ArmNN
 22.05
LstmLayer.cpp
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1 //
2 // Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 #include "LstmLayer.hpp"
6 
7 #include "LayerCloneBase.hpp"
8 
9 #include <armnn/LstmParams.hpp>
10 #include <armnn/TypesUtils.hpp>
13 
14 namespace armnn
15 {
16 
17 LstmLayer::LstmLayer(const LstmDescriptor& param, const char* name)
18  : LayerWithParameters(3, 4, LayerType::Lstm, param, name)
19 {
20 }
21 
22 std::unique_ptr<IWorkload> LstmLayer::CreateWorkload(const IWorkloadFactory& factory) const
23 {
24  LstmQueueDescriptor descriptor;
25 
26  // Basic parameters
34  descriptor.m_CellBias = m_BasicParameters.m_CellBias.get();
36 
37  // Cifg parameters
39  {
43  }
44 
45  // Projection parameters
47  {
50  }
51 
52  // Peephole parameters
54  {
56  {
58  }
61  }
62 
63  // Layer normalisation parameters
65  {
67  {
69  }
73  }
74 
75  SetAdditionalInfo(descriptor);
76 
77  return factory.CreateWorkload(LayerType::Lstm, descriptor, PrepInfoAndDesc(descriptor));
78 }
79 
81 {
82  auto layer = CloneBase<LstmLayer>(graph, m_Param, GetName());
83 
86  : nullptr;
87  layer->m_BasicParameters.m_InputToCellWeights = m_BasicParameters.m_InputToCellWeights ?
89  layer->m_BasicParameters.m_InputToOutputWeights = m_BasicParameters.m_InputToOutputWeights ?
91  layer->m_BasicParameters.m_RecurrentToForgetWeights = m_BasicParameters.m_RecurrentToForgetWeights ?
93  layer->m_BasicParameters.m_RecurrentToCellWeights = m_BasicParameters.m_RecurrentToCellWeights ?
95  layer->m_BasicParameters.m_RecurrentToOutputWeights = m_BasicParameters.m_RecurrentToOutputWeights ?
97  layer->m_BasicParameters.m_ForgetGateBias = m_BasicParameters.m_ForgetGateBias ?
99  layer->m_BasicParameters.m_CellBias = m_BasicParameters.m_CellBias ?
100  m_BasicParameters.m_CellBias : nullptr;
101  layer->m_BasicParameters.m_OutputGateBias = m_BasicParameters.m_OutputGateBias ?
103 
104  if (!m_Param.m_CifgEnabled)
105  {
106  layer->m_CifgParameters.m_InputToInputWeights = m_CifgParameters.m_InputToInputWeights ?
108  layer->m_CifgParameters.m_RecurrentToInputWeights = m_CifgParameters.m_RecurrentToInputWeights ?
110  layer->m_CifgParameters.m_InputGateBias = m_CifgParameters.m_InputGateBias ?
112  }
113 
114  if (m_Param.m_ProjectionEnabled)
115  {
116  layer->m_ProjectionParameters.m_ProjectionWeights = m_ProjectionParameters.m_ProjectionWeights ?
118  layer->m_ProjectionParameters.m_ProjectionBias = m_ProjectionParameters.m_ProjectionBias ?
120  }
121 
122  if (m_Param.m_PeepholeEnabled)
123  {
124  if (!m_Param.m_CifgEnabled)
125  {
126  layer->m_PeepholeParameters.m_CellToInputWeights = m_PeepholeParameters.m_CellToInputWeights ?
128  }
129  layer->m_PeepholeParameters.m_CellToForgetWeights = m_PeepholeParameters.m_CellToForgetWeights ?
131  layer->m_PeepholeParameters.m_CellToOutputWeights = m_PeepholeParameters.m_CellToOutputWeights ?
133  }
134 
135  if (m_Param.m_LayerNormEnabled)
136  {
137  layer->m_LayerNormParameters.m_InputLayerNormWeights = m_LayerNormParameters.m_InputLayerNormWeights ?
