ArmNN
 21.08
LstmSerializationTests.cpp
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1 //
2 // Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
6 #include "../Serializer.hpp"
7 #include "SerializerTestUtils.hpp"
8 
9 #include <armnn/Descriptors.hpp>
10 #include <armnn/INetwork.hpp>
11 #include <armnn/IRuntime.hpp>
12 #include <armnnDeserializer/IDeserializer.hpp>
13 #include <armnn/utility/IgnoreUnused.hpp>
14 #include <armnn/LstmParams.hpp>
15 #include <armnn/QuantizedLstmParams.hpp>
16 
17 #include <doctest/doctest.h>
18 #include <fmt/format.h>
19 
20 
21 TEST_SUITE("SerializerTests")
22 {
23 template<typename Descriptor>
24 armnn::LstmInputParams ConstantVector2LstmInputParams(const std::vector<armnn::ConstTensor>& constants,
25  Descriptor& descriptor)
26 {
27  armnn::LstmInputParams lstmInputParams;
28  size_t i = 0;
29 
30  // Inserting basic paramters
31  lstmInputParams.m_InputToForgetWeights = &constants[i++];
32  lstmInputParams.m_InputToCellWeights = &constants[i++];
33  lstmInputParams.m_InputToOutputWeights = &constants[i++];
34  lstmInputParams.m_RecurrentToForgetWeights = &constants[i++];
35  lstmInputParams.m_RecurrentToCellWeights = &constants[i++];
36  lstmInputParams.m_RecurrentToOutputWeights = &constants[i++];
37  lstmInputParams.m_ForgetGateBias = &constants[i++];
38  lstmInputParams.m_CellBias = &constants[i++];
39  lstmInputParams.m_OutputGateBias = &constants[i++];
40  if (!descriptor.m_CifgEnabled)
41  {
42  lstmInputParams.m_InputToInputWeights = &constants[i++];
43  lstmInputParams.m_RecurrentToInputWeights = &constants[i++];
44  lstmInputParams.m_InputGateBias = &constants[i++];
45  }
46 
47  if (descriptor.m_PeepholeEnabled)
48  {
49  if (!descriptor.m_CifgEnabled)
50  {
51  lstmInputParams.m_CellToInputWeights = &constants[i++];
52  }
53  lstmInputParams.m_CellToForgetWeights = &constants[i++];
54  lstmInputParams.m_CellToOutputWeights = &constants[i++];
55  }
56 
57  if (descriptor.m_ProjectionEnabled)
58  {
59  lstmInputParams.m_ProjectionWeights = &constants[i++];
60  lstmInputParams.m_ProjectionBias = &constants[i++];
61  }
62 
63  if (descriptor.m_LayerNormEnabled)
64  {
65  if (!descriptor.m_CifgEnabled)
66  {
67  lstmInputParams.m_InputLayerNormWeights = &constants[i++];
68  }
69  lstmInputParams.m_ForgetLayerNormWeights = &constants[i++];
70  lstmInputParams.m_CellLayerNormWeights = &constants[i++];
71  lstmInputParams.m_OutputLayerNormWeights = &constants[i++];
72  }
73 
74  return lstmInputParams;
75 }
76 
77 // Works for Lstm, UnidirectionalSequenceLstm and QLstm (QuantizedLstm uses different parameters)
78 template<typename Descriptor>
79 class VerifyLstmLayer : public LayerVerifierBaseWithDescriptor<Descriptor>
80 {
81 public:
82  VerifyLstmLayer(const std::string& layerName,
83  const std::vector<armnn::TensorInfo>& inputInfos,
84  const std::vector<armnn::TensorInfo>& outputInfos,
85  const Descriptor& descriptor,
86  const armnn::LstmInputParams& inputParams)
87  : LayerVerifierBaseWithDescriptor<Descriptor>(layerName, inputInfos, outputInfos, descriptor)
88  , m_InputParams(inputParams) {}
89 
90  void ExecuteStrategy(const armnn::IConnectableLayer* layer,
91  const armnn::BaseDescriptor& descriptor,
92  const std::vector<armnn::ConstTensor>& constants,
93  const char* name,
94  const armnn::LayerBindingId id = 0) override
95  {
96  armnn::IgnoreUnused(constants, id);
97  switch (layer->GetType())
98  {
99  case armnn::LayerType::Input: break;
100  case armnn::LayerType::Output: break;
101  case armnn::LayerType::Lstm:
102  case armnn::LayerType::UnidirectionalSequenceLstm:
103  {
104  this->VerifyNameAndConnections(layer, name);
105  const Descriptor& internalDescriptor = static_cast<const Descriptor&>(descriptor);
106  this->VerifyDescriptor(internalDescriptor);
107  armnn::LstmInputParams lstmParams = ConstantVector2LstmInputParams(constants, internalDescriptor);
108  VerifyInputParameters(lstmParams);
109  break;
110  }
111  case armnn::LayerType::QLstm:
112  {
113  this->VerifyNameAndConnections(layer, name);
114  const Descriptor& internalDescriptor = static_cast<const Descriptor&>(descriptor);
115  this->VerifyDescriptor(internalDescriptor);
116  armnn::LstmInputParams lstmParams = ConstantVector2LstmInputParams(constants, internalDescriptor);
117  VerifyInputParameters(lstmParams);
118  break;
119  }
120  default:
121  {
122  throw armnn::Exception("Unexpected layer type in Lstm test model");
123  }
124  }
125  }
126 
127 protected:
128  void VerifyInputParameters(const armnn::LstmInputParams& params)
129  {
130  this->VerifyConstTensors(
131  "m_InputToInputWeights", m_InputParams.m_InputToInputWeights, params.m_InputToInputWeights);
132  this->VerifyConstTensors(
133  "m_InputToForgetWeights", m_InputParams.m_InputToForgetWeights, params.m_InputToForgetWeights);
134  this->VerifyConstTensors(
135  "m_InputToCellWeights", m_InputParams.m_InputToCellWeights, params.m_InputToCellWeights);
136  this->VerifyConstTensors(
137  "m_InputToOutputWeights", m_InputParams.m_InputToOutputWeights, params.m_InputToOutputWeights);
138  this->VerifyConstTensors(
139  "m_RecurrentToInputWeights", m_InputParams.m_RecurrentToInputWeights, params.m_RecurrentToInputWeights);
140  this->VerifyConstTensors(
141  "m_RecurrentToForgetWeights", m_InputParams.m_RecurrentToForgetWeights, params.m_RecurrentToForgetWeights);
142  this->VerifyConstTensors(
143  "m_RecurrentToCellWeights", m_InputParams.m_RecurrentToCellWeights, params.m_RecurrentToCellWeights);
144  this->VerifyConstTensors(
145  "m_RecurrentToOutputWeights", m_InputParams.m_RecurrentToOutputWeights, params.m_RecurrentToOutputWeights);
146  this->VerifyConstTensors(
147  "m_CellToInputWeights", m_InputParams.m_CellToInputWeights, params.m_CellToInputWeights);
148  this->VerifyConstTensors(
149  "m_CellToForgetWeights", m_InputParams.m_CellToForgetWeights, params.m_CellToForgetWeights);
150  this->VerifyConstTensors(
151  "m_CellToOutputWeights", m_InputParams.m_CellToOutputWeights, params.m_CellToOutputWeights);
152  this->VerifyConstTensors(
153  "m_InputGateBias", m_InputParams.m_InputGateBias, params.m_InputGateBias);
154  this->VerifyConstTensors(
155  "m_ForgetGateBias", m_InputParams.m_ForgetGateBias, params.m_ForgetGateBias);
156  this->VerifyConstTensors(
157  "m_CellBias", m_InputParams.m_CellBias, params.m_CellBias);
158  this->VerifyConstTensors(
159  "m_OutputGateBias", m_InputParams.m_OutputGateBias, params.m_OutputGateBias);
160  this->VerifyConstTensors(
161  "m_ProjectionWeights", m_InputParams.m_ProjectionWeights, params.m_ProjectionWeights);
162  this->VerifyConstTensors(
163  "m_ProjectionBias", m_InputParams.m_ProjectionBias, params.m_ProjectionBias);
164  this->VerifyConstTensors(
165  "m_InputLayerNormWeights", m_InputParams.m_InputLayerNormWeights, params.m_InputLayerNormWeights);
166  this->VerifyConstTensors(
