ArmNN
 24.02
ClLstmFloatWorkload.cpp
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1 //
2 // Copyright © 2017-2023 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
6 #include "ClLstmFloatWorkload.hpp"
7 #include <cl/ClTensorHandle.hpp>
8 #include <armnn/backends/TensorHandle.hpp>
9 #include <cl/ClLayerSupport.hpp>
10 #include <aclCommon/ArmComputeUtils.hpp>
11 #include <aclCommon/ArmComputeTensorUtils.hpp>
12 
13 #include <armnn/utility/NumericCast.hpp>
14 
15 #include <arm_compute/runtime/CL/functions/CLLSTMLayer.h>
16 
17 #include "ClWorkloadUtils.hpp"
18 
19 namespace armnn
20 {
21 using namespace armcomputetensorutils;
22 
23 ClLstmFloatWorkload::ClLstmFloatWorkload(const LstmQueueDescriptor& descriptor,
24  const WorkloadInfo& info,
25  const arm_compute::CLCompileContext& clCompileContext)
26  : FloatWorkload<LstmQueueDescriptor>(descriptor, info)
27 {
28  // Report Profiling Details
29  ARMNN_REPORT_PROFILING_WORKLOAD_DESC("ClLstmFloatWorkload_Construct",
30  descriptor.m_Parameters,
31  info,
32  GetGuid());
33 
34  arm_compute::LSTMParams<arm_compute::ICLTensor> lstm_param;
35 
36  // Basic parameters
37  m_InputToForgetWeightsTensor = std::make_unique<arm_compute::CLTensor>();
38  BuildArmComputeTensor(*m_InputToForgetWeightsTensor, m_Data.m_InputToForgetWeights->GetTensorInfo());
39 
40  m_InputToCellWeightsTensor = std::make_unique<arm_compute::CLTensor>();
41  BuildArmComputeTensor(*m_InputToCellWeightsTensor, m_Data.m_InputToCellWeights->GetTensorInfo());
42 
43  m_InputToOutputWeightsTensor = std::make_unique<arm_compute::CLTensor>();
44  BuildArmComputeTensor(*m_InputToOutputWeightsTensor, m_Data.m_InputToOutputWeights->GetTensorInfo());
45 
46  m_RecurrentToForgetWeightsTensor = std::make_unique<arm_compute::CLTensor>();
47  BuildArmComputeTensor(*m_RecurrentToForgetWeightsTensor, m_Data.m_RecurrentToForgetWeights->GetTensorInfo());
48 
49  m_RecurrentToCellWeightsTensor = std::make_unique<arm_compute::CLTensor>();
50  BuildArmComputeTensor(*m_RecurrentToCellWeightsTensor, m_Data.m_RecurrentToCellWeights->GetTensorInfo());
51 
52  m_RecurrentToOutputWeightsTensor = std::make_unique<arm_compute::CLTensor>();
53  BuildArmComputeTensor(*m_RecurrentToOutputWeightsTensor, m_Data.m_RecurrentToOutputWeights->GetTensorInfo());
54 
55  m_ForgetGateBiasTensor = std::make_unique<arm_compute::CLTensor>();
56  BuildArmComputeTensor(*m_ForgetGateBiasTensor, m_Data.m_ForgetGateBias->GetTensorInfo());
57 
58  m_CellBiasTensor = std::make_unique<arm_compute::CLTensor>();
59  BuildArmComputeTensor(*m_CellBiasTensor, m_Data.m_CellBias->GetTensorInfo());
60 
61  m_OutputGateBiasTensor = std::make_unique<arm_compute::CLTensor>();
62  BuildArmComputeTensor(*m_OutputGateBiasTensor, m_Data.m_OutputGateBias->GetTensorInfo());
63 
64  // for future reference: check the AndroidNN API for the logic here
65  if (!m_Data.m_Parameters.m_CifgEnabled)
66  {
67  m_InputToInputWeightsTensor = std::make_unique<arm_compute::CLTensor>();
68  BuildArmComputeTensor(*m_InputToInputWeightsTensor, m_Data.m_InputToInputWeights->GetTensorInfo());
69 
70  m_RecurrentToInputWeightsTensor = std::make_unique<arm_compute::CLTensor>();
71  BuildArmComputeTensor(*m_RecurrentToInputWeightsTensor, m_Data.m_RecurrentToInputWeights->GetTensorInfo());
72 
73  m_CellToInputWeightsTensor = std::make_unique<arm_compute::CLTensor>();
74  if (m_Data.m_CellToInputWeights != nullptr)
75  {
76  BuildArmComputeTensor(*m_CellToInputWeightsTensor, m_Data.m_CellToInputWeights->GetTensorInfo());