139  layer->m_LayerNormParameters.m_ForgetLayerNormWeights = m_LayerNormParameters.m_ForgetLayerNormWeights ?
141  layer->m_LayerNormParameters.m_CellLayerNormWeights = m_LayerNormParameters.m_CellLayerNormWeights ?
143  layer->m_LayerNormParameters.m_OutputLayerNormWeights = m_LayerNormParameters.m_OutputLayerNormWeights ?
145  }
146 
147  return std::move(layer);
148 }
149 
150 std::vector<TensorShape> LstmLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
151 {
152  ARMNN_ASSERT(inputShapes.size() == 3);
153 
154  // Get input values for validation
155  unsigned int batchSize = inputShapes[0][0];
156  unsigned int outputSize = inputShapes[1][1];
157  unsigned int numUnits = inputShapes[2][1];
158 
159  std::vector<TensorShape> outShapes;
160  outShapes.push_back(TensorShape({batchSize, numUnits * (m_Param.m_CifgEnabled ? 3 : 4)}));
161  outShapes.push_back(TensorShape({batchSize, outputSize}));
162  outShapes.push_back(TensorShape({batchSize, numUnits}));
163  outShapes.push_back(TensorShape({batchSize, outputSize}));
164 
165  return outShapes;
166 }
167 
169 {
171 
172  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
173 
175 
176  auto inferredShapes = InferOutputShapes( {
180  });
181 
182  ARMNN_ASSERT(inferredShapes.size() == 4);
183 
184  // Check if the weights are nullptr
186  "LstmLayer: m_BasicParameters.m_InputToForgetWeights should not be null.");
188  "LstmLayer: m_BasicParameters.m_InputToCellWeights should not be null.");
190  "LstmLayer: m_BasicParameters.m_InputToOutputWeights should not be null.");
192  "LstmLayer: m_BasicParameters.m_RecurrentToForgetWeights should not be null.");
194  "LstmLayer: m_BasicParameters.m_RecurrentToCellWeights should not be null.");
196  "LstmLayer: m_BasicParameters.m_RecurrentToOutputWeights should not be null.");
198  "LstmLayer: m_BasicParameters.m_ForgetGateBias should not be null.");
200  "LstmLayer: m_BasicParameters.m_CellBias should not be null.");
202  "LstmLayer: m_BasicParameters.m_OutputGateBias should not be null.");
203 
204  if (!m_Param.m_CifgEnabled)
205  {
207  "LstmLayer: m_CifgParameters.m_InputToInputWeights should not be null.");
209  "LstmLayer: m_CifgParameters.m_RecurrentToInputWeights should not be null.");
211  "LstmLayer: m_CifgParameters.m_InputGateBias should not be null.");
212 
213  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "LstmLayer");
214  }
215  else
216  {
218  "LstmLayer: m_CifgParameters.m_InputToInputWeights should not have a value when CIFG is enabled.");
220  "LstmLayer: m_CifgParameters.m_RecurrentToInputWeights should not have a value when CIFG is enabled.");
222  "LstmLayer: m_CifgParameters.m_InputGateBias should not have a value when CIFG is enabled.");
223 
224  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "LstmLayer");
225  }
226 
228  {
230  "LstmLayer: m_ProjectionParameters.m_ProjectionWeights should not be null.");
231  }
232 
234  {
235  if (!m_Param.m_CifgEnabled)
236  {
238  "LstmLayer: m_PeepholeParameters.m_CellToInputWeights should not be null "
239  "when Peephole is enabled and CIFG is disabled.");
240  }