167  "m_ForgetLayerNormWeights", m_InputParams.m_ForgetLayerNormWeights, params.m_ForgetLayerNormWeights);
168  this->VerifyConstTensors(
169  "m_CellLayerNormWeights", m_InputParams.m_CellLayerNormWeights, params.m_CellLayerNormWeights);
170  this->VerifyConstTensors(
171  "m_OutputLayerNormWeights", m_InputParams.m_OutputLayerNormWeights, params.m_OutputLayerNormWeights);
172  }
173 
174 private:
175  armnn::LstmInputParams m_InputParams;
176 };
177 
178 TEST_CASE("SerializeDeserializeLstmCifgPeepholeNoProjection")
179 {
180  armnn::LstmDescriptor descriptor;
181  descriptor.m_ActivationFunc = 4;
182  descriptor.m_ClippingThresProj = 0.0f;
183  descriptor.m_ClippingThresCell = 0.0f;
184  descriptor.m_CifgEnabled = true; // if this is true then we DON'T need to set the OptCifgParams
185  descriptor.m_ProjectionEnabled = false;
186  descriptor.m_PeepholeEnabled = true;
187 
188  const uint32_t batchSize = 1;
189  const uint32_t inputSize = 2;
190  const uint32_t numUnits = 4;
191  const uint32_t outputSize = numUnits;
192 
193  armnn::TensorInfo inputWeightsInfo1({numUnits, inputSize}, armnn::DataType::Float32);
194  std::vector<float> inputToForgetWeightsData = GenerateRandomData<float>(inputWeightsInfo1.GetNumElements());
195  armnn::ConstTensor inputToForgetWeights(inputWeightsInfo1, inputToForgetWeightsData);
196 
197  std::vector<float> inputToCellWeightsData = GenerateRandomData<float>(inputWeightsInfo1.GetNumElements());
198  armnn::ConstTensor inputToCellWeights(inputWeightsInfo1, inputToCellWeightsData);
199 
200  std::vector<float> inputToOutputWeightsData = GenerateRandomData<float>(inputWeightsInfo1.GetNumElements());
201  armnn::ConstTensor inputToOutputWeights(inputWeightsInfo1, inputToOutputWeightsData);
202 
203  armnn::TensorInfo inputWeightsInfo2({numUnits, outputSize}, armnn::DataType::Float32);
204  std::vector<float> recurrentToForgetWeightsData = GenerateRandomData<float>(inputWeightsInfo2.GetNumElements());
205  armnn::ConstTensor recurrentToForgetWeights(inputWeightsInfo2, recurrentToForgetWeightsData);
206 
207  std::vector<float> recurrentToCellWeightsData = GenerateRandomData<float>(inputWeightsInfo2.GetNumElements());
208  armnn::ConstTensor recurrentToCellWeights(inputWeightsInfo2, recurrentToCellWeightsData);
209 
210  std::vector<float> recurrentToOutputWeightsData = GenerateRandomData<float>(inputWeightsInfo2.GetNumElements());
211  armnn::ConstTensor recurrentToOutputWeights(inputWeightsInfo2, recurrentToOutputWeightsData);
212 
213  armnn::TensorInfo inputWeightsInfo3({numUnits}, armnn::DataType::Float32);
214  std::vector<float> cellToForgetWeightsData = GenerateRandomData<float>(inputWeightsInfo3.GetNumElements());
215  armnn::ConstTensor cellToForgetWeights(inputWeightsInfo3, cellToForgetWeightsData);
216 
217  std::vector<float> cellToOutputWeightsData = GenerateRandomData<float>(inputWeightsInfo3.GetNumElements());
218  armnn::ConstTensor cellToOutputWeights(inputWeightsInfo3, cellToOutputWeightsData);
219 
220  std::vector<float> forgetGateBiasData(numUnits, 1.0f);
221  armnn::ConstTensor forgetGateBias(inputWeightsInfo3, forgetGateBiasData);
222 
223  std::vector<float> cellBiasData(numUnits, 0.0f);
224  armnn::ConstTensor cellBias(inputWeightsInfo3, cellBiasData);
225 
226  std::vector<float> outputGateBiasData(numUnits, 0.0f);
227  armnn::ConstTensor outputGateBias(inputWeightsInfo3, outputGateBiasData);
228 
229  armnn::LstmInputParams params;
230  params.m_InputToForgetWeights = &inputToForgetWeights;
231  params.m_InputToCellWeights = &inputToCellWeights;
232  params.m_InputToOutputWeights = &inputToOutputWeights;
233  params.m_RecurrentToForgetWeights = &recurrentToForgetWeights;
234  params.m_RecurrentToCellWeights = &recurrentToCellWeights;
235  params.m_RecurrentToOutputWeights = &recurrentToOutputWeights;
236  params.m_ForgetGateBias = &forgetGateBias;
237  params.m_CellBias = &cellBias;
238  params.m_OutputGateBias = &outputGateBias;
239  params.m_CellToForgetWeights = &cellToForgetWeights;
240  params.m_CellToOutputWeights = &cellToOutputWeights;
241 
242  armnn::INetworkPtr network = armnn::INetwork::Create();
243  armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
244  armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(1);
245  armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(2);
246  const std::string layerName("lstm");
247  armnn::IConnectableLayer* const lstmLayer = network->AddLstmLayer(descriptor, params, layerName.c_str());
248  armnn::IConnectableLayer* const scratchBuffer = network->AddOutputLayer(0);
249  armnn::IConnectableLayer* const outputStateOut = network->AddOutputLayer(1);
250  armnn::IConnectableLayer* const cellStateOut = network->AddOutputLayer(2);
251  armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(3);
252 
253  // connect up
254  armnn::TensorInfo inputTensorInfo({ batchSize, inputSize }, armnn::DataType::Float32);
255  armnn::TensorInfo cellStateTensorInfo({ batchSize, numUnits}, armnn::DataType::Float32);
256  armnn::TensorInfo outputStateTensorInfo({ batchSize, outputSize }, armnn::DataType::Float32);
257  armnn::TensorInfo lstmTensorInfoScratchBuff({ batchSize, numUnits * 3 }, armnn::DataType::Float32);
258 
259  inputLayer->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(0));
260  inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
261 
262  outputStateIn->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(1));
263  outputStateIn->GetOutputSlot(0).SetTensorInfo(outputStateTensorInfo);
264 
265  cellStateIn->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(2));
266  cellStateIn->GetOutputSlot(0).SetTensorInfo(cellStateTensorInfo);
267 
268  lstmLayer->GetOutputSlot(0).Connect(scratchBuffer->GetInputSlot(0));
269  lstmLayer->GetOutputSlot(0).SetTensorInfo(lstmTensorInfoScratchBuff);
270 
271  lstmLayer->GetOutputSlot(1).Connect(outputStateOut->GetInputSlot(0));
272  lstmLayer->GetOutputSlot(1).SetTensorInfo(outputStateTensorInfo);
273 
274  lstmLayer->GetOutputSlot(2).Connect(cellStateOut->GetInputSlot(0));
275  lstmLayer->GetOutputSlot(2).SetTensorInfo(cellStateTensorInfo);
276 
277  lstmLayer->GetOutputSlot(3).Connect(outputLayer->GetInputSlot(0));
278  lstmLayer->GetOutputSlot(3).SetTensorInfo(outputStateTensorInfo);
279 
280  armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
281  CHECK(deserializedNetwork);
282 
283  VerifyLstmLayer<armnn::LstmDescriptor> checker(
284  layerName,
285  {inputTensorInfo, outputStateTensorInfo, cellStateTensorInfo},
286  {lstmTensorInfoScratchBuff, outputStateTensorInfo, cellStateTensorInfo, outputStateTensorInfo},
287  descriptor,
288  params);
289  deserializedNetwork->ExecuteStrategy(checker);
290 }
291 
292 TEST_CASE("SerializeDeserializeLstmNoCifgWithPeepholeAndProjection")
293 {
294  armnn::LstmDescriptor descriptor;
295  descriptor.m_ActivationFunc = 4;
296  descriptor.m_ClippingThresProj = 0.0f;
297  descriptor.m_ClippingThresCell = 0.0f;