77  }
78 
79  m_InputGateBiasTensor = std::make_unique<arm_compute::CLTensor>();
80  BuildArmComputeTensor(*m_InputGateBiasTensor, m_Data.m_InputGateBias->GetTensorInfo());
81 
82  lstm_param.set_cifg_params(m_InputToInputWeightsTensor.get(),
83  m_RecurrentToInputWeightsTensor.get(),
84  m_Data.m_CellToInputWeights != nullptr ? m_CellToInputWeightsTensor.get() : nullptr,
85  m_InputGateBiasTensor.get());
86  }
87 
88  if (m_Data.m_Parameters.m_ProjectionEnabled)
89  {
90  m_ProjectionWeightsTensor = std::make_unique<arm_compute::CLTensor>();
91  BuildArmComputeTensor(*m_ProjectionWeightsTensor, m_Data.m_ProjectionWeights->GetTensorInfo());
92 
93  m_ProjectionBiasTensor = std::make_unique<arm_compute::CLTensor>();
94  if (m_Data.m_ProjectionBias != nullptr)
95  {
96  BuildArmComputeTensor(*m_ProjectionBiasTensor, m_Data.m_ProjectionBias->GetTensorInfo());
97  }
98 
99  lstm_param.set_projection_params(m_ProjectionWeightsTensor.get(),
100  m_Data.m_ProjectionBias != nullptr ? m_ProjectionBiasTensor.get() : nullptr);
101  }
102 
103  if (m_Data.m_Parameters.m_PeepholeEnabled)
104  {
105  m_CellToForgetWeightsTensor = std::make_unique<arm_compute::CLTensor>();
106  BuildArmComputeTensor(*m_CellToForgetWeightsTensor, m_Data.m_CellToForgetWeights->GetTensorInfo());
107 
108  m_CellToOutputWeightsTensor = std::make_unique<arm_compute::CLTensor>();
109  BuildArmComputeTensor(*m_CellToOutputWeightsTensor, m_Data.m_CellToOutputWeights->GetTensorInfo());
110 
111  lstm_param.set_peephole_params(m_CellToForgetWeightsTensor.get(), m_CellToOutputWeightsTensor.get());
112  }
113 
114  if (m_Data.m_Parameters.m_LayerNormEnabled)
115  {
116  m_InputLayerNormWeightsTensor = std::make_unique<arm_compute::CLTensor>();
117  m_ForgetLayerNormWeightsTensor = std::make_unique<arm_compute::CLTensor>();
118  m_CellLayerNormWeightsTensor = std::make_unique<arm_compute::CLTensor>();
119  m_OutputLayerNormWeightsTensor = std::make_unique<arm_compute::CLTensor>();
120 
121  if (!m_Data.m_Parameters.m_CifgEnabled)
122  {
123  BuildArmComputeTensor(*m_InputLayerNormWeightsTensor, m_Data.m_InputLayerNormWeights->GetTensorInfo());
124  }
125  BuildArmComputeTensor(*m_ForgetLayerNormWeightsTensor, m_Data.m_ForgetLayerNormWeights->GetTensorInfo());
126  BuildArmComputeTensor(*m_CellLayerNormWeightsTensor, m_Data.m_CellLayerNormWeights->GetTensorInfo());
127  BuildArmComputeTensor(*m_OutputLayerNormWeightsTensor, m_Data.m_OutputLayerNormWeights->GetTensorInfo());
128 
129  lstm_param.set_layer_normalization_params(m_Data.m_Parameters.m_CifgEnabled ? nullptr :
130  m_InputLayerNormWeightsTensor.get(),
131  m_ForgetLayerNormWeightsTensor.get(),
132  m_CellLayerNormWeightsTensor.get(),
133  m_OutputLayerNormWeightsTensor.get());
134  }
135 
136  const arm_compute::ICLTensor& input = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
137  const arm_compute::ICLTensor& output_state_in = static_cast<IClTensorHandle*>(m_Data.m_Inputs[1])->GetTensor();
138  arm_compute::ICLTensor& cell_state_in = static_cast<IClTensorHandle*>(m_Data.m_Inputs[2])->GetTensor();
139 
140  arm_compute::ICLTensor& output_state_out = static_cast<IClTensorHandle*>(m_Data.m_Outputs[1])->GetTensor();
141  arm_compute::ICLTensor& cell_state_out = static_cast<IClTensorHandle*>(m_Data.m_Outputs[2])->GetTensor();
142  arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(m_Data.m_Outputs[3])->GetTensor();
143 
144  // Get the batch_size and the num_units from the cellStateIn dimensions