242  "LstmLayer: m_PeepholeParameters.m_CellToForgetWeights should not be null.");
244  "LstmLayer: m_PeepholeParameters.m_CellToOutputWeights should not be null.");
245  }
246 
248  GetOutputSlot(1).GetTensorInfo().GetShape(), inferredShapes[1], m_ShapeInferenceMethod, "LstmLayer", 1);
250  GetOutputSlot(2).GetTensorInfo().GetShape(), inferredShapes[2], m_ShapeInferenceMethod, "LstmLayer", 2);
252  GetOutputSlot(3).GetTensorInfo().GetShape(), inferredShapes[3], m_ShapeInferenceMethod, "LstmLayer", 3);
253 
255  {
257  {
259  "LstmLayer: m_LayerNormParameters.m_inputLayerNormWeights should not be null.");
260  }
262  "LstmLayer: m_LayerNormParameters.m_forgetLayerNormWeights should not be null.");
264  "LstmLayer: m_LayerNormParameters.m_cellLayerNormWeights should not be null.");
266  "LstmLayer: m_LayerNormParameters.m_outputLayerNormWeights should not be null.");
267  }
268 }
269 
271 {
272  // For API stability DO NOT ALTER order and add new members to the end of vector
282 
283  // Cifg parameters
287 
288  // Projection parameters
291 
292  // Peephole parameters
296 
297  // Layer normalisation parameters
302 }
303 
305 void LstmLayer::Accept(ILayerVisitor& visitor) const
306 {
307  LstmInputParams inputParams;
317 
318  // Cifg parameters
322 
323  // Projection parameters
326 
327  // Peephole parameters
331 
332  // Layer normalisation parameters
337 
338  ConstTensor inputToInputWeightsTensor;
340  {
341  ConstTensor inputToInputWeightsTensorCopy(managedInputToInputWeights.GetTensorInfo(),
342  managedInputToInputWeights.Map());
343  inputToInputWeightsTensor = inputToInputWeightsTensorCopy;
344  inputParams.m_InputToInputWeights = &inputToInputWeightsTensor;
345  }
346  ConstTensor inputToForgetWeightsTensor;
348  {
349  ConstTensor inputToForgetWeightsTensorCopy(managedInputToForgetWeights.GetTensorInfo(),
350  managedInputToForgetWeights.Map());
351  inputToForgetWeightsTensor = inputToForgetWeightsTensorCopy;
352  inputParams.m_InputToForgetWeights = &inputToForgetWeightsTensor;
353  }
354  ConstTensor inputToCellWeightsTensor;
356  {
357  ConstTensor inputToCellWeightsTensorCopy(managedInputToCellWeights.GetTensorInfo(),
358  managedInputToCellWeights.Map());
359  inputToCellWeightsTensor = inputToCellWeightsTensorCopy;
360  inputParams.m_InputToCellWeights = &inputToCellWeightsTensor;
361  }
362  ConstTensor inputToOutputWeightsTensor;
364  {
365  ConstTensor inputToOutputWeightsTensorCopy(managedInputToOutputWeights.GetTensorInfo(),
366  managedInputToOutputWeights.Map());
367  inputToOutputWeightsTensor = inputToOutputWeightsTensorCopy;
368  inputParams.m_InputToOutputWeights = &inputToOutputWeightsTensor;
369  }
370  ConstTensor recurrentToInputWeightsTensor;
372  {
373  ConstTensor recurrentToInputWeightsTensorCopy(
374  managedRecurrentToInputWeights.GetTensorInfo(),
375  managedRecurrentToInputWeights.Map());
376  recurrentToInputWeightsTensor = recurrentToInputWeightsTensorCopy;
377  inputParams.m_RecurrentToInputWeights = &recurrentToInputWeightsTensor;
378  }
379  ConstTensor recurrentToForgetWeightsTensor;
381  {
382  ConstTensor recurrentToForgetWeightsTensorCopy(