298  descriptor.m_CifgEnabled = false; // if this is true then we DON'T need to set the OptCifgParams
299  descriptor.m_ProjectionEnabled = true;
300  descriptor.m_PeepholeEnabled = true;
301 
302  const uint32_t batchSize = 2;
303  const uint32_t inputSize = 5;
304  const uint32_t numUnits = 20;
305  const uint32_t outputSize = 16;
306 
307  armnn::TensorInfo tensorInfo20x5({numUnits, inputSize}, armnn::DataType::Float32);
308  std::vector<float> inputToInputWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
309  armnn::ConstTensor inputToInputWeights(tensorInfo20x5, inputToInputWeightsData);
310 
311  std::vector<float> inputToForgetWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
312  armnn::ConstTensor inputToForgetWeights(tensorInfo20x5, inputToForgetWeightsData);
313 
314  std::vector<float> inputToCellWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
315  armnn::ConstTensor inputToCellWeights(tensorInfo20x5, inputToCellWeightsData);
316 
317  std::vector<float> inputToOutputWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
318  armnn::ConstTensor inputToOutputWeights(tensorInfo20x5, inputToOutputWeightsData);
319 
320  armnn::TensorInfo tensorInfo20({numUnits}, armnn::DataType::Float32);
321  std::vector<float> inputGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
322  armnn::ConstTensor inputGateBias(tensorInfo20, inputGateBiasData);
323 
324  std::vector<float> forgetGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
325  armnn::ConstTensor forgetGateBias(tensorInfo20, forgetGateBiasData);
326 
327  std::vector<float> cellBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
328  armnn::ConstTensor cellBias(tensorInfo20, cellBiasData);
329 
330  std::vector<float> outputGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
331  armnn::ConstTensor outputGateBias(tensorInfo20, outputGateBiasData);
332 
333  armnn::TensorInfo tensorInfo20x16({numUnits, outputSize}, armnn::DataType::Float32);
334  std::vector<float> recurrentToInputWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
335  armnn::ConstTensor recurrentToInputWeights(tensorInfo20x16, recurrentToInputWeightsData);
336 
337  std::vector<float> recurrentToForgetWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
338  armnn::ConstTensor recurrentToForgetWeights(tensorInfo20x16, recurrentToForgetWeightsData);
339 
340  std::vector<float> recurrentToCellWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
341  armnn::ConstTensor recurrentToCellWeights(tensorInfo20x16, recurrentToCellWeightsData);
342 
343  std::vector<float> recurrentToOutputWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
344  armnn::ConstTensor recurrentToOutputWeights(tensorInfo20x16, recurrentToOutputWeightsData);
345 
346  std::vector<float> cellToInputWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
347  armnn::ConstTensor cellToInputWeights(tensorInfo20, cellToInputWeightsData);
348 
349  std::vector<float> cellToForgetWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
350  armnn::ConstTensor cellToForgetWeights(tensorInfo20, cellToForgetWeightsData);
351 
352  std::vector<float> cellToOutputWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
353  armnn::ConstTensor cellToOutputWeights(tensorInfo20, cellToOutputWeightsData);
354 
355  armnn::TensorInfo tensorInfo16x20({outputSize, numUnits}, armnn::DataType::Float32);
356  std::vector<float> projectionWeightsData = GenerateRandomData<float>(tensorInfo16x20.GetNumElements());
357  armnn::ConstTensor projectionWeights(tensorInfo16x20, projectionWeightsData);
358 
359  armnn::TensorInfo tensorInfo16({outputSize}, armnn::DataType::Float32);
360  std::vector<float> projectionBiasData(outputSize, 0.f);
361  armnn::ConstTensor projectionBias(tensorInfo16, projectionBiasData);
362 
363  armnn::LstmInputParams params;
364  params.m_InputToForgetWeights = &inputToForgetWeights;
365  params.m_InputToCellWeights = &inputToCellWeights;
366  params.m_InputToOutputWeights = &inputToOutputWeights;
367  params.m_RecurrentToForgetWeights = &recurrentToForgetWeights;
368  params.m_RecurrentToCellWeights = &recurrentToCellWeights;
369  params.m_RecurrentToOutputWeights = &recurrentToOutputWeights;
370  params.m_ForgetGateBias = &forgetGateBias;
371  params.m_CellBias = &cellBias;
372  params.m_OutputGateBias = &outputGateBias;
373 
374  // additional params because: descriptor.m_CifgEnabled = false
375  params.m_InputToInputWeights = &inputToInputWeights;
376  params.m_RecurrentToInputWeights = &recurrentToInputWeights;
377  params.m_CellToInputWeights = &cellToInputWeights;
378  params.m_InputGateBias = &inputGateBias;
379 
380  // additional params because: descriptor.m_ProjectionEnabled = true
381  params.m_ProjectionWeights = &projectionWeights;
382  params.m_ProjectionBias = &projectionBias;
383 
384  // additional params because: descriptor.m_PeepholeEnabled = true
385  params.m_CellToForgetWeights = &cellToForgetWeights;
386  params.m_CellToOutputWeights = &cellToOutputWeights;
387 
388  armnn::INetworkPtr network = armnn::INetwork::Create();
389  armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
390  armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(1);
391  armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(2);
392  const std::string layerName("lstm");
393  armnn::IConnectableLayer* const lstmLayer = network->AddLstmLayer(descriptor, params, layerName.c_str());
394  armnn::IConnectableLayer* const scratchBuffer = network->AddOutputLayer(0);
395  armnn::IConnectableLayer* const outputStateOut = network->AddOutputLayer(1);
396  armnn::IConnectableLayer* const cellStateOut = network->AddOutputLayer(2);
397  armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(3);
398 
399  // connect up
400  armnn::TensorInfo inputTensorInfo({ batchSize, inputSize }, armnn::DataType::Float32);
401  armnn::TensorInfo cellStateTensorInfo({ batchSize, numUnits}, armnn::DataType::Float32);
402  armnn::TensorInfo outputStateTensorInfo({ batchSize, outputSize }, armnn::DataType::Float32);
403  armnn::TensorInfo lstmTensorInfoScratchBuff({ batchSize, numUnits * 4 }, armnn::DataType::Float32);
404 
405  inputLayer->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(0));
406  inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
407 
408  outputStateIn->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(1));
409  outputStateIn->GetOutputSlot(0).SetTensorInfo(outputStateTensorInfo);
410 
411  cellStateIn->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(2));
412  cellStateIn->GetOutputSlot(0).SetTensorInfo(cellStateTensorInfo);
413 
414  lstmLayer->GetOutputSlot(0).Connect(scratchBuffer->GetInputSlot(0));
415  lstmLayer->GetOutputSlot(0).SetTensorInfo(lstmTensorInfoScratchBuff);
416 
417  lstmLayer->GetOutputSlot(1).Connect(outputStateOut->GetInputSlot(0));
418  lstmLayer->GetOutputSlot(1).SetTensorInfo(outputStateTensorInfo);
419 