145  const TensorInfo& inputTensorInfo = info.m_InputTensorInfos[2];
146  const unsigned int batch_size = armnn::numeric_cast<unsigned int>(inputTensorInfo.GetShape()[0]);
147  const unsigned int num_units = armnn::numeric_cast<unsigned int>(inputTensorInfo.GetShape()[1]);
148 
149  m_ScratchBuffer = std::make_unique<arm_compute::CLTensor>();
150  if (m_Data.m_Parameters.m_CifgEnabled)
151  {
152  // 2D tensor with dimensions [num_units * 3, batch_size] with CIFG
153  armnn::TensorInfo scratchBuffer1({ batch_size, num_units * 3 }, DataType::Float32);
154  BuildArmComputeTensor(*m_ScratchBuffer, scratchBuffer1);
155  }
156  else
157  {
158  // scratch_buffer [num_units * 4, batch_size] without CIFG
159  armnn::TensorInfo scratchBuffer2({ batch_size, num_units * 4 }, DataType::Float32);
160  BuildArmComputeTensor(*m_ScratchBuffer, scratchBuffer2);
161  }
162 
163  float cell_threshold = m_Data.m_Parameters.m_ClippingThresCell;
164  float projection_threshold = m_Data.m_Parameters.m_ClippingThresProj;
165 
166  // for preparing the object for the class ActivationLayerInfo, we need to consider 5 situations
167  arm_compute::ActivationLayerInfo activationLayerInfo =
168  ConvertLstmActivationFuncToAclLayerInfo(m_Data.m_Parameters.m_ActivationFunc);
169 
170  {
171  ARMNN_SCOPED_PROFILING_EVENT_CL_NAME_GUID("ClLstmFloatWorkload_configure");
172  m_LstmLayer.configure(clCompileContext, &input, m_InputToForgetWeightsTensor.get(),
173  m_InputToCellWeightsTensor.get(), m_InputToOutputWeightsTensor.get(),
174  m_RecurrentToForgetWeightsTensor.get(), m_RecurrentToCellWeightsTensor.get(),
175  m_RecurrentToOutputWeightsTensor.get(), m_ForgetGateBiasTensor.get(),
176  m_CellBiasTensor.get(), m_OutputGateBiasTensor.get(), &output_state_in,
177  &cell_state_in, m_ScratchBuffer.get(), &output_state_out,
178  &cell_state_out, &output, lstm_param, activationLayerInfo,
179  cell_threshold, projection_threshold);
180  }
181 
182  armcomputetensorutils::InitialiseArmComputeTensorEmpty(*m_ScratchBuffer);
183 
184  InitializeArmComputeClTensorData(*m_InputToForgetWeightsTensor, m_Data.m_InputToForgetWeights);
185  InitializeArmComputeClTensorData(*m_InputToCellWeightsTensor, m_Data.m_InputToCellWeights);
186  InitializeArmComputeClTensorData(*m_InputToOutputWeightsTensor, m_Data.m_InputToOutputWeights);
187  InitializeArmComputeClTensorData(*m_RecurrentToForgetWeightsTensor, m_Data.m_RecurrentToForgetWeights);
188  InitializeArmComputeClTensorData(*m_RecurrentToCellWeightsTensor, m_Data.m_RecurrentToCellWeights);
189  InitializeArmComputeClTensorData(*m_RecurrentToOutputWeightsTensor, m_Data.m_RecurrentToOutputWeights);
190  InitializeArmComputeClTensorData(*m_ForgetGateBiasTensor, m_Data.m_ForgetGateBias);
191  InitializeArmComputeClTensorData(*m_CellBiasTensor, m_Data.m_CellBias);
192  InitializeArmComputeClTensorData(*m_OutputGateBiasTensor, m_Data.m_OutputGateBias);
193 
194  if (!m_Data.m_Parameters.m_CifgEnabled)
195  {
196  InitializeArmComputeClTensorData(*m_InputToInputWeightsTensor, m_Data.m_InputToInputWeights);
197  InitializeArmComputeClTensorData(*m_RecurrentToInputWeightsTensor, m_Data.m_RecurrentToInputWeights);
198  if (m_Data.m_CellToInputWeights != nullptr)
199  {
200  InitializeArmComputeClTensorData(*m_CellToInputWeightsTensor, m_Data.m_CellToInputWeights);
201  }
202  InitializeArmComputeClTensorData(*m_InputGateBiasTensor, m_Data.m_InputGateBias);
203  }
204 
205  if (m_Data.m_Parameters.m_ProjectionEnabled)
206  {
