| // |
| // Copyright © 2020 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "NeonQLstmWorkload.hpp" |
| #include "NeonWorkloadUtils.hpp" |
| |
| #include "aclCommon/ArmComputeTensorUtils.hpp" |
| |
| #include "neon/NeonTensorHandle.hpp" |
| |
| namespace armnn |
| { |
| using namespace armcomputetensorutils; |
| |
| NeonQLstmWorkload::NeonQLstmWorkload(const QLstmQueueDescriptor& descriptor, const WorkloadInfo& info) |
| : BaseWorkload<QLstmQueueDescriptor>(descriptor, info) |
| { |
| arm_compute::LSTMParams<arm_compute::ITensor> qLstmParams; |
| |
| // Mandatory params |
| 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_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_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()); |
| |
| // Create tensors for optional params if they are enabled |
| if (m_Data.m_Parameters.m_PeepholeEnabled) |
| { |
| m_CellToInputWeightsTensor = std::make_unique<arm_compute::Tensor>(); |
| |
| if (!m_Data.m_Parameters.m_CifgEnabled) |
| { |
| // In ACL this is categorised as a CIFG param and not a Peephole param |
| BuildArmComputeTensor(*m_CellToInputWeightsTensor, m_Data.m_CellToInputWeights->GetTensorInfo()); |
| } |
| |
| m_CellToForgetWeightsTensor = std::make_unique<arm_compute::Tensor>(); |
| BuildArmComputeTensor(*m_CellToForgetWeightsTensor, m_Data.m_CellToForgetWeights->GetTensorInfo()); |
| |
| m_CellToOutputWeightsTensor = std::make_unique<arm_compute::Tensor>(); |
| BuildArmComputeTensor(*m_CellToOutputWeightsTensor, m_Data.m_CellToOutputWeights->GetTensorInfo()); |
| |
| // Set Peephole params |
| qLstmParams.set_peephole_params(m_CellToForgetWeightsTensor.get(), |
| m_CellToOutputWeightsTensor.get()); |
| } |
| |
| if (m_Data.m_Parameters.m_ProjectionEnabled) |
| { |
| m_ProjectionWeightsTensor = std::make_unique<arm_compute::Tensor>(); |
| BuildArmComputeTensor(*m_ProjectionWeightsTensor, m_Data.m_ProjectionWeights->GetTensorInfo()); |
| |
| m_ProjectionBiasTensor = std::make_unique<arm_compute::Tensor>(); |
| if (m_Data.m_ProjectionBias != nullptr) |
| { |
| BuildArmComputeTensor(*m_ProjectionBiasTensor, m_Data.m_ProjectionBias->GetTensorInfo()); |
| } |
| |
| // Set projection params |
| qLstmParams.set_projection_params( |
| m_ProjectionWeightsTensor.get(), |
| m_Data.m_ProjectionBias != nullptr ? m_ProjectionBiasTensor.get() : nullptr); |
| } |
| |
| if (m_Data.m_Parameters.m_LayerNormEnabled) |
| { |
| m_InputLayerNormWeightsTensor = std::make_unique<arm_compute::Tensor>(); |
| |
| if (!m_Data.m_Parameters.m_CifgEnabled) |
| { |
| BuildArmComputeTensor(*m_InputLayerNormWeightsTensor, m_Data.m_InputLayerNormWeights->GetTensorInfo()); |
| } |
| |
| m_ForgetLayerNormWeightsTensor = std::make_unique<arm_compute::Tensor>(); |
| BuildArmComputeTensor(*m_ForgetLayerNormWeightsTensor, m_Data.m_ForgetLayerNormWeights->GetTensorInfo()); |
| |
| m_CellLayerNormWeightsTensor = std::make_unique<arm_compute::Tensor>(); |
| BuildArmComputeTensor(*m_CellLayerNormWeightsTensor, m_Data.m_CellLayerNormWeights->GetTensorInfo()); |
| |
| m_OutputLayerNormWeightsTensor = std::make_unique<arm_compute::Tensor>(); |
| BuildArmComputeTensor(*m_OutputLayerNormWeightsTensor, m_Data.m_OutputLayerNormWeights->GetTensorInfo()); |
| |
| // Set layer norm params |
| qLstmParams.set_layer_normalization_params( |
| m_Data.m_InputLayerNormWeights != nullptr ? m_InputLayerNormWeightsTensor.get() : nullptr, |
| m_ForgetLayerNormWeightsTensor.get(), |
| m_CellLayerNormWeightsTensor.get(), |