383  managedRecurrentToForgetWeights.GetTensorInfo(),
384  managedRecurrentToForgetWeights.Map());
385  recurrentToForgetWeightsTensor = recurrentToForgetWeightsTensorCopy;
386  inputParams.m_RecurrentToForgetWeights = &recurrentToForgetWeightsTensor;
387  }
388  ConstTensor recurrentToCellWeightsTensor;
390  {
391  ConstTensor recurrentToCellWeightsTensorCopy(
392  managedRecurrentToCellWeights.GetTensorInfo(),
393  managedRecurrentToCellWeights.Map());
394  recurrentToCellWeightsTensor = recurrentToCellWeightsTensorCopy;
395  inputParams.m_RecurrentToCellWeights = &recurrentToCellWeightsTensor;
396  }
397  ConstTensor recurrentToOutputWeightsTensor;
399  {
400  ConstTensor recurrentToOutputWeightsTensorCopy(
401  managedRecurrentToOutputWeights.GetTensorInfo(),
402  managedRecurrentToOutputWeights.Map());
403  recurrentToOutputWeightsTensor = recurrentToOutputWeightsTensorCopy;
404  inputParams.m_RecurrentToOutputWeights = &recurrentToOutputWeightsTensor;
405  }
406  ConstTensor cellToInputWeightsTensor;
408  {
409  ConstTensor cellToInputWeightsTensorCopy(managedCellToInputWeights.GetTensorInfo(),
410  managedCellToInputWeights.Map());
411  cellToInputWeightsTensor = cellToInputWeightsTensorCopy;
412  inputParams.m_CellToInputWeights = &cellToInputWeightsTensor;
413  }
414  ConstTensor cellToForgetWeightsTensor;
416  {
417  ConstTensor cellToForgetWeightsTensorCopy(managedCellToForgetWeights.GetTensorInfo(),
418  managedCellToForgetWeights.Map());
419  cellToForgetWeightsTensor = cellToForgetWeightsTensorCopy;
420  inputParams.m_CellToForgetWeights = &cellToForgetWeightsTensor;
421  }
422  ConstTensor cellToOutputWeightsTensor;
424  {
425  ConstTensor cellToOutputWeightsTensorCopy(managedCellToOutputWeights.GetTensorInfo(),
426  managedCellToOutputWeights.Map());
427  cellToOutputWeightsTensor = cellToOutputWeightsTensorCopy;
428  inputParams.m_CellToOutputWeights = &cellToOutputWeightsTensor;
429  }
430  ConstTensor inputGateBiasTensor;
431  if (m_CifgParameters.m_InputGateBias != nullptr)
432  {
433  ConstTensor inputGateBiasTensorCopy(managedInputGateBias.GetTensorInfo(),
434  managedInputGateBias.Map());
435  inputGateBiasTensor = inputGateBiasTensorCopy;
436  inputParams.m_InputGateBias = &inputGateBiasTensor;
437  }
438  ConstTensor forgetGateBiasTensor;
439  if (m_BasicParameters.m_ForgetGateBias != nullptr)
440  {
441  ConstTensor forgetGateBiasTensorCopy(managedForgetGateBias.GetTensorInfo(),
442  managedForgetGateBias.Map());
443  forgetGateBiasTensor = forgetGateBiasTensorCopy;
444  inputParams.m_ForgetGateBias = &forgetGateBiasTensor;
445  }
446  ConstTensor cellBiasTensor;
447  if (m_BasicParameters.m_CellBias != nullptr)
448  {
449  ConstTensor cellBiasTensorCopy(managedCellBias.GetTensorInfo(),
450  managedCellBias.Map());
451  cellBiasTensor = cellBiasTensorCopy;
452  inputParams.m_CellBias = &cellBiasTensor;
453  }
454  ConstTensor outputGateBias;
455  if (m_BasicParameters.m_OutputGateBias != nullptr)
456  {
457  ConstTensor outputGateBiasCopy(managedOutputGateBias.GetTensorInfo(),
458  managedOutputGateBias.Map());
459  outputGateBias = outputGateBiasCopy;
460  inputParams.m_OutputGateBias = &outputGateBias;