207  InitializeArmComputeClTensorData(*m_ProjectionWeightsTensor, m_Data.m_ProjectionWeights);
208  if (m_Data.m_ProjectionBias != nullptr)
209  {
210  InitializeArmComputeClTensorData(*m_ProjectionBiasTensor, m_Data.m_ProjectionBias);
211  }
212  }
213 
214  if (m_Data.m_Parameters.m_PeepholeEnabled)
215  {
216  InitializeArmComputeClTensorData(*m_CellToForgetWeightsTensor, m_Data.m_CellToForgetWeights);
217  InitializeArmComputeClTensorData(*m_CellToOutputWeightsTensor, m_Data.m_CellToOutputWeights);
218  }
219 
220  if (m_Data.m_Parameters.m_LayerNormEnabled)
221  {
222  if (!m_Data.m_Parameters.m_CifgEnabled)
223  {
224  InitializeArmComputeClTensorData(*m_InputLayerNormWeightsTensor, m_Data.m_InputLayerNormWeights);
225  }
226 
227  InitializeArmComputeClTensorData(*m_ForgetLayerNormWeightsTensor, m_Data.m_ForgetLayerNormWeights);
228  InitializeArmComputeClTensorData(*m_CellLayerNormWeightsTensor, m_Data.m_CellLayerNormWeights);
229  InitializeArmComputeClTensorData(*m_OutputLayerNormWeightsTensor, m_Data.m_OutputLayerNormWeights);
230  }
231 
232  // Force Compute Library to perform the necessary copying and reshaping, after which
233  // delete all the input tensors that will no longer be needed
234  m_LstmLayer.prepare();
235  FreeUnusedTensors();
236 }
237 
238 void ClLstmFloatWorkload::Execute() const
239 {
240  ARMNN_SCOPED_PROFILING_EVENT_CL_NAME_GUID("ClLstmFloatWorkload_Execute");
241  RunClFunction(m_LstmLayer, CHECK_LOCATION());
242 }
243 
244 arm_compute::Status ClLstmFloatWorkloadValidate(const TensorInfo& input, const TensorInfo& outputStateIn,
245  const TensorInfo& cellStateIn, const TensorInfo& scratchBuffer,
246  const TensorInfo& outputStateOut, const TensorInfo& cellStateOut,
247  const TensorInfo& output, const LstmDescriptor& descriptor,
248  const LstmInputParamsInfo& paramsInfo)
249 {
250  arm_compute::LSTMParams<arm_compute::ITensorInfo> lstm_params_info;
251 
252  // The inputs and the outputs
253  const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input);
254  const arm_compute::TensorInfo aclOutputStateInInfo = BuildArmComputeTensorInfo(outputStateIn);
255  const arm_compute::TensorInfo aclCellStateInInfo = BuildArmComputeTensorInfo(cellStateIn);
256  const arm_compute::TensorInfo aclScratchBufferInfo = BuildArmComputeTensorInfo(scratchBuffer);
257  const arm_compute::TensorInfo aclOutputStateOutInfo = BuildArmComputeTensorInfo(outputStateOut);
258  const arm_compute::TensorInfo aclCellStateOutInfo = BuildArmComputeTensorInfo(cellStateOut);
259  const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output);
260 
261  // Basic parameters
262  const arm_compute::TensorInfo aclInputToForgetWeightsInfo
263  = BuildArmComputeTensorInfo(paramsInfo.GetInputToForgetWeights());
264  const arm_compute::TensorInfo aclInputToCellWeightsInfo
265  = BuildArmComputeTensorInfo(paramsInfo.GetInputToCellWeights());
266  const arm_compute::TensorInfo aclInputToOutputWeightsInfo
267  = BuildArmComputeTensorInfo(paramsInfo.GetInputToOutputWeights());
268  const arm_compute::TensorInfo aclRecurrentToForgetWeightsInfo
269  = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToForgetWeights());
270  const arm_compute::TensorInfo aclRecurrentToCellWeightsInfo
271  = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToCellWeights());
272  const arm_compute::TensorInfo aclRecurrentToOutputWeightsInfo
273  = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToOutputWeights());