420  lstmLayer->GetOutputSlot(2).Connect(cellStateOut->GetInputSlot(0));
421  lstmLayer->GetOutputSlot(2).SetTensorInfo(cellStateTensorInfo);
422 
423  lstmLayer->GetOutputSlot(3).Connect(outputLayer->GetInputSlot(0));
424  lstmLayer->GetOutputSlot(3).SetTensorInfo(outputStateTensorInfo);
425 
426  armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
427  CHECK(deserializedNetwork);
428 
429  VerifyLstmLayer<armnn::LstmDescriptor> checker(
430  layerName,
431  {inputTensorInfo, outputStateTensorInfo, cellStateTensorInfo},
432  {lstmTensorInfoScratchBuff, outputStateTensorInfo, cellStateTensorInfo, outputStateTensorInfo},
433  descriptor,
434  params);
435  deserializedNetwork->ExecuteStrategy(checker);
436 }
437 
438 TEST_CASE("SerializeDeserializeLstmNoCifgWithPeepholeWithProjectionWithLayerNorm")
439 {
440  armnn::LstmDescriptor descriptor;
441  descriptor.m_ActivationFunc = 4;
442  descriptor.m_ClippingThresProj = 0.0f;
443  descriptor.m_ClippingThresCell = 0.0f;
444  descriptor.m_CifgEnabled = false; // if this is true then we DON'T need to set the OptCifgParams
445  descriptor.m_ProjectionEnabled = true;
446  descriptor.m_PeepholeEnabled = true;
447  descriptor.m_LayerNormEnabled = true;
448 
449  const uint32_t batchSize = 2;
450  const uint32_t inputSize = 5;
451  const uint32_t numUnits = 20;
452  const uint32_t outputSize = 16;
453 
454  armnn::TensorInfo tensorInfo20x5({numUnits, inputSize}, armnn::DataType::Float32);
455  std::vector<float> inputToInputWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
456  armnn::ConstTensor inputToInputWeights(tensorInfo20x5, inputToInputWeightsData);
457 
458  std::vector<float> inputToForgetWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
459  armnn::ConstTensor inputToForgetWeights(tensorInfo20x5, inputToForgetWeightsData);
460 
461  std::vector<float> inputToCellWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
462  armnn::ConstTensor inputToCellWeights(tensorInfo20x5, inputToCellWeightsData);
463 
464  std::vector<float> inputToOutputWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
465  armnn::ConstTensor inputToOutputWeights(tensorInfo20x5, inputToOutputWeightsData);
466 
467  armnn::TensorInfo tensorInfo20({numUnits}, armnn::DataType::Float32);
468  std::vector<float> inputGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
469  armnn::ConstTensor inputGateBias(tensorInfo20, inputGateBiasData);
470 
471  std::vector<float> forgetGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
472  armnn::ConstTensor forgetGateBias(tensorInfo20, forgetGateBiasData);
473 
474  std::vector<float> cellBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
475  armnn::ConstTensor cellBias(tensorInfo20, cellBiasData);
476 
477  std::vector<float> outputGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
478  armnn::ConstTensor outputGateBias(tensorInfo20, outputGateBiasData);
479 
480  armnn::TensorInfo tensorInfo20x16({numUnits, outputSize}, armnn::DataType::Float32);
481  std::vector<float> recurrentToInputWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
482  armnn::ConstTensor recurrentToInputWeights(tensorInfo20x16, recurrentToInputWeightsData);
483 
484  std::vector<float> recurrentToForgetWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
485  armnn::ConstTensor recurrentToForgetWeights(tensorInfo20x16, recurrentToForgetWeightsData);
486 
487  std::vector<float> recurrentToCellWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
488  armnn::ConstTensor recurrentToCellWeights(tensorInfo20x16, recurrentToCellWeightsData);
489 
490  std::vector<float> recurrentToOutputWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
491  armnn::ConstTensor recurrentToOutputWeights(tensorInfo20x16, recurrentToOutputWeightsData);
492 
493  std::vector<float> cellToInputWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
494  armnn::ConstTensor cellToInputWeights(tensorInfo20, cellToInputWeightsData);
495 
496  std::vector<float> cellToForgetWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
497  armnn::ConstTensor cellToForgetWeights(tensorInfo20, cellToForgetWeightsData);
498 
499  std::vector<float> cellToOutputWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
500  armnn::ConstTensor cellToOutputWeights(tensorInfo20, cellToOutputWeightsData);
501 
502  armnn::TensorInfo tensorInfo16x20({outputSize, numUnits}, armnn::DataType::Float32);
503  std::vector<float> projectionWeightsData = GenerateRandomData<float>(tensorInfo16x20.GetNumElements());
504  armnn::ConstTensor projectionWeights(tensorInfo16x20, projectionWeightsData);
505 
506  armnn::TensorInfo tensorInfo16({outputSize}, armnn::DataType::Float32);
507  std::vector<float> projectionBiasData(outputSize, 0.f);
508  armnn::ConstTensor projectionBias(tensorInfo16, projectionBiasData);
509 
510  std::vector<float> inputLayerNormWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
511  armnn::ConstTensor inputLayerNormWeights(tensorInfo20, forgetGateBiasData);
512 
513  std::vector<float> forgetLayerNormWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
514  armnn::ConstTensor forgetLayerNormWeights(tensorInfo20, forgetGateBiasData);
515 
516  std::vector<float> cellLayerNormWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
517  armnn::ConstTensor cellLayerNormWeights(tensorInfo20, forgetGateBiasData);
518 
519  std::vector<float> outLayerNormWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
520  armnn::ConstTensor outLayerNormWeights(tensorInfo20, forgetGateBiasData);
521 
522  armnn::LstmInputParams params;
523  params.m_InputToForgetWeights = &inputToForgetWeights;
524  params.m_InputToCellWeights = &inputToCellWeights;
525  params.m_InputToOutputWeights = &inputToOutputWeights;
526  params.m_RecurrentToForgetWeights = &recurrentToForgetWeights;
527  params.m_RecurrentToCellWeights = &recurrentToCellWeights;
528  params.m_RecurrentToOutputWeights = &recurrentToOutputWeights;
529  params.m_ForgetGateBias = &forgetGateBias;
530  params.m_CellBias = &cellBias;
531  params.m_OutputGateBias = &outputGateBias;
532 
533  // additional params because: descriptor.m_CifgEnabled = false
534  params.m_InputToInputWeights = &inputToInputWeights;
535  params.m_RecurrentToInputWeights = &recurrentToInputWeights;
536  params.m_CellToInputWeights = &cellToInputWeights;
537  params.m_InputGateBias = &inputGateBias;
538 
539  // additional params because: descriptor.m_ProjectionEnabled = true
540  params.m_ProjectionWeights = &projectionWeights;
541  params.m_ProjectionBias = &projectionBias;
542 
543  // additional params because: descriptor.m_PeepholeEnabled = true
544  params.m_CellToForgetWeights = &cellToForgetWeights;
545  params.m_CellToOutputWeights = &cellToOutputWeights;
546 
547  // additional params because: despriptor.m_LayerNormEnabled = true
548  params.m_InputLayerNormWeights = &inputLayerNormWeights;
549  params.m_ForgetLayerNormWeights = &forgetLayerNormWeights;