| m_OutputLayerNormWeightsTensor.get()); |
| } |
| |
| if (!m_Data.m_Parameters.m_CifgEnabled) |
| { |
| m_InputToInputWeightsTensor = std::make_unique<arm_compute::Tensor>(); |
| BuildArmComputeTensor(*m_InputToInputWeightsTensor, m_Data.m_InputToInputWeights->GetTensorInfo()); |
| |
| m_RecurrentToInputWeightsTensor = std::make_unique<arm_compute::Tensor>(); |
| BuildArmComputeTensor(*m_RecurrentToInputWeightsTensor, m_Data.m_RecurrentToInputWeights->GetTensorInfo()); |
| |
| m_InputGateBiasTensor = std::make_unique<arm_compute::Tensor>(); |
| BuildArmComputeTensor(*m_InputGateBiasTensor, m_Data.m_InputGateBias->GetTensorInfo()); |
| |
| // Set CIFG params |
| qLstmParams.set_cifg_params( |
| m_InputToInputWeightsTensor.get(), |
| m_RecurrentToInputWeightsTensor.get(), |
| m_Data.m_CellToInputWeights != nullptr ? m_CellToInputWeightsTensor.get() : nullptr, |
| m_InputGateBiasTensor.get()); |
| } |
| |
| // Input/Output tensors |
| const arm_compute::ITensor& input = static_cast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); |
| arm_compute::ITensor& outputStateIn = static_cast<IAclTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); |
| const arm_compute::ITensor& cellStateIn = static_cast<IAclTensorHandle*>(m_Data.m_Inputs[2])->GetTensor(); |
| |
| arm_compute::ITensor& outputStateOut = static_cast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); |
| arm_compute::ITensor& cellStateOut = static_cast<IAclTensorHandle*>(m_Data.m_Outputs[1])->GetTensor(); |
| arm_compute::ITensor& output = static_cast<IAclTensorHandle*>(m_Data.m_Outputs[2])->GetTensor(); |
| |
| // Set scalar descriptor params |
| qLstmParams.set_cell_clip_params(m_Data.m_Parameters.m_CellClip); |
| qLstmParams.set_projection_clip_params(m_Data.m_Parameters.m_ProjectionClip); |
| qLstmParams.set_hidden_state_params(m_Data.m_Parameters.m_HiddenStateZeroPoint, |
| m_Data.m_Parameters.m_HiddenStateScale); |
| qLstmParams.set_matmul_scale_params(m_Data.m_Parameters.m_InputIntermediateScale, |
| m_Data.m_Parameters.m_ForgetIntermediateScale, |
| m_Data.m_Parameters.m_CellIntermediateScale, |
| m_Data.m_Parameters.m_OutputIntermediateScale); |
| |
| // QLSTM NEON configure |
| m_QLstmLayer.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(), |
| &cellStateIn, |
| &outputStateIn, |
| &cellStateOut, |
| &outputStateOut, |
| &output, |
| qLstmParams); |
| |
| // Initialise ACL tensor data for mandatory params |
| InitializeArmComputeTensorData(*m_InputToForgetWeightsTensor, m_Data.m_InputToForgetWeights); |
| InitializeArmComputeTensorData(*m_InputToCellWeightsTensor, m_Data.m_InputToCellWeights); |
| InitializeArmComputeTensorData(*m_InputToOutputWeightsTensor, m_Data.m_InputToOutputWeights); |
| |
| InitializeArmComputeTensorData(*m_RecurrentToForgetWeightsTensor, m_Data.m_RecurrentToForgetWeights); |
| InitializeArmComputeTensorData(*m_RecurrentToCellWeightsTensor, m_Data.m_RecurrentToCellWeights); |
| InitializeArmComputeTensorData(*m_RecurrentToOutputWeightsTensor, m_Data.m_RecurrentToOutputWeights); |
| |
| InitializeArmComputeTensorData(*m_ForgetGateBiasTensor, m_Data.m_ForgetGateBias); |
| InitializeArmComputeTensorData(*m_CellBiasTensor, m_Data.m_CellBias); |
| InitializeArmComputeTensorData(*m_OutputGateBiasTensor, m_Data.m_OutputGateBias); |
| |
| // Initialise ACL tensor data for optional params |
| if (!m_Data.m_Parameters.m_CifgEnabled) |
| { |
| InitializeArmComputeTensorData(*m_InputToInputWeightsTensor, m_Data.m_InputToInputWeights); |