461  }
462  ConstTensor projectionWeightsTensor;
464  {
465  ConstTensor projectionWeightsTensorCopy(managedProjectionWeights.GetTensorInfo(),
466  managedProjectionWeights.Map());
467  projectionWeightsTensor = projectionWeightsTensorCopy;
468  inputParams.m_ProjectionWeights = &projectionWeightsTensor;
469  }
470  ConstTensor projectionBiasTensor;
472  {
473  ConstTensor projectionBiasTensorCopy(managedProjectionBias.GetTensorInfo(),
474  managedProjectionBias.Map());
475  projectionBiasTensor = projectionBiasTensorCopy;
476  inputParams.m_ProjectionBias = &projectionBiasTensor;
477  }
478  ConstTensor inputLayerNormTensor;
480  {
481  ConstTensor inputLayerNormTensorCopy(managedInputLayerNormWeights.GetTensorInfo(),
482  managedInputLayerNormWeights.Map());
483  inputLayerNormTensor = inputLayerNormTensorCopy;
484  inputParams.m_InputLayerNormWeights = &inputLayerNormTensor;
485  }
486  ConstTensor forgetLayerNormTensor;
488  {
489  ConstTensor forgetLayerNormTensorCopy(managedForgetLayerNormWeights.GetTensorInfo(),
490  managedForgetLayerNormWeights.Map());
491  forgetLayerNormTensor = forgetLayerNormTensorCopy;
492  inputParams.m_ForgetLayerNormWeights = &forgetLayerNormTensor;
493  }
494  ConstTensor cellLayerNormTensor;
496  {
497  ConstTensor cellLayerNormTensorCopy(managedCellLayerNormWeights.GetTensorInfo(),
498  managedCellLayerNormWeights.Map());
499  cellLayerNormTensor = cellLayerNormTensorCopy;
500  inputParams.m_CellLayerNormWeights = &cellLayerNormTensor;
501  }
502  ConstTensor outputLayerNormTensor;
504  {
505  ConstTensor outputLayerNormTensorCopy(managedOutputLayerNormWeights.GetTensorInfo(),
506  managedOutputLayerNormWeights.Map());
507  outputLayerNormTensor = outputLayerNormTensorCopy;
508  inputParams.m_OutputLayerNormWeights = &outputLayerNormTensor;
509  }
510 
511 
512  visitor.VisitLstmLayer(this, GetParameters(), inputParams, GetName());
513 }
515 
517 {
518  std::vector<ConstTensor> constTensors;
519 
520  LstmDescriptor descriptor = GetParameters();
521 
531 
532  // Cifg parameters
536 
537  // Projection parameters
540 
541  // Peephole parameters
545 
546  // Layer normalisation parameters
551 
552  // First add mandatory/basic parameters
554  {
555  constTensors.emplace_back(ConstTensor(managedInputToForgetWeights.GetTensorInfo(),
556  managedInputToForgetWeights.Map()));
557  }
559  {
560  constTensors.emplace_back(ConstTensor(managedInputToCellWeights.GetTensorInfo(),
561  managedInputToCellWeights.Map()));
562  }
564  {
565  constTensors.emplace_back(ConstTensor(managedInputToOutputWeights.GetTensorInfo(),
566  managedInputToOutputWeights.Map()));
567  }
569  {
570  constTensors.emplace_back(ConstTensor(
571  managedRecurrentToForgetWeights.GetTensorInfo(),
572  managedRecurrentToForgetWeights.Map()));
573  }
575  {
576  constTensors.emplace_back(ConstTensor(
577  managedRecurrentToCellWeights.GetTensorInfo(),
578  managedRecurrentToCellWeights.Map()));
579  }
581  {
582  constTensors.emplace_back(ConstTensor(
583  managedRecurrentToOutputWeights.GetTensorInfo(),
584  managedRecurrentToOutputWeights.Map()));
585  }