274  const arm_compute::TensorInfo aclForgetGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetForgetGateBias());
275  const arm_compute::TensorInfo aclCellBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellBias());
276  const arm_compute::TensorInfo aclOutputGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetOutputGateBias());
277 
278  arm_compute::TensorInfo aclInputToInputWeightsInfo;
279  arm_compute::TensorInfo aclRecurrentToInputWeightsInfo;
280  arm_compute::TensorInfo aclCellToInputWeightsInfo;
281  arm_compute::TensorInfo aclInputGateBiasInfo;
282  arm_compute::TensorInfo aclProjectionWeightsInfo;
283  arm_compute::TensorInfo aclProjectionBiasInfo;
284  arm_compute::TensorInfo aclCellToForgetWeightsInfo;
285  arm_compute::TensorInfo aclCellToOutputWeightsInfo;
286  arm_compute::TensorInfo aclInputLayerNormWeightsInfo;
287  arm_compute::TensorInfo aclForgetLayerNormWeightsInfo;
288  arm_compute::TensorInfo aclCellLayerNormWeightsInfo;
289  arm_compute::TensorInfo aclOutputLayerNormWeightsInfo;
290 
291  if (!descriptor.m_CifgEnabled)
292  {
293  aclInputToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetInputToInputWeights());
294  aclRecurrentToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToInputWeights());
295 
296  if (paramsInfo.m_CellToInputWeights != nullptr)
297  {
298  aclCellToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellToInputWeights());
299  }
300  aclInputGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetInputGateBias());
301  lstm_params_info.set_cifg_params(&aclInputToInputWeightsInfo, &aclRecurrentToInputWeightsInfo,
302  paramsInfo.m_CellToInputWeights != nullptr ?
303  &aclCellToInputWeightsInfo: nullptr,
304  &aclInputGateBiasInfo);
305  }
306 
307  if (descriptor.m_ProjectionEnabled)
308  {
309  aclProjectionWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetProjectionWeights());
310 
311  if (paramsInfo.m_ProjectionBias != nullptr)
312  {
313  aclProjectionBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetProjectionBias());
314  }
315  lstm_params_info.set_projection_params(&aclProjectionWeightsInfo,
316  paramsInfo.m_ProjectionBias != nullptr ?
317  &aclProjectionBiasInfo: nullptr);
318  }
319 
320  if (descriptor.m_PeepholeEnabled)
321  {
322  aclCellToForgetWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellToForgetWeights());
323  aclCellToOutputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellToOutputWeights());
324  lstm_params_info.set_peephole_params(&aclCellToForgetWeightsInfo, &aclCellToOutputWeightsInfo);
325  }
326 
327  float cell_threshold = descriptor.m_ClippingThresCell;
328  float projection_threshold = descriptor.m_ClippingThresProj;
329 
330  // for preparing the object for the class ActivationLayerInfo, we need to consider 5 situations
331  arm_compute::ActivationLayerInfo activationLayerInfo =
332  ConvertLstmActivationFuncToAclLayerInfo(descriptor.m_ActivationFunc);
333 
334  if (descriptor.m_LayerNormEnabled)
335  {
336  if (!descriptor.m_CifgEnabled)
337  {
338  aclInputLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetInputLayerNormWeights());
339  }
340 
341  aclForgetLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetForgetLayerNormWeights());
342 
343  aclCellLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellLayerNormWeights());
344 
345  aclOutputLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetOutputLayerNormWeights());
346 
347  lstm_params_info.set_layer_normalization_params(descriptor.m_CifgEnabled ?
