blob: 7ea0d25a93fcc07d6572a3675353fc8affc56b69 [file] [log] [blame]
//
// Copyright © 2020 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "ClQLstmWorkload.hpp"
#include "ClWorkloadUtils.hpp"
#include "aclCommon/ArmComputeTensorUtils.hpp"
#include "cl/ClTensorHandle.hpp"
namespace armnn
{
using namespace armcomputetensorutils;
ClQLstmWorkload::ClQLstmWorkload(const QLstmQueueDescriptor &descriptor, const WorkloadInfo &info)
: BaseWorkload<QLstmQueueDescriptor>(descriptor, info)
{
arm_compute::LSTMParams<arm_compute::ICLTensor> qLstmParams;
// Mandatory params
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());
// Create tensors for optional params if they are enabled
if (m_Data.m_Parameters.m_PeepholeEnabled)
{
m_CellToInputWeightsTensor = std::make_unique<arm_compute::CLTensor>();
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::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());
// 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::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());
}
// 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::CLTensor>();
if (!m_Data.m_Parameters.m_CifgEnabled)
{
BuildArmComputeTensor(*m_InputLayerNormWeightsTensor, m_Data.m_InputLayerNormWeights->GetTensorInfo());
}
m_ForgetLayerNormWeightsTensor = std::make_unique<arm_compute::CLTensor>();
BuildArmComputeTensor(*m_ForgetLayerNormWeightsTensor, m_Data.m_ForgetLayerNormWeights->GetTensorInfo());
m_CellLayerNormWeightsTensor = std::make_unique<arm_compute::CLTensor>();
BuildArmComputeTensor(*m_CellLayerNormWeightsTensor, m_Data.m_CellLayerNormWeights->GetTensorInfo());
m_OutputLayerNormWeightsTensor = std::make_unique<arm_compute::CLTensor>();
BuildArmComputeTensor(*m_OutputLayerNormWeightsTensor, m_Data.m_OutputLayerNormWeights->GetTensorInfo());
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::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_InputGateBiasTensor = std::make_unique<arm_compute::CLTensor>();
BuildArmComputeTensor(*m_InputGateBiasTensor, m_Data.m_InputGateBias->GetTensorInfo());
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::ICLTensor& input = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
arm_compute::ICLTensor& outputStateIn = static_cast<IClTensorHandle*>(m_Data.m_Inputs[1])->GetTensor();
arm_compute::ICLTensor& cellStateIn = static_cast<IClTensorHandle*>(m_Data.m_Inputs[2])->GetTensor();
arm_compute::ICLTensor& outputStateOut = static_cast<IClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
arm_compute::ICLTensor& cellStateOut = static_cast<IClTensorHandle*>(m_Data.m_Outputs[1])->GetTensor();
arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(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);
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);
// InitializeArmComputeTensorData for mandatory params
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);
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)
{
if (!m_Data.m_Parameters.m_CifgEnabled)
{
InitializeArmComputeClTensorData(*m_CellToInputWeightsTensor, m_Data.m_CellToInputWeights);
}
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);
}
m_QLstmLayer.prepare();
FreeUnusedTensors();
}
void ClQLstmWorkload::Execute() const
{
m_QLstmLayer.run();
}
arm_compute::Status ClQLstmWorkloadValidate(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;
// The inputs and 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 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;
if (descriptor.m_PeepholeEnabled)
{
if (!descriptor.m_CifgEnabled)
{
aclCellToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellToInputWeights());
}
aclCellToForgetWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellToForgetWeights());
aclCellToOutputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellToOutputWeights());
aclParamsInfo.set_peephole_params(&aclCellToForgetWeightsInfo,
&aclCellToOutputWeightsInfo);
}
if (descriptor.m_ProjectionEnabled)
{
aclProjectionWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetProjectionWeights());
if (paramsInfo.m_ProjectionBias != nullptr)
{
aclProjectionBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetProjectionBias());
}
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());
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());
aclParamsInfo.set_cifg_params(
&aclInputToInputWeightsInfo,
&aclRecurrentToInputWeightsInfo,
paramsInfo.m_CellToInputWeights != nullptr ? &aclCellToInputWeightsInfo : nullptr,
&aclInputGateBiasInfo);
}
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);
return arm_compute::CLQLSTMLayer::validate(&aclInputInfo,
&aclInputToForgetWeightsInfo,
&aclInputToCellWeightsInfo,
&aclInputToOutputWeightsInfo,
&aclRecurrentToForgetWeightsInfo,
&aclRecurrentToCellWeightsInfo,
&aclRecurrentToOutputWeightsInfo,
&aclForgetGateBiasInfo,
&aclCellBiasInfo,
&aclOutputGateBiasInfo,
&aclCellStateInInfo,
&aclOutputStateInInfo,
&aclCellStateOutInfo,
&aclOutputStateOutInfo,
&aclOutputInfo,
aclParamsInfo);
}
void ClQLstmWorkload::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