586  if (m_BasicParameters.m_ForgetGateBias != nullptr)
587  {
588  constTensors.emplace_back(ConstTensor(managedForgetGateBias.GetTensorInfo(),
589  managedForgetGateBias.Map()));
590  }
591  if (m_BasicParameters.m_CellBias != nullptr)
592  {
593  constTensors.emplace_back(ConstTensor(managedCellBias.GetTensorInfo(),
594  managedCellBias.Map()));
595  }
596  if (m_BasicParameters.m_OutputGateBias != nullptr)
597  {
598  constTensors.emplace_back(ConstTensor(managedOutputGateBias.GetTensorInfo(),
599  managedOutputGateBias.Map()));
600  }
601 
602  // Add cifg parameters
603  if (!descriptor.m_CifgEnabled)
604  {
606  {
607  constTensors.emplace_back(ConstTensor(managedInputToInputWeights.GetTensorInfo(),
608  managedInputToInputWeights.Map()));
609  }
611  {
612  constTensors.emplace_back(ConstTensor(
613  managedRecurrentToInputWeights.GetTensorInfo(),
614  managedRecurrentToInputWeights.Map()));
615  }
616  if (m_CifgParameters.m_InputGateBias != nullptr)
617  {
618  constTensors.emplace_back(ConstTensor(managedInputGateBias.GetTensorInfo(),
619  managedInputGateBias.Map()));
620  }
621  }
622 
623  // Add peephole parameters
624  if (descriptor.m_PeepholeEnabled)
625  {
626  if (!descriptor.m_CifgEnabled)
627  {
629  {
630  constTensors.emplace_back(ConstTensor(managedCellToInputWeights.GetTensorInfo(),
631  managedCellToInputWeights.Map()));
632  }
633  }
635  {
636  constTensors.emplace_back(ConstTensor(managedCellToForgetWeights.GetTensorInfo(),
637  managedCellToForgetWeights.Map()));
638  }
640  {
641  constTensors.emplace_back(ConstTensor(managedCellToOutputWeights.GetTensorInfo(),
642  managedCellToOutputWeights.Map()));
643  }
644  }
645 
646  // Add projection parameters
647  if (descriptor.m_ProjectionEnabled)
648  {
650  {
651  constTensors.emplace_back(ConstTensor(managedProjectionWeights.GetTensorInfo(),
652  managedProjectionWeights.Map()));
653  }
655  {
656  constTensors.emplace_back(ConstTensor(managedProjectionBias.GetTensorInfo(),
657  managedProjectionBias.Map()));
658  }
659  }
660 
661  // Add norm parameters
662  if (descriptor.m_LayerNormEnabled)
663  {
664  if (!descriptor.m_CifgEnabled)
665  {
667  {
668  constTensors.emplace_back(ConstTensor(managedInputLayerNormWeights.GetTensorInfo(),
669  managedInputLayerNormWeights.Map()));
670  }
671  }
673  {
674  constTensors.emplace_back(ConstTensor(managedForgetLayerNormWeights.GetTensorInfo(),
675  managedForgetLayerNormWeights.Map()));
676  }
678  {
679  constTensors.emplace_back(ConstTensor(managedCellLayerNormWeights.GetTensorInfo(),
680  managedCellLayerNormWeights.Map()));
681  }
683  {
684  constTensors.emplace_back(ConstTensor(managedOutputLayerNormWeights.GetTensorInfo(),
685  managedOutputLayerNormWeights.Map()));
686  }
687  }
688 
689  strategy.ExecuteStrategy(this, GetParameters(), constTensors, GetName());
690 }
691 
692 } // namespace armnn
std::shared_ptr< ConstTensorHandle > m_ForgetGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
std::shared_ptr< ConstTensorHandle > m_OutputGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
bool m_ProjectionEnabled
Enable/disable the projection layer.