550  params.m_CellLayerNormWeights = &cellLayerNormWeights;
551  params.m_OutputLayerNormWeights = &outLayerNormWeights;
552 
553  armnn::INetworkPtr network = armnn::INetwork::Create();
554  armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
555  armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(1);
556  armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(2);
557  const std::string layerName("lstm");
558  armnn::IConnectableLayer* const lstmLayer = network->AddLstmLayer(descriptor, params, layerName.c_str());
559  armnn::IConnectableLayer* const scratchBuffer = network->AddOutputLayer(0);
560  armnn::IConnectableLayer* const outputStateOut = network->AddOutputLayer(1);
561  armnn::IConnectableLayer* const cellStateOut = network->AddOutputLayer(2);
562  armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(3);
563 
564  // connect up
565  armnn::TensorInfo inputTensorInfo({ batchSize, inputSize }, armnn::DataType::Float32);
566  armnn::TensorInfo cellStateTensorInfo({ batchSize, numUnits}, armnn::DataType::Float32);
567  armnn::TensorInfo outputStateTensorInfo({ batchSize, outputSize }, armnn::DataType::Float32);
568  armnn::TensorInfo lstmTensorInfoScratchBuff({ batchSize, numUnits * 4 }, armnn::DataType::Float32);
569 
570  inputLayer->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(0));
571  inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
572 
573  outputStateIn->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(1));
574  outputStateIn->GetOutputSlot(0).SetTensorInfo(outputStateTensorInfo);
575 
576  cellStateIn->GetOutputSlot(0).Connect(lstmLayer->GetInputSlot(2));
577  cellStateIn->GetOutputSlot(0).SetTensorInfo(cellStateTensorInfo);
578 
579  lstmLayer->GetOutputSlot(0).Connect(scratchBuffer->GetInputSlot(0));
580  lstmLayer->GetOutputSlot(0).SetTensorInfo(lstmTensorInfoScratchBuff);
581 
582  lstmLayer->GetOutputSlot(1).Connect(outputStateOut->GetInputSlot(0));
583  lstmLayer->GetOutputSlot(1).SetTensorInfo(outputStateTensorInfo);
584 
585  lstmLayer->GetOutputSlot(2).Connect(cellStateOut->GetInputSlot(0));
586  lstmLayer->GetOutputSlot(2).SetTensorInfo(cellStateTensorInfo);
587 
588  lstmLayer->GetOutputSlot(3).Connect(outputLayer->GetInputSlot(0));
589  lstmLayer->GetOutputSlot(3).SetTensorInfo(outputStateTensorInfo);
590 
591  armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
592  CHECK(deserializedNetwork);
593 
594  VerifyLstmLayer<armnn::LstmDescriptor> checker(
595  layerName,
596  {inputTensorInfo, outputStateTensorInfo, cellStateTensorInfo},
597  {lstmTensorInfoScratchBuff, outputStateTensorInfo, cellStateTensorInfo, outputStateTensorInfo},
598  descriptor,
599  params);
600  deserializedNetwork->ExecuteStrategy(checker);
601 }
602 
603 TEST_CASE("EnsureLstmLayersBackwardCompatibility")
604 {
605  // The hex data below is a flat buffer containing a lstm layer with no Cifg, with peephole and projection
606  // enabled. That data was obtained before additional layer normalization parameters where added to the
607  // lstm serializer. That way it can be tested if a lstm model with the old parameter configuration can
608  // still be loaded
609  const std::vector<uint8_t> lstmNoCifgWithPeepholeAndProjectionModel =
610  {
611  0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x0A, 0x00,
612  0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x2C, 0x00, 0x00, 0x00, 0x38, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00,
613  0xDC, 0x29, 0x00, 0x00, 0x38, 0x29, 0x00, 0x00, 0xB4, 0x28, 0x00, 0x00, 0x94, 0x01, 0x00, 0x00, 0x3C, 0x01,
614  0x00, 0x00, 0xE0, 0x00, 0x00, 0x00, 0x84, 0x00, 0x00, 0x00, 0x28, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00,
615  0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x04, 0x00,
616  0x00, 0x00, 0x05, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x70, 0xD6, 0xFF, 0xFF,
617  0x00, 0x00, 0x00, 0x0B, 0x04, 0x00, 0x00, 0x00, 0x06, 0xD7, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x88, 0xD7,
618  0xFF, 0xFF, 0x08, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0xF6, 0xD6, 0xFF, 0xFF, 0x07, 0x00, 0x00, 0x00,
619  0x10, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00,
620  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
621  0xE8, 0xD7, 0xFF, 0xFF, 0x03, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0xC8, 0xD6, 0xFF, 0xFF, 0x00, 0x00,
622  0x00, 0x0B, 0x04, 0x00, 0x00, 0x00, 0x5E, 0xD7, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0xE0, 0xD7, 0xFF, 0xFF,
623  0x08, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x4E, 0xD7, 0xFF, 0xFF, 0x06, 0x00, 0x00, 0x00, 0x10, 0x00,
624  0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
625  0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x40, 0xD8,
626  0xFF, 0xFF, 0x03, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x20, 0xD7, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x0B,
627  0x04, 0x00, 0x00, 0x00, 0xB6, 0xD7, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x38, 0xD8, 0xFF, 0xFF, 0x08, 0x00,
628  0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0xA6, 0xD7, 0xFF, 0xFF, 0x05, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00,
629  0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
630  0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x98, 0xD8, 0xFF, 0xFF,
631  0x03, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x78, 0xD7, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x0B, 0x04, 0x00,
632  0x00, 0x00, 0x0E, 0xD8, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x16, 0xD8, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00,
633  0xFA, 0xD7, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x10, 0x00,
634  0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
635  0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xEC, 0xD8, 0xFF, 0xFF, 0x03, 0x00, 0x00, 0x00, 0x00, 0x00,
636  0x00, 0x00, 0x6C, 0xD8, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x23, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00,
637  0x12, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x0A, 0x00, 0x00, 0x00, 0xE0, 0x25, 0x00, 0x00, 0xD0, 0x25,
638  0x00, 0x00, 0x2C, 0x00, 0x00, 0x00, 0x00, 0x00, 0x26, 0x00, 0x48, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00,
639  0x10, 0x00, 0x14, 0x00, 0x18, 0x00, 0x1C, 0x00, 0x20, 0x00, 0x24, 0x00, 0x28, 0x00, 0x2C, 0x00, 0x30, 0x00,
640  0x34, 0x00, 0x38, 0x00, 0x3C, 0x00, 0x40, 0x00, 0x44, 0x00, 0x26, 0x00, 0x00, 0x00, 0xC4, 0x23, 0x00, 0x00,
641  0xF8, 0x21, 0x00, 0x00, 0x2C, 0x20, 0x00, 0x00, 0xF0, 0x1A, 0x00, 0x00, 0xB4, 0x15, 0x00, 0x00, 0x78, 0x10,
642  0x00, 0x00, 0xF0, 0x0F, 0x00, 0x00, 0x68, 0x0F, 0x00, 0x00, 0xE0, 0x0E, 0x00, 0x00, 0x14, 0x0D, 0x00, 0x00,
643  0xD8, 0x07, 0x00, 0x00, 0x50, 0x07, 0x00, 0x00, 0xC8, 0x06, 0x00, 0x00, 0x8C, 0x01, 0x00, 0x00, 0x14, 0x01,
644  0x00, 0x00, 0x8C, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xEE, 0xD7, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x03,