348  nullptr : &aclInputLayerNormWeightsInfo,
349  &aclForgetLayerNormWeightsInfo,
350  &aclCellLayerNormWeightsInfo,
351  &aclOutputLayerNormWeightsInfo);
352  }
353 
354  return arm_compute::CLLSTMLayer::validate(&aclInputInfo, &aclInputToForgetWeightsInfo,
355  &aclInputToCellWeightsInfo,
356  &aclInputToOutputWeightsInfo,
357  &aclRecurrentToForgetWeightsInfo,
358  &aclRecurrentToCellWeightsInfo,
359  &aclRecurrentToOutputWeightsInfo,
360  &aclForgetGateBiasInfo,
361  &aclCellBiasInfo,
362  &aclOutputGateBiasInfo,
363  &aclOutputStateInInfo, &aclCellStateInInfo,
364  &aclScratchBufferInfo, &aclOutputStateOutInfo,
365  &aclCellStateOutInfo, &aclOutputInfo,
366  lstm_params_info, activationLayerInfo,
367  cell_threshold, projection_threshold);
368 }
369 
370 void ClLstmFloatWorkload::FreeUnusedTensors()
371 {
372  FreeTensorIfUnused(m_InputToInputWeightsTensor);
373  FreeTensorIfUnused(m_InputToForgetWeightsTensor);
374  FreeTensorIfUnused(m_InputToCellWeightsTensor);
375  FreeTensorIfUnused(m_InputToOutputWeightsTensor);
376  FreeTensorIfUnused(m_RecurrentToInputWeightsTensor);
377  FreeTensorIfUnused(m_RecurrentToForgetWeightsTensor);
378  FreeTensorIfUnused(m_RecurrentToCellWeightsTensor);
379  FreeTensorIfUnused(m_RecurrentToOutputWeightsTensor);
380  FreeTensorIfUnused(m_CellToInputWeightsTensor);
381  FreeTensorIfUnused(m_CellToForgetWeightsTensor);
382  FreeTensorIfUnused(m_CellToOutputWeightsTensor);
383  FreeTensorIfUnused(m_InputGateBiasTensor);
384  FreeTensorIfUnused(m_ForgetGateBiasTensor);
385  FreeTensorIfUnused(m_CellBiasTensor);
386  FreeTensorIfUnused(m_OutputGateBiasTensor);
387  FreeTensorIfUnused(m_ProjectionWeightsTensor);
388  FreeTensorIfUnused(m_ProjectionBiasTensor);
389  FreeTensorIfUnused(m_ScratchBuffer);
390  FreeTensorIfUnused(m_InputLayerNormWeightsTensor);
391  FreeTensorIfUnused(m_ForgetLayerNormWeightsTensor);
392  FreeTensorIfUnused(m_CellLayerNormWeightsTensor);
393  FreeTensorIfUnused(m_OutputLayerNormWeightsTensor);
394 }
395 
396 void ClLstmFloatWorkload::ReplaceInputTensorHandle(ITensorHandle* tensorHandle, unsigned int slot)
397 {
398  ITensorHandle* backupHandle = this->m_Data.m_Inputs[slot];
399  this->m_Data.m_Inputs[slot] = tensorHandle;
400  try
401  {
402  Reconfigure();
403  }
404  catch(armnn::UnimplementedException& e)
405  {
406  // Cannot reconfigure, revert the slot back and throw the exception.
407  this->m_Data.m_Inputs[slot] = backupHandle;
408  throw e;
409  }
410 }
411 
412 // Replace output tensor handle with the given TensorHandle
413 void ClLstmFloatWorkload::ReplaceOutputTensorHandle(ITensorHandle* tensorHandle, unsigned int slot)
414 {
415  ITensorHandle* backupHandle = this->m_Data.m_Inputs[slot];
416  this->m_Data.m_Inputs[slot] = tensorHandle;
417  try
418  {
419  Reconfigure();
420  }
421  catch(armnn::UnimplementedException& e)
422  {
423  // Cannot reconfigure, revert the slot back and throw the exception.
