - } - else - { - // scratch_buffer [num_units * 4, batch_size] without CIFG - armnn::TensorInfo scratchBuffer2({ batch_size, num_units * 4 }, DataType::Float32); - BuildArmComputeTensor(*m_ScratchBuffer, scratchBuffer2); - } - - float cell_threshold = m_Data.m_Parameters.m_ClippingThresCell; - float projection_threshold = m_Data.m_Parameters.m_ClippingThresProj; - - // for preparing the object for the class ActivationLayerInfo, we need to consider 5 situations - arm_compute::ActivationLayerInfo activationLayerInfo; - if (m_Data.m_Parameters.m_ActivationFunc == 0) - { - // no activation, do nothing - } - else if (m_Data.m_Parameters.m_ActivationFunc == 1) - { - activationLayerInfo = arm_compute::ActivationLayerInfo( - arm_compute::ActivationLayerInfo::ActivationFunction::RELU); - } - else if (m_Data.m_Parameters.m_ActivationFunc == 3) - { - activationLayerInfo = arm_compute::ActivationLayerInfo( - arm_compute::ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.0); - } - else if (m_Data.m_Parameters.m_ActivationFunc == 4) - { - activationLayerInfo = arm_compute::ActivationLayerInfo( - arm_compute::ActivationLayerInfo::ActivationFunction::TANH, 1.0, 1.0); - } - else if (m_Data.m_Parameters.m_ActivationFunc == 6) - { - activationLayerInfo = arm_compute::ActivationLayerInfo( - arm_compute::ActivationLayerInfo::ActivationFunction::LOGISTIC); - } - else - { - throw armnn::Exception("Wrong Type of Activation Function!"); - } - - m_LstmLayer.configure(&input, m_InputToForgetWeightsTensor.get(), m_InputToCellWeightsTensor.get(), - m_InputToOutputWeightsTensor.get(), m_RecurrentToForgetWeightsTensor.get(), - m_RecurrentToCellWeightsTensor.get(), m_RecurrentToOutputWeightsTensor.get(), - m_ForgetGateBiasTensor.get(), m_CellBiasTensor.get(), m_OutputGateBiasTensor.get(), - &output_state_in, &cell_state_in, m_ScratchBuffer.get(), &output_state_out, - &cell_state_out, &output, lstm_param, activationLayerInfo, - cell_threshold, projection_threshold); - - armcomputetensorutils::InitialiseArmComputeTensorEmpty(*m_ScratchBuffer); - - InitializeArmComputeClTensorData(*m_InputToForgetWeightsTensor, m_Data.m_InputToForgetWeights); - InitializeArmComputeClTensorData(*m_InputToCellWeightsTensor, m_Data.m_InputToCellWeights); - InitializeArmComputeClTensorData(*m_InputToOutputWeightsTensor, m_Data.m_InputToOutputWeights); - InitializeArmComputeClTensorData(*m_RecurrentToForgetWeightsTensor, m_Data.m_RecurrentToForgetWeights); - InitializeArmComputeClTensorData(*m_RecurrentToCellWeightsTensor, m_Data.m_RecurrentToCellWeights); - InitializeArmComputeClTensorData(*m_RecurrentToOutputWeightsTensor, m_Data.m_RecurrentToOutputWeights); - InitializeArmComputeClTensorData(*m_ForgetGateBiasTensor, m_Data.m_ForgetGateBias); - InitializeArmComputeClTensorData(*m_CellBiasTensor, m_Data.m_CellBias); - InitializeArmComputeClTensorData(*m_OutputGateBiasTensor, m_Data.m_OutputGateBias); - - if (!m_Data.m_Parameters.m_CifgEnabled) - { - InitializeArmComputeClTensorData(*m_InputToInputWeightsTensor, m_Data.m_InputToInputWeights); - InitializeArmComputeClTensorData(*m_RecurrentToInputWeightsTensor, m_Data.m_RecurrentToInputWeights); - if (m_Data.m_CellToInputWeights != nullptr) - { - InitializeArmComputeClTensorData(*m_CellToInputWeightsTensor, m_Data.m_CellToInputWeights); - } - InitializeArmComputeClTensorData(*m_InputGateBiasTensor, m_Data.m_InputGateBias); - } - - if (m_Data.m_Parameters.m_ProjectionEnabled) - { - InitializeArmComputeClTensorData(*m_ProjectionWeightsTensor, m_Data.m_ProjectionWeights); - if (m_Data.m_ProjectionBias != nullptr) - { - InitializeArmComputeClTensorData(*m_ProjectionBiasTensor, m_Data.m_ProjectionBias); - } - } - - if (m_Data.m_Parameters.m_PeepholeEnabled) - { - InitializeArmComputeClTensorData(*m_CellToForgetWeightsTensor, m_Data.m_CellToForgetWeights); - InitializeArmComputeClTensorData(*m_CellToOutputWeightsTensor, m_Data.m_CellToOutputWeights); - } - - if (m_Data.m_Parameters.m_LayerNormEnabled) - { - if (!m_Data.m_Parameters.m_CifgEnabled) - { - InitializeArmComputeClTensorData(*m_InputLayerNormWeightsTensor, m_Data.m_InputLayerNormWeights); - } - - InitializeArmComputeClTensorData(*m_ForgetLayerNormWeightsTensor, m_Data.m_ForgetLayerNormWeights); - InitializeArmComputeClTensorData(*m_CellLayerNormWeightsTensor, m_Data.m_CellLayerNormWeights); - InitializeArmComputeClTensorData(*m_OutputLayerNormWeightsTensor, m_Data.m_OutputLayerNormWeights); - } - - // Force