645  0x64, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xFE, 0xD8, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x14, 0x00,
646  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
647  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
648  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
649  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
650  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x5A, 0xD8, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01,
651  0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x72, 0xD8,
652  0xFF, 0xFF, 0x00, 0x00, 0x00, 0x03, 0x64, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x82, 0xD9, 0xFF, 0xFF,
653  0x04, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
654  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
655  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
656  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
657  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xDE, 0xD8,
658  0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
659  0x14, 0x00, 0x00, 0x00, 0xF6, 0xD8, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x03, 0x54, 0x00, 0x00, 0x00, 0x04, 0x00,
660  0x00, 0x00, 0x06, 0xDA, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
661  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
662  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
663  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
664  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x52, 0xD9, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00,
665  0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x6A, 0xD9, 0xFF, 0xFF, 0x00, 0x00,
666  0x00, 0x03, 0x14, 0x05, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x7A, 0xDA, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00,
667  0x40, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
668  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
669  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
670  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
671  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
672  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
673  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
674  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
675  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
676  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
677  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
678  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
679  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
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997  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
998  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
999  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1000  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1001  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1002  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1003  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1004  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1005  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1006  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1007  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1008  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1009  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1010  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1011  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1012  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1013  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1014  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1015  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1016  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1017  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1018  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1019  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1020  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1021  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1022  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1023  0x8A, 0xF2, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00,
1024  0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0xA6, 0xF2, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x03,
1025  0x14, 0x05, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xB6, 0xF3, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x40, 0x01,
1026  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1027  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1028  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1029  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1030  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1031  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1032  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1033  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1034  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1035  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1036  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1037  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1038  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1039  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1040  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1041  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1042  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1043  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1044  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1045  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1046  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1047  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1048  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1049  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1050  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1051  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1052  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1053  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1054  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1055  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1056  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1057  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1058  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1059  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1060  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1061  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1062  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1063  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1064  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1065  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1066  