424  this->m_Data.m_Inputs[slot] = backupHandle;
425  throw e;
426  }
427 }
428 
429 void ClLstmFloatWorkload::Reconfigure()
430 {
431  throw armnn::UnimplementedException("Reconfigure not implemented for this workload");
432 }
433 
434 } //namespace armnn
armnn::LstmInputParamsInfo::GetCellBias
const TensorInfo & GetCellBias() const
Definition: LstmParams.hpp:173
armnn::InitializeArmComputeClTensorData
void InitializeArmComputeClTensorData(arm_compute::CLTensor &clTensor, const ConstTensorHandle *handle)
Definition: ClWorkloadUtils.hpp:124
armnn::LstmInputParamsInfo::GetInputToCellWeights
const TensorInfo & GetInputToCellWeights() const
Definition: LstmParams.hpp:129
armnn::TensorInfo
Definition: Tensor.hpp:152
ClLayerSupport.hpp
armnn::LstmInputParamsInfo::GetProjectionBias
const TensorInfo & GetProjectionBias() const
Definition: LstmParams.hpp:185
CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203
armnn::ClLstmFloatWorkload::ReplaceOutputTensorHandle
void ReplaceOutputTensorHandle(ITensorHandle *tensorHandle, unsigned int slot) override
Definition: ClLstmFloatWorkload.cpp:413
armnn::DataType::Float32
@ Float32
armnn::LstmInputParamsInfo::m_CellToInputWeights
const TensorInfo * m_CellToInputWeights
Definition: LstmParams.hpp:97
armnn::ITensorHandle
Definition: ITensorHandle.hpp:16
armnn::LstmInputParamsInfo::GetInputGateBias
const TensorInfo & GetInputGateBias() const
Definition: LstmParams.hpp:165
armnn::LstmInputParamsInfo::GetRecurrentToInputWeights
const TensorInfo & GetRecurrentToInputWeights() const
Definition: LstmParams.hpp:137
armnn::LstmInputParamsInfo::GetRecurrentToForgetWeights
const TensorInfo & GetRecurrentToForgetWeights() const
Definition: LstmParams.hpp:141
armnn::TypedWorkload
Definition: Workload.hpp:101
armnn::LstmInputParamsInfo::GetRecurrentToCellWeights
const TensorInfo & GetRecurrentToCellWeights() const
Definition: LstmParams.hpp:145
NumericCast.hpp
armnn::LstmInputParamsInfo::GetInputLayerNormWeights
const TensorInfo & GetInputLayerNormWeights() const
Definition: LstmParams.hpp:189
armnn::LstmDescriptor::m_PeepholeEnabled
bool m_PeepholeEnabled
Enable/disable peephole.
Definition: Descriptors.hpp:1148
armnn::LstmDescriptor::m_ClippingThresProj
float m_ClippingThresProj
Clipping threshold value for the projection.
Definition: Descriptors.hpp:1144
armnn::QueueDescriptorWithParameters::m_Parameters
LayerDescriptor m_Parameters
Definition: WorkloadData.hpp:66
armnn::LstmInputParamsInfo::GetCellToInputWeights
const TensorInfo & GetCellToInputWeights() const
Definition: LstmParams.hpp:153
armnn::LstmInputParamsInfo::GetRecurrentToOutputWeights
const TensorInfo & GetRecurrentToOutputWeights() const
Definition: LstmParams.hpp:149
armnn::LstmInputParamsInfo::GetInputToInputWeights
const TensorInfo & GetInputToInputWeights() const
Definition: LstmParams.hpp:121
ARMNN_SCOPED_PROFILING_EVENT_CL_NAME_GUID
#define ARMNN_SCOPED_PROFILING_EVENT_CL_NAME_GUID(label)
Creates a profiling event that uses GetGuid() and GetName() from the calling class.
Definition: ClWorkloadUtils.hpp:36
armnn::WorkloadInfo
Contains information about TensorInfos of a layer.
Definition: WorkloadInfo.hpp:16
armnn::LstmInputParamsInfo::GetForgetGateBias
const TensorInfo & GetForgetGateBias() const
Definition: LstmParams.hpp:169
ClWorkloadUtils.hpp
armnn::ConvertLstmActivationFuncToAclLayerInfo
arm_compute::ActivationLayerInfo ConvertLstmActivationFuncToAclLayerInfo(uint32_t activationFunction)
Definition: ArmComputeUtils.hpp:118
armnn::LstmInputParamsInfo::GetCellToForgetWeights
const TensorInfo & GetCellToForgetWeights() const
Definition: LstmParams.hpp:157
armnn::ClLstmFloatWorkload::Execute
void Execute() const override
Definition: ClLstmFloatWorkload.cpp:238
ArmComputeUtils.hpp
ClLstmFloatWorkload.hpp
armnn::ClLstmFloatWorkloadValidate
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)
Definition: ClLstmFloatWorkload.cpp:244
armnn::BoostLogSeverityMapping::info
@ info
armnn::QueueDescriptor::m_Outputs
std::vector< ITensorHandle * > m_Outputs
Definition: WorkloadData.hpp:27
ARMNN_REPORT_PROFILING_WORKLOAD_DESC
#define ARMNN_REPORT_PROFILING_WORKLOAD_DESC(name, desc, infos, guid)
Definition: Profiling.hpp:227
armnn::BaseWorkload::GetGuid
arm::pipe::ProfilingGuid GetGuid() const final
Definition: Workload.hpp:67
armnn::IClTensorHandle
Definition: IClTensorHandle.hpp:13
armnn::LstmDescriptor
An LstmDescriptor for the LstmLayer.