LstmBasicParameters m_BasicParameters
Definition: LstmLayer.hpp:20
const ConstTensor * m_ProjectionWeights
Definition: LstmParams.hpp:55
const ConstTensorHandle * m_ProjectionWeights
const ConstTensorHandle * m_RecurrentToForgetWeights
std::shared_ptr< ConstTensorHandle > m_OutputLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
const ConstTensor * m_CellBias
Definition: LstmParams.hpp:53
std::shared_ptr< ConstTensorHandle > m_CellToForgetWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
LstmDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
const TensorShape & GetShape() const
Definition: Tensor.hpp:191
ARMNN_NO_DEPRECATE_WARN_END void ExecuteStrategy(IStrategy &strategy) const override
Apply a visitor to this layer.
Definition: LstmLayer.cpp:516
const ConstTensorHandle * m_InputGateBias
const ConstTensor * m_CellToOutputWeights
Definition: LstmParams.hpp:50
#define ARMNN_NO_DEPRECATE_WARN_BEGIN
Definition: Deprecated.hpp:33
const ConstTensorHandle * m_RecurrentToCellWeights
const ConstTensorHandle * m_CellBias
virtual void ExecuteStrategy(const armnn::IConnectableLayer *layer, const armnn::BaseDescriptor &descriptor, const std::vector< armnn::ConstTensor > &constants, const char *name, const armnn::LayerBindingId id=0)=0
const ConstTensor * m_CellToInputWeights
Definition: LstmParams.hpp:48
std::shared_ptr< ConstTensorHandle > m_InputLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
const ConstTensor * m_InputGateBias
Definition: LstmParams.hpp:51
const ConstTensor * m_RecurrentToCellWeights
Definition: LstmParams.hpp:46
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the LSTM type.
Definition: LstmLayer.cpp:22
const ConstTensorHandle * m_InputToOutputWeights
std::shared_ptr< ConstTensorHandle > m_ProjectionWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
const ConstTensorHandle * m_OutputLayerNormWeights
const ConstTensor * m_ForgetLayerNormWeights
Definition: LstmParams.hpp:58
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:491
const ConstTensor * m_CellToForgetWeights
Definition: LstmParams.hpp:49
const TensorInfo & GetTensorInfo() const
Copyright (c) 2021 ARM Limited and Contributors.
std::shared_ptr< ConstTensorHandle > m_InputToCellWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
const LstmDescriptor & GetParameters() const override
This layer represents a LSTM operation.
Definition: LstmLayer.hpp:16
const IOutputSlot * GetConnection() const override
Definition: Layer.hpp:204
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
Definition: Layer.cpp:422
const ConstTensor * m_OutputGateBias
Definition: LstmParams.hpp:54
std::shared_ptr< ConstTensorHandle > m_InputGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
const ConstTensorHandle * m_OutputGateBias
std::shared_ptr< ConstTensorHandle > m_CellToOutputWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:378
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:322
const ConstTensor * m_InputLayerNormWeights
Definition: LstmParams.hpp:57
std::shared_ptr< ConstTensorHandle > m_RecurrentToCellWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of LstmLayer.
Definition: LstmLayer.cpp:168
std::shared_ptr< ConstTensorHandle > m_CellBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
const ConstTensorHandle * m_CellLayerNormWeights
std::vector< std::reference_wrapper< std::shared_ptr< ConstTensorHandle > >> ConstantTensors
Definition: INetwork.hpp:124
const ConstTensor * m_RecurrentToOutputWeights
Definition: LstmParams.hpp:47
LstmLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
Definition: LstmLayer.cpp:80
An LstmDescriptor for the LstmLayer.
#define ARMNN_NO_DEPRECATE_WARN_END
Definition: Deprecated.hpp:34
#define ARMNN_ASSERT_MSG(COND, MSG)
Definition: Assert.hpp:15
const ConstTensor * m_ProjectionBias
Definition: LstmParams.hpp:56
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
Definition: Tensor.hpp:327
std::shared_ptr< ConstTensorHandle > m_RecurrentToInputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
bool m_PeepholeEnabled
Enable/disable peephole.
