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Diffstat (limited to 'src/backends/neon/workloads/NeonQuantizedLstmWorkload.cpp')
| -rw-r--r-- | src/backends/neon/workloads/NeonQuantizedLstmWorkload.cpp | 210 |
1 files changed, 210 insertions, 0 deletions
diff --git a/src/backends/neon/workloads/NeonQuantizedLstmWorkload.cpp b/src/backends/neon/workloads/NeonQuantizedLstmWorkload.cpp new file mode 100644 index 0000000000..d4319d414d --- /dev/null +++ b/src/backends/neon/workloads/NeonQuantizedLstmWorkload.cpp @@ -0,0 +1,210 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "NeonQuantizedLstmWorkload.hpp" +#include "NeonWorkloadUtils.hpp" + +#include <aclCommon/ArmComputeTensorUtils.hpp> +#include <backendsCommon/CpuTensorHandle.hpp> +#include <neon/NeonTensorHandle.hpp> + +namespace armnn +{ +using namespace armcomputetensorutils; + +NeonQuantizedLstmWorkload::NeonQuantizedLstmWorkload(const QuantizedLstmQueueDescriptor &descriptor, + const WorkloadInfo &info) + : BaseWorkload<QuantizedLstmQueueDescriptor>(descriptor, info) +{ + // Basic parameters + m_InputToInputWeightsTensor = std::make_unique<arm_compute::Tensor>(); + BuildArmComputeTensor(*m_InputToInputWeightsTensor, m_Data.m_InputToInputWeights->GetTensorInfo()); + + m_InputToForgetWeightsTensor = std::make_unique<arm_compute::Tensor>(); + BuildArmComputeTensor(*m_InputToForgetWeightsTensor, m_Data.m_InputToForgetWeights->GetTensorInfo()); + + m_InputToCellWeightsTensor = std::make_unique<arm_compute::Tensor>(); + BuildArmComputeTensor(*m_InputToCellWeightsTensor, m_Data.m_InputToCellWeights->GetTensorInfo()); + + m_InputToOutputWeightsTensor = std::make_unique<arm_compute::Tensor>(); + BuildArmComputeTensor(*m_InputToOutputWeightsTensor, m_Data.m_InputToOutputWeights->GetTensorInfo()); + + m_RecurrentToInputWeightsTensor = std::make_unique<arm_compute::Tensor>(); + BuildArmComputeTensor(*m_RecurrentToInputWeightsTensor, m_Data.m_RecurrentToInputWeights->GetTensorInfo()); + + m_RecurrentToForgetWeightsTensor = std::make_unique<arm_compute::Tensor>(); + BuildArmComputeTensor(*m_RecurrentToForgetWeightsTensor, m_Data.m_RecurrentToForgetWeights->GetTensorInfo()); + + m_RecurrentToCellWeightsTensor = std::make_unique<arm_compute::Tensor>(); + BuildArmComputeTensor(*m_RecurrentToCellWeightsTensor, m_Data.m_RecurrentToCellWeights->GetTensorInfo()); + + m_RecurrentToOutputWeightsTensor = std::make_unique<arm_compute::Tensor>(); + BuildArmComputeTensor(*m_RecurrentToOutputWeightsTensor, m_Data.m_RecurrentToOutputWeights->GetTensorInfo()); + + m_InputGateBiasTensor = std::make_unique<arm_compute::Tensor>(); + BuildArmComputeTensor(*m_InputGateBiasTensor, m_Data.m_InputGateBias->GetTensorInfo()); + + m_ForgetGateBiasTensor = std::make_unique<arm_compute::Tensor>(); + BuildArmComputeTensor(*m_ForgetGateBiasTensor, m_Data.m_ForgetGateBias->GetTensorInfo()); + + m_CellBiasTensor = std::make_unique<arm_compute::Tensor>(); + BuildArmComputeTensor(*m_CellBiasTensor, m_Data.m_CellBias->GetTensorInfo()); + + m_OutputGateBiasTensor = std::make_unique<arm_compute::Tensor>(); + BuildArmComputeTensor(*m_OutputGateBiasTensor, m_Data.m_OutputGateBias->GetTensorInfo()); + + const arm_compute::ITensor& input = static_cast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& cell_state_in = static_cast<IAclTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); + const arm_compute::ITensor& output_state_in = static_cast<IAclTensorHandle*>(m_Data.m_Inputs[2])->GetTensor(); + + arm_compute::ITensor& cell_state_out = static_cast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& output_state_out = static_cast<IAclTensorHandle*>(m_Data.m_Outputs[1])->GetTensor(); + + m_QuantizedLstmLayer.configure(&input, + m_InputToInputWeightsTensor.get(), + m_InputToForgetWeightsTensor.get(), + m_InputToCellWeightsTensor.get(), + m_InputToOutputWeightsTensor.get(), + m_RecurrentToInputWeightsTensor.get(), + m_RecurrentToForgetWeightsTensor.get(), + m_RecurrentToCellWeightsTensor.get(), + m_RecurrentToOutputWeightsTensor.get(), + m_InputGateBiasTensor.get(), + m_ForgetGateBiasTensor.get(), + m_CellBiasTensor.get(), + m_OutputGateBiasTensor.get(), + &cell_state_in, + &output_state_in, + &cell_state_out, + &output_state_out); + + InitializeArmComputeTensorData(*m_InputToInputWeightsTensor, + m_Data.m_InputToInputWeights); + + InitializeArmComputeTensorData(*m_InputToForgetWeightsTensor, + m_Data.m_InputToForgetWeights); + + InitializeArmComputeTensorData(