Definition: Descriptors.hpp:1102
armnn::LstmQueueDescriptor
Definition: WorkloadData.hpp:400
TensorHandle.hpp
armnn::Status
Status
Definition: Types.hpp:42
ClTensorHandle.hpp
armnn::LstmInputParamsInfo::GetInputToOutputWeights
const TensorInfo & GetInputToOutputWeights() const
Definition: LstmParams.hpp:133
armnn::LstmDescriptor::m_CifgEnabled
bool m_CifgEnabled
Enable/disable cifg (coupled input & forget gate).
Definition: Descriptors.hpp:1146
armnn::BaseWorkload::m_Data
QueueDescriptor m_Data
Definition: Workload.hpp:89
armnn::RunClFunction
void RunClFunction(arm_compute::IFunction &function, const CheckLocation &location)
Definition: ClWorkloadUtils.hpp:168
armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:193
armnn::LstmInputParamsInfo::GetOutputGateBias
const TensorInfo & GetOutputGateBias() const
Definition: LstmParams.hpp:177
armnn::LstmDescriptor::m_LayerNormEnabled
bool m_LayerNormEnabled
Enable/disable layer normalization.
Definition: Descriptors.hpp:1152
armnn::LstmInputParamsInfo::GetCellToOutputWeights
const TensorInfo & GetCellToOutputWeights() const
Definition: LstmParams.hpp:161
armnn::LstmInputParamsInfo::GetOutputLayerNormWeights
const TensorInfo & GetOutputLayerNormWeights() const
Definition: LstmParams.hpp:201
armnn
Copyright (c) 2021 ARM Limited and Contributors.
Definition: 01_00_quick_start.dox:6
armnn::LstmInputParamsInfo
Definition: LstmParams.hpp:63
armnn::ClLstmFloatWorkload::ReplaceInputTensorHandle
void ReplaceInputTensorHandle(ITensorHandle *tensorHandle, unsigned int slot) override
Definition: ClLstmFloatWorkload.cpp:396
ArmComputeTensorUtils.hpp
armnn::LstmDescriptor::m_ProjectionEnabled
bool m_ProjectionEnabled
Enable/disable the projection layer.
Definition: Descriptors.hpp:1150
armnn::LstmInputParamsInfo::GetProjectionWeights
const TensorInfo & GetProjectionWeights() const
Definition: LstmParams.hpp:181
armnn::UnimplementedException
Definition: Exceptions.hpp:98
armnn::LstmDescriptor::m_ActivationFunc
uint32_t m_ActivationFunc
The activation function to use.
Definition: Descriptors.hpp:1140
armnn::LstmDescriptor::m_ClippingThresCell
float m_ClippingThresCell
Clipping threshold value for the cell state.
Definition: Descriptors.hpp:1142
armnn::ClLstmFloatWorkload::ClLstmFloatWorkload
ClLstmFloatWorkload(const LstmQueueDescriptor &descriptor, const WorkloadInfo &info, const arm_compute::CLCompileContext &clCompileContext)
Definition: ClLstmFloatWorkload.cpp:23
armnn::LstmInputParamsInfo::m_ProjectionBias
const TensorInfo * m_ProjectionBias
Definition: LstmParams.hpp:105
armnn::LstmInputParamsInfo::GetForgetLayerNormWeights
const TensorInfo & GetForgetLayerNormWeights() const
Definition: LstmParams.hpp:193
armnn::LstmInputParamsInfo::GetCellLayerNormWeights
const TensorInfo & GetCellLayerNormWeights() const
Definition: LstmParams.hpp:197
armnn::QueueDescriptor::m_Inputs
std::vector< ITensorHandle * > m_Inputs
Definition: WorkloadData.hpp:26
armnn::LstmInputParamsInfo::GetInputToForgetWeights
const TensorInfo & GetInputToForgetWeights() const
Definition: LstmParams.hpp:125