const ConstTensorHandle * m_CellToOutputWeights
std::shared_ptr< ConstTensorHandle > m_CellLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
LstmOptLayerNormParameters m_LayerNormParameters
Definition: LstmLayer.hpp:24
std::shared_ptr< ConstTensorHandle > m_RecurrentToOutputWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
const ConstTensorHandle * m_InputToCellWeights
std::shared_ptr< ConstTensorHandle > m_InputToInputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
const ConstTensorHandle * m_InputToForgetWeights
ARMNN_NO_DEPRECATE_WARN_BEGIN void Accept(ILayerVisitor &visitor) const override
Definition: LstmLayer.cpp:305
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203
std::shared_ptr< ConstTensorHandle > m_ProjectionBias
A unique pointer to represent 1D weights tensor with dimensions [output_size].
const ConstTensorHandle * m_RecurrentToInputWeights
Layer::ConstantTensors GetConstantTensorsByRef() override
Retrieve the handles to the constant values stored by the layer.
Definition: LstmLayer.cpp:270
LstmOptPeepholeParameters m_PeepholeParameters
Definition: LstmLayer.hpp:23
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:274
const ConstTensor * m_CellLayerNormWeights
Definition: LstmParams.hpp:59
const ConstTensor * m_ForgetGateBias
Definition: LstmParams.hpp:52
const ConstTensor * m_InputToCellWeights
Definition: LstmParams.hpp:42
const ConstTensorHandle * m_ForgetGateBias
const ConstTensor * m_InputToOutputWeights
Definition: LstmParams.hpp:43
LstmOptProjectionParameters m_ProjectionParameters
Definition: LstmLayer.hpp:22
bool m_CifgEnabled
Enable/disable cifg (coupled input & forget gate).
std::shared_ptr< ConstTensorHandle > m_InputToForgetWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
const ConstTensor * m_RecurrentToForgetWeights
Definition: LstmParams.hpp:45
std::shared_ptr< ConstTensorHandle > m_RecurrentToForgetWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
const ConstTensorHandle * m_CellToForgetWeights
const ConstTensorHandle * m_ProjectionBias
const ConstTensor * m_RecurrentToInputWeights
Definition: LstmParams.hpp:44
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *LayerCreateWorkload.
LstmLayer(const LstmDescriptor &param, const char *name)
Constructor to create a LstmLayer.
Definition: LstmLayer.cpp:17
bool m_LayerNormEnabled
Enable/disable layer normalization.
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
Definition: Layer.hpp:324
const ConstTensorHandle * m_ForgetLayerNormWeights
virtual const TensorInfo & GetTensorInfo() const =0
LstmOptCifgParameters m_CifgParameters
Definition: LstmLayer.hpp:21
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:317
const ConstTensorHandle * m_InputLayerNormWeights
std::shared_ptr< ConstTensorHandle > m_ForgetLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override
By default returns inputShapes if the number of inputs are equal to number of outputs, otherwise infers the output shapes from given input shapes and layer properties.
Definition: LstmLayer.cpp:150
std::shared_ptr< ConstTensorHandle > m_CellToInputWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
const ConstTensor * m_OutputLayerNormWeights
Definition: LstmParams.hpp:60
const void * Map(bool blocking=true)
RAII Managed resource Unmaps MemoryArea once out of scope.
const TensorInfo & GetTensorInfo(const ITensorHandle *tensorHandle)
float32 helpers
const ConstTensorHandle * m_CellToInputWeights
virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:92
const ConstTensorHandle * m_InputToInputWeights
ShapeInferenceMethod m_ShapeInferenceMethod
Definition: Layer.hpp:421
const ConstTensor * m_InputToForgetWeights
Definition: LstmParams.hpp:41
std::shared_ptr< ConstTensorHandle > m_InputToOutputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
LayerType
When adding a new layer, adapt also the LastLayer enum value in the enum class LayerType below...
Definition: Types.hpp:467
const ConstTensor * m_InputToInputWeights
Definition: LstmParams.hpp:40
const ConstTensorHandle * m_RecurrentToOutputWeights