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1067  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1068  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1069  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1070  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1071  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1072  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1073  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1074  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1075  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1076  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1077  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1078  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1079  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1080  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1081  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1082  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1083  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1084  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1085  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1086  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1087  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1088  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1089  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1090  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1091  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1092  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1093  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1094  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1095  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1096  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1097  0x00, 0x00, 0x00, 0x00, 0xC2, 0xF7, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00,
1098  0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0xDE, 0xF7, 0xFF, 0xFF,
1099  0x00, 0x00, 0x00, 0x03, 0xA4, 0x01, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xEE, 0xF8, 0xFF, 0xFF, 0x04, 0x00,
1100  0x00, 0x00, 0x64, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1101  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1102  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1103  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1104  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1105  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1106  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1107  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1108  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1109  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1110  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1111  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1112  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1113  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1114  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1115  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1116  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1117  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1118  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1119  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1120  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1121  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1122  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x8A, 0xF9, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01,
1123  0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x05, 0x00,
1124  0x00, 0x00, 0xA6, 0xF9, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x03, 0xA4, 0x01, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
1125  0xB6, 0xFA, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x64, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1126  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1127  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1128  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1129  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1130  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1131  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1132  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1133  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1134  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1135  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1136  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1137  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1138  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1139  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1140  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1141  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1142  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1143  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1144  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1145  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1146  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1147  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x52, 0xFB,
1148  0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
1149  0x14, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, 0x6E, 0xFB, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x03, 0xA4, 0x01,
1150  0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x7E, 0xFC, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x64, 0x00, 0x00, 0x00,
1151  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1152  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1153  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1154  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1155  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1156  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1157  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1158  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1159  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1160  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1161  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1162  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1163  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1164  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1165  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1166  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1167  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1168  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1169  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1170  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1171  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1172  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1173  0x00, 0x00, 0x00, 0x00, 0x1A, 0xFD, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00,