| InitializeArmComputeTensorData(*m_RecurrentToInputWeightsTensor, m_Data.m_RecurrentToInputWeights); |
| InitializeArmComputeTensorData(*m_InputGateBiasTensor, m_Data.m_InputGateBias); |
| } |
| |
| if (m_Data.m_Parameters.m_ProjectionEnabled) |
| { |
| InitializeArmComputeTensorData(*m_ProjectionWeightsTensor, m_Data.m_ProjectionWeights); |
| |
| if (m_Data.m_ProjectionBias != nullptr) |
| { |
| InitializeArmComputeTensorData(*m_ProjectionBiasTensor, m_Data.m_ProjectionBias); |
| } |
| } |
| |
| if (m_Data.m_Parameters.m_PeepholeEnabled) |
| { |
| if (!m_Data.m_Parameters.m_CifgEnabled) |
| { |
| InitializeArmComputeTensorData(*m_CellToInputWeightsTensor, m_Data.m_CellToInputWeights); |
| } |
| |
| InitializeArmComputeTensorData(*m_CellToForgetWeightsTensor, m_Data.m_CellToForgetWeights); |
| InitializeArmComputeTensorData(*m_CellToOutputWeightsTensor, m_Data.m_CellToOutputWeights); |
| } |
| |
| if (m_Data.m_Parameters.m_LayerNormEnabled) |
| { |
| if (!m_Data.m_Parameters.m_CifgEnabled) |
| { |
| InitializeArmComputeTensorData(*m_InputLayerNormWeightsTensor, m_Data.m_InputLayerNormWeights); |
| } |
| |
| InitializeArmComputeTensorData(*m_ForgetLayerNormWeightsTensor, m_Data.m_ForgetLayerNormWeights); |
| InitializeArmComputeTensorData(*m_CellLayerNormWeightsTensor, m_Data.m_CellLayerNormWeights); |
| InitializeArmComputeTensorData(*m_OutputLayerNormWeightsTensor, m_Data.m_OutputLayerNormWeights); |
| } |
| |
| // QLSTM NEON prepare |
| m_QLstmLayer.prepare(); |
| |
| FreeUnusedTensors(); |
| } |
| |
| void NeonQLstmWorkload::Execute() const |
| { |
| m_QLstmLayer.run(); |
| } |
| |
| arm_compute::Status NeonQLstmWorkloadValidate(const TensorInfo& input, |
| const TensorInfo& cellStateIn, |
| const TensorInfo& outputStateIn, |
| const TensorInfo& cellStateOut, |
| const TensorInfo& outputStateOut, |
| const TensorInfo& output, |
| const QLstmDescriptor& descriptor, |
| const LstmInputParamsInfo& paramsInfo) |
| { |
| arm_compute::LSTMParams<arm_compute::ITensorInfo> aclParamsInfo; |
| |
| // Input/Output tensor info |
| 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 aclOutputStateOutInfo = BuildArmComputeTensorInfo(outputStateOut); |
| const arm_compute::TensorInfo aclCellStateOutInfo = BuildArmComputeTensorInfo(cellStateOut); |
| const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output); |
| |
| // Mandatory tensor info |
| 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()); |
| |
| // Optional tensor info |
| arm_compute::TensorInfo aclInputToInputWeightsInfo; |
| arm_compute::TensorInfo aclRecurrentToInputWeightsInfo; |
| |
| arm_compute::TensorInfo aclCellToInputWeightsInfo; |
| arm_compute::TensorInfo aclCellToForgetWeightsInfo; |
| arm_compute::TensorInfo aclCellToOutputWeightsInfo; |
| |
| arm_compute::TensorInfo aclInputGateBiasInfo; |
| |
| arm_compute::TensorInfo aclProjectionWeightsInfo; |
| arm_compute::TensorInfo aclProjectionBiasInfo; |
| |
| arm_compute::TensorInfo aclInputLayerNormWeightsInfo; |
| arm_compute::TensorInfo aclForgetLayerNormWeightsInfo; |
| arm_compute::TensorInfo aclCellLayerNormWeightsInfo; |
| arm_compute::TensorInfo aclOutputLayerNormWeightsInfo; |
| |
| // Create tensor info for optional params if they are enabled |
| if (descriptor.m_PeepholeEnabled) |
| { |
| if (!descriptor.m_CifgEnabled) |
| { |
| aclCellToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellToInputWeights()); |
| } |
| |
| aclCellToForgetWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellToForgetWeights()); |
| aclCellToOutputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellToOutputWeights()); |
| |
| // Set peephole params info |
| aclParamsInfo.set_peephole_params(&aclCellToForgetWeightsInfo, |
| &aclCellToOutputWeightsInfo); |
| } |
| |
| if (descriptor.m_ProjectionEnabled) |
| { |
| aclProjectionWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetProjectionWeights()); |
| |
| if (paramsInfo.m_ProjectionBias != nullptr) |
| { |
| aclProjectionBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetProjectionBias()); |
| } |
| |
| // Set projection params info |
| aclParamsInfo.set_projection_params( |
| &aclProjectionWeightsInfo, |
| paramsInfo.m_ProjectionBias != nullptr ? &aclProjectionBiasInfo : nullptr); |
| } |
| |
| if (descriptor.m_LayerNormEnabled) |
| { |
| if (!descriptor.m_CifgEnabled) |
| { |
| aclInputLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetInputLayerNormWeights()); |
| } |
| |
| aclForgetLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetForgetLayerNormWeights()); |
| aclCellLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellLayerNormWeights()); |
| aclOutputLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetOutputLayerNormWeights()); |
| |
| // Set layer norm params info |
| aclParamsInfo.set_layer_normalization_params( |
| paramsInfo.m_InputLayerNormWeights != nullptr ? &aclInputLayerNormWeightsInfo : nullptr, |
| &aclForgetLayerNormWeightsInfo, |
| &aclCellLayerNormWeightsInfo, |
| &aclOutputLayerNormWeightsInfo); |
| } |
| |
| if (!descriptor.m_CifgEnabled) |
| { |
| aclInputToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetInputToInputWeights()); |
| aclRecurrentToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToInputWeights()); |
| aclInputGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetInputGateBias()); |
| |
| // Set CIFG params info |
| aclParamsInfo.set_cifg_params( |
| &aclInputToInputWeightsInfo, |
| &aclRecurrentToInputWeightsInfo, |
| paramsInfo.m_CellToInputWeights != nullptr ? &aclCellToInputWeightsInfo : nullptr, |
| &aclInputGateBiasInfo); |
| } |
| |
| // Set scalar descriptor params |
| aclParamsInfo.set_cell_clip_params(descriptor.m_CellClip); |
| aclParamsInfo.set_projection_clip_params(descriptor.m_ProjectionClip); |
| aclParamsInfo.set_hidden_state_params(descriptor.m_HiddenStateZeroPoint, descriptor.m_HiddenStateScale); |
| aclParamsInfo.set_matmul_scale_params(descriptor.m_InputIntermediateScale, |
| descriptor.m_ForgetIntermediateScale, |
| descriptor.m_CellIntermediateScale, |
| descriptor.m_OutputIntermediateScale); |
| |
| // QLSTM NEON validate |
| return arm_compute::NEQLSTMLayer::validate(&aclInputInfo, |
| &aclInputToForgetWeightsInfo, |
| &aclInputToCellWeightsInfo, |
| &aclInputToOutputWeightsInfo, |
| &aclRecurrentToForgetWeightsInfo, |
| &aclRecurrentToCellWeightsInfo, |
| &aclRecurrentToOutputWeightsInfo, |
| &aclForgetGateBiasInfo, |
| &aclCellBiasInfo, |
| &aclOutputGateBiasInfo, |
| &aclCellStateInInfo, |
| &aclOutputStateInInfo, |
| &aclCellStateOutInfo, |
| &aclOutputStateOutInfo, |
| &aclOutputInfo, |
| aclParamsInfo); |
| } |
| |
| void NeonQLstmWorkload::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_InputLayerNormWeightsTensor); |
| FreeTensorIfUnused(m_ForgetLayerNormWeightsTensor); |
| FreeTensorIfUnused(m_CellLayerNormWeightsTensor); |
| FreeTensorIfUnused(m_OutputLayerNormWeightsTensor); |
| } |
| |
| } //namespace armnn |