Compute Library to perform the necessary copying and reshaping, after which - // delete all the input tensors that will no longer be needed - m_LstmLayer.prepare(); - FreeUnusedTensors(); -} - -void ClLstmFloatWorkload::Execute() const -{ - ARMNN_SCOPED_PROFILING_EVENT_CL("ClLstmFloatWorkload_Execute"); - RunClFunction(m_LstmLayer, CHECK_LOCATION()); -} - -arm_compute::Status ClLstmFloatWorkloadValidate(const TensorInfo& input, const TensorInfo& outputStateIn, - const TensorInfo& cellStateIn, const TensorInfo& scratchBuffer, - const TensorInfo& outputStateOut, const TensorInfo& cellStateOut, - const TensorInfo& output, const LstmDescriptor& descriptor, - const LstmInputParamsInfo& paramsInfo) -{ - arm_compute::LSTMParams<arm_compute::ITensorInfo> lstm_params_info; - - // The inputs and the outputs - const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input); - const arm_compute::TensorInfo aclOutputStateInInfo = BuildArmComputeTensorInfo(outputStateIn); - const arm_compute::TensorInfo aclCellStateInInfo = BuildArmComputeTensorInfo(cellStateIn); - const arm_compute::TensorInfo aclScratchBufferInfo = BuildArmComputeTensorInfo(scratchBuffer); - const arm_compute::TensorInfo aclOutputStateOutInfo = BuildArmComputeTensorInfo(outputStateOut); - const arm_compute::TensorInfo aclCellStateOutInfo = BuildArmComputeTensorInfo(cellStateOut); - const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output); - - // Basic parameters - const arm_compute::TensorInfo aclInputToForgetWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.GetInputToForgetWeights()); - const arm_compute::TensorInfo aclInputToCellWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.GetInputToCellWeights()); - const arm_compute::TensorInfo aclInputToOutputWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.GetInputToOutputWeights()); - const arm_compute::TensorInfo aclRecurrentToForgetWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToForgetWeights()); - const arm_compute::TensorInfo aclRecurrentToCellWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToCellWeights()); - const arm_compute::TensorInfo aclRecurrentToOutputWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToOutputWeights()); - const arm_compute::TensorInfo aclForgetGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetForgetGateBias()); - const arm_compute::TensorInfo aclCellBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellBias()); - const arm_compute::TensorInfo aclOutputGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetOutputGateBias()); - - arm_compute::TensorInfo aclInputToInputWeightsInfo; - arm_compute::TensorInfo aclRecurrentToInputWeightsInfo; - arm_compute::TensorInfo aclCellToInputWeightsInfo; - arm_compute::TensorInfo aclInputGateBiasInfo; - arm_compute::TensorInfo aclProjectionWeightsInfo; - arm_compute::TensorInfo aclProjectionBiasInfo; - arm_compute::TensorInfo aclCellToForgetWeightsInfo; - arm_compute::TensorInfo aclCellToOutputWeightsInfo; - arm_compute::TensorInfo aclInputLayerNormWeightsInfo; - arm_compute::TensorInfo aclForgetLayerNormWeightsInfo; - arm_compute::TensorInfo aclCellLayerNormWeightsInfo; - arm_compute::TensorInfo aclOutputLayerNormWeightsInfo; - - if (!descriptor.m_CifgEnabled) - { - aclInputToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetInputToInputWeights()); - aclRecurrentToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToInputWeights()); - - if (paramsInfo.m_CellToInputWeights != nullptr) - { - aclCellToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellToInputWeights()); - } - aclInputGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetInputGateBias()); - lstm_params_info.set_cifg_params(&aclInputToInputWeightsInfo, &aclRecurrentToInputWeightsInfo, - paramsInfo.m_CellToInputWeights != nullptr ? - &aclCellToInputWeightsInfo: nullptr, - &aclInputGateBiasInfo); - } - - if (descriptor.m_ProjectionEnabled) - { - aclProjectionWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetProjectionWeights()); - - if (paramsInfo.m_ProjectionBias != nullptr) - { - aclProjectionBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetInputGateBias()); - } - lstm_params_info.set_projection_params(&aclProjectionWeightsInfo, - paramsInfo.m_ProjectionBias != nullptr ? - &aclProjectionBiasInfo: nullptr); - } - - if (descriptor.m_PeepholeEnabled) - { - aclCellToForgetWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellToForgetWeights()); - aclCellToOutputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellToOutputWeights()); - lstm_params_info.set_peephole_params(&aclCellToForgetWeightsInfo, &aclCellToOutputWeightsInfo); - } - - float cell_threshold = descriptor.m_ClippingThresCell; - float projection_threshold = descriptor.m_ClippingThresProj; - - // for preparing the object for the class ActivationLayerInfo, we need to consider 5 situations - arm_compute::ActivationLayerInfo activationLayerInfo; - if (descriptor.m_ActivationFunc == 0) - { - // no activation, do nothing - } - else if (descriptor.m_ActivationFunc == 1) - { - activationLayerInfo = arm_compute::ActivationLayerInfo( - arm_compute::ActivationLayerInfo::ActivationFunction::RELU); - } - else if (descriptor.m_ActivationFunc == 3) - { - activationLayerInfo = arm_compute::ActivationLayerInfo( - arm_compute::ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.0); - } - else if (descriptor.m_ActivationFunc == 4) - { - activationLayerInfo = arm_compute::ActivationLayerInfo( - arm_compute::ActivationLayerInfo::ActivationFunction::TANH, 1.0, 1.0); - } - else if (descriptor.m_ActivationFunc == 6) - { - activationLayerInfo = arm_compute::ActivationLayerInfo( - arm_compute::ActivationLayerInfo::ActivationFunction::LOGISTIC); - } - else - { - throw armnn::Exception("Wrong Type of Activation Function!"); - } - - if (descriptor.m_LayerNormEnabled) - { - if (!descriptor.m_CifgEnabled) - { - aclInputLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetInputLayerNormWeights()); - } - - aclForgetLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetForgetLayerNormWeights()); - - aclCellLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellLayerNormWeights()); - - aclOutputLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetOutputLayerNormWeights()); - - lstm_params_info.set_layer_normalization_params(descriptor.m_CifgEnabled ? - nullptr : &aclInputLayerNormWeightsInfo, - &aclForgetLayerNormWeightsInfo, - &aclCellLayerNormWeightsInfo, - &aclOutputLayerNormWeightsInfo); - } - - return arm_compute::CLLSTMLayer::validate(&aclInputInfo, &aclInputToForgetWeightsInfo, - &aclInputToCellWeightsInfo, - &aclInputToOutputWeightsInfo, - &aclRecurrentToForgetWeightsInfo, - &aclRecurrentToCellWeightsInfo, - &aclRecurrentToOutputWeightsInfo, - &aclForgetGateBiasInfo, - &aclCellBiasInfo, - &aclOutputGateBiasInfo, - &aclOutputStateInInfo, &aclCellStateInInfo, - &aclScratchBufferInfo, &aclOutputStateOutInfo, - &aclCellStateOutInfo, &aclOutputInfo, - lstm_params_info, activationLayerInfo, - cell_threshold, projection_threshold); -} - -void ClLstmFloatWorkload::FreeUnusedTensors() -{ - FreeTensorIfUnused(m_InputToInputWeightsTensor); - FreeTensorIfUnused(m_InputToForgetWeightsTensor); - FreeTensorIfUnused(m_InputToCellWeightsTensor); - FreeTensorIfUnused(m_InputToOutputWeightsTensor); - FreeTensorIfUnused(m_RecurrentToInputWeightsTensor); - FreeTensorIfUnused(m_RecurrentToForgetWeightsTensor); - FreeTensorIfUnused(m_RecurrentToCellWeightsTensor); - FreeTensorIfUnused(m_RecurrentToOutputWeightsTensor); - FreeTensorIfUnused(m_CellToInputWeightsTensor); - FreeTensorIfUnused(m_CellToForgetWeightsTensor); - FreeTensorIfUnused(m_CellToOutputWeightsTensor); - FreeTensorIfUnused(m_InputGateBiasTensor); - FreeTensorIfUnused(m_ForgetGateBiasTensor); - FreeTensorIfUnused(m_CellBiasTensor); - FreeTensorIfUnused(m_OutputGateBiasTensor); - FreeTensorIfUnused(m_ProjectionWeightsTensor); - FreeTensorIfUnused(m_ProjectionBiasTensor); - FreeTensorIfUnused(m_ScratchBuffer); - FreeTensorIfUnused(m_InputLayerNormWeightsTensor); - FreeTensorIfUnused(m_ForgetLayerNormWeightsTensor); - FreeTensorIfUnused(m_CellLayerNormWeightsTensor); - FreeTensorIfUnused(m_OutputLayerNormWeightsTensor); -} - -} //namespace armnn |