1174  0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, 0x10, 0x00, 0x0C, 0x00,
1175  0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x05, 0x00, 0x06, 0x00, 0x07, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00,
1176  0x01, 0x01, 0x04, 0x00, 0x00, 0x00, 0x2E, 0xFE, 0xFF, 0xFF, 0x03, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00,
1177  0x22, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6C, 0x73,
1178  0x74, 0x6D, 0x00, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0xEC, 0x00, 0x00, 0x00, 0xD0, 0x00, 0x00, 0x00,
1179  0xB4, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x88, 0x00, 0x00, 0x00, 0x5C, 0x00, 0x00, 0x00, 0x30, 0x00,
1180  0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x14, 0xFF, 0xFF, 0xFF, 0x03, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
1181  0xA6, 0xFD, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00,
1182  0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x3C, 0xFF, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00,
1183  0x04, 0x00, 0x00, 0x00, 0xCE, 0xFD, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00,
1184  0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x64, 0xFF, 0xFF, 0xFF,
1185  0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xF6, 0xFD, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00,
1186  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00,
1187  0xB4, 0xFE, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0x1A, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00,
1188  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x50, 0x00, 0x00, 0x00,
1189  0xF0, 0xFF, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x00,
1190  0x10, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
1191  0x00, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00,
1192  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xE8, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x09, 0x04, 0x00, 0x00, 0x00,
1193  0x7E, 0xFF, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00,
1194  0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x76, 0xFF, 0xFF, 0xFF, 0x02, 0x00, 0x00, 0x00,
1195  0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00,
1196  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
1197  0x68, 0xFF, 0xFF, 0xFF, 0x04, 0x00, 0x00, 0x00, 0xCE, 0xFE, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00,
1198  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00,
1199  0x08, 0x00, 0x0E, 0x00, 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09, 0x0C, 0x00,
1200  0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x08, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00,
1201  0x08, 0x00, 0x0E, 0x00, 0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x01, 0x00,
1202  0x00, 0x00, 0x00, 0x00, 0x0E, 0x00, 0x18, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0C, 0x00, 0x10, 0x00, 0x14, 0x00,
1203  0x0E, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00,
1204  0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1205  0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00,
1206  0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x6E, 0xFF, 0xFF, 0xFF, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00,
1207  0x00, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x08, 0x00,
1208  0x0C, 0x00, 0x07, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09, 0x04, 0x00, 0x00, 0x00,
1209  0xF6, 0xFF, 0xFF, 0xFF, 0x0C, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x0A, 0x00, 0x04, 0x00, 0x06, 0x00,
1210  0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0E, 0x00, 0x14, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00,
1211  0x0C, 0x00, 0x10, 0x00, 0x0E, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x00,
1212  0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1213  0x01, 0x00, 0x00, 0x00, 0x0C, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0A, 0x00, 0x00, 0x00, 0x04, 0x00, 0x08, 0x00,
1214  0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0A, 0x00, 0x10, 0x00, 0x08, 0x00, 0x07, 0x00, 0x0C, 0x00,
1215  0x0A, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x02, 0x00,
1216  0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, 0x00
1217  };
1218 
1219  armnn::INetworkPtr deserializedNetwork =
1220  DeserializeNetwork(std::string(lstmNoCifgWithPeepholeAndProjectionModel.begin(),
1221  lstmNoCifgWithPeepholeAndProjectionModel.end()));
1222 
1223  CHECK(deserializedNetwork);
1224 
1225  // generating the same model parameters which where used to serialize the model (Layer norm is not specified)
1226  armnn::LstmDescriptor descriptor;
1227  descriptor.m_ActivationFunc = 4;
1228  descriptor.m_ClippingThresProj = 0.0f;
1229  descriptor.m_ClippingThresCell = 0.0f;
1230  descriptor.m_CifgEnabled = false;
1231  descriptor.m_ProjectionEnabled = true;
1232  descriptor.m_PeepholeEnabled = true;
1233 
1234  const uint32_t batchSize = 2u;
1235  const uint32_t inputSize = 5u;
1236  const uint32_t numUnits = 20u;
1237  const uint32_t outputSize = 16u;
1238 
1239  armnn::TensorInfo tensorInfo20x5({numUnits, inputSize}, armnn::DataType::Float32);
1240  std::vector<float> inputToInputWeightsData(tensorInfo20x5.GetNumElements(), 0.0f);
1241  armnn::ConstTensor inputToInputWeights(tensorInfo20x5, inputToInputWeightsData);
1242 
1243  std::vector<float> inputToForgetWeightsData(tensorInfo20x5.GetNumElements(), 0.0f);
1244  armnn::ConstTensor inputToForgetWeights(tensorInfo20x5, inputToForgetWeightsData);
1245 
1246  std::vector<float> inputToCellWeightsData(tensorInfo20x5.GetNumElements(), 0.0f);
1247  armnn::ConstTensor inputToCellWeights(tensorInfo20x5, inputToCellWeightsData);
1248 
1249  std::vector<float> inputToOutputWeightsData(tensorInfo20x5.GetNumElements(), 0.0f);
1250  armnn::ConstTensor inputToOutputWeights(tensorInfo20x5, inputToOutputWeightsData);
1251 
1252  armnn::TensorInfo tensorInfo20({numUnits}, armnn::DataType::Float32);
1253  std::vector<float> inputGateBiasData(tensorInfo20.GetNumElements(), 0.0f);
1254  armnn::ConstTensor inputGateBias(tensorInfo20, inputGateBiasData);
1255 
1256  std::vector<float> forgetGateBiasData(tensorInfo20.GetNumElements(), 0.0f);
1257  armnn::ConstTensor forgetGateBias(tensorInfo20, forgetGateBiasData);
1258 
1259  std::vector<float> cellBiasData(tensorInfo20.GetNumElements(), 0.0f);
1260  armnn::ConstTensor cellBias(tensorInfo20, cellBiasData);
1261 
1262  std::vector<float> outputGateBiasData(tensorInfo20.GetNumElements(), 0.0f);
1263  armnn::ConstTensor outputGateBias(tensorInfo20, outputGateBiasData);
1264 
1265  armnn::TensorInfo tensorInfo20x16({numUnits, outputSize}, armnn::DataType::Float32);
1266  std::vector<float> recurrentToInputWeightsData(tensorInfo20x16.GetNumElements(), 0.0f);
1267  armnn::ConstTensor recurrentToInputWeights(tensorInfo20x16, recurrentToInputWeightsData);
1