1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
|
//
// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "NeonQuantizedLstmWorkload.hpp"
#include "NeonWorkloadUtils.hpp"
#include <aclCommon/ArmComputeTensorUtils.hpp>
#include <armnn/backends/TensorHandle.hpp>
#include <neon/NeonTensorHandle.hpp>
namespace armnn
{
using namespace armcomputetensorutils;
NeonQuantizedLstmWorkload::NeonQuantizedLstmWorkload(const QuantizedLstmQueueDescriptor &descriptor,
const WorkloadInfo &info)
: NeonBaseWorkload<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
{
ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID("NeonQuantizedLstmWorkload_Execute", this->GetGuid());
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.GetInputToInputWeights());
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 aclRecurrentToInputWeightsInfo
= BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToInputWeights());
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 aclInputGateBiasInfo
= BuildArmComputeTensorInfo(paramsInfo.GetInputGateBias());
const arm_compute::TensorInfo aclForgetGateBiasInfo
= BuildArmComputeTensorInfo(paramsInfo.GetForgetGateBias());
const arm_compute::TensorInfo aclCellBiasInfo
= BuildArmComputeTensorInfo(paramsInfo.GetCellBias());
const arm_compute::TensorInfo aclOutputGateBiasInfo
= BuildArmComputeTensorInfo(paramsInfo.GetOutputGateBias());
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
|