*m_InputToCellWeightsTensor, + m_Data.m_InputToCellWeights); + + InitializeArmComputeTensorData(*m_InputToOutputWeightsTensor, + m_Data.m_InputToOutputWeights); + + InitializeArmComputeTensorData(*m_RecurrentToInputWeightsTensor, + m_Data.m_RecurrentToInputWeights); + + InitializeArmComputeTensorData(*m_RecurrentToForgetWeightsTensor, + m_Data.m_RecurrentToForgetWeights); + + InitializeArmComputeTensorData(*m_RecurrentToCellWeightsTensor, + m_Data.m_RecurrentToCellWeights); + + InitializeArmComputeTensorData(*m_RecurrentToOutputWeightsTensor, + m_Data.m_RecurrentToOutputWeights); + + InitializeArmComputeTensorData(*m_InputGateBiasTensor, + m_Data.m_InputGateBias); + + InitializeArmComputeTensorData(*m_ForgetGateBiasTensor, + m_Data.m_ForgetGateBias); + + InitializeArmComputeTensorData(*m_CellBiasTensor, + m_Data.m_CellBias); + + InitializeArmComputeTensorData(*m_OutputGateBiasTensor, + m_Data.m_OutputGateBias); + + // Force Compute Library to perform the necessary copying and reshaping, after which + // delete all the input tensors that will no longer be needed + m_QuantizedLstmLayer.prepare(); + FreeUnusedTensors(); +} + +void NeonQuantizedLstmWorkload::Execute() const +{ + m_QuantizedLstmLayer.run(); +} + +arm_compute::Status NeonQuantizedLstmWorkloadValidate(const TensorInfo& input, + const TensorInfo& cellStateIn, + const TensorInfo& outputStateIn, + const TensorInfo& cellStateOut, + const TensorInfo& outputStateOut, + const QuantizedLstmInputParamsInfo& paramsInfo) +{ + // The inputs and outputs + const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input); + const arm_compute::TensorInfo aclCellStateInInfo = BuildArmComputeTensorInfo(cellStateIn); + const arm_compute::TensorInfo aclOutputStateInInfo = BuildArmComputeTensorInfo(outputStateIn); + const arm_compute::TensorInfo aclCellStateOutInfo = BuildArmComputeTensorInfo(cellStateOut); + const arm_compute::TensorInfo aclOutputStateOutInfo = BuildArmComputeTensorInfo(outputStateOut); + + // Basic parameters + const arm_compute::TensorInfo aclInputToInputWeightsInfo + = BuildArmComputeTensorInfo(paramsInfo.get_InputToInputWeights()); + const arm_compute::TensorInfo aclInputToForgetWeightsInfo + = BuildArmComputeTensorInfo(paramsInfo.get_InputToForgetWeights()); + const arm_compute::TensorInfo aclInputToCellWeightsInfo + = BuildArmComputeTensorInfo(paramsInfo.get_InputToCellWeights()); + const arm_compute::TensorInfo aclInputToOutputWeightsInfo + = BuildArmComputeTensorInfo(paramsInfo.get_InputToOutputWeights()); + + const arm_compute::TensorInfo aclRecurrentToInputWeightsInfo + = BuildArmComputeTensorInfo(paramsInfo.get_RecurrentToInputWeights()); + const arm_compute::TensorInfo aclRecurrentToForgetWeightsInfo + = BuildArmComputeTensorInfo(paramsInfo.get_RecurrentToForgetWeights()); + const arm_compute::TensorInfo aclRecurrentToCellWeightsInfo + = BuildArmComputeTensorInfo(paramsInfo.get_RecurrentToCellWeights()); + const arm_compute::TensorInfo aclRecurrentToOutputWeightsInfo + = BuildArmComputeTensorInfo(paramsInfo.get_RecurrentToOutputWeights()); + + const arm_compute::TensorInfo aclInputGateBiasInfo + = BuildArmComputeTensorInfo(paramsInfo.get_InputGateBias()); + const arm_compute::TensorInfo aclForgetGateBiasInfo + = BuildArmComputeTensorInfo(paramsInfo.get_ForgetGateBias()); + const arm_compute::TensorInfo aclCellBiasInfo + = BuildArmComputeTensorInfo(paramsInfo.get_CellBias()); + const arm_compute::TensorInfo aclOutputGateBiasInfo + = BuildArmComputeTensorInfo(paramsInfo.get_OutputGateBias()); + + return arm_compute::NELSTMLayerQuantized::validate(&aclInputInfo, + &aclInputToInputWeightsInfo, + &aclInputToForgetWeightsInfo, + &aclInputToCellWeightsInfo, + &aclInputToOutputWeightsInfo, + &aclRecurrentToInputWeightsInfo, + &aclRecurrentToForgetWeightsInfo, + &aclRecurrentToCellWeightsInfo, + &aclRecurrentToOutputWeightsInfo, + &aclInputGateBiasInfo, + &aclForgetGateBiasInfo, + &aclCellBiasInfo, + &aclOutputGateBiasInfo, + &aclCellStateInInfo, + &aclOutputStateInInfo, + &aclCellStateOutInfo, + &aclOutputStateOutInfo); +} + +void NeonQuantizedLstmWorkload::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_InputGateBiasTensor); + FreeTensorIfUnused(m_ForgetGateBiasTensor); + FreeTensorIfUnused(m_CellBiasTensor); + FreeTensorIfUnused(m_OutputGateBiasTensor); + FreeTensorIfUnused(m_CellStateInTensor); + FreeTensorIfUnused(m_OutputStateInTensor); + FreeTensorIfUnused(m_CellStateOutTensor); +} + +} //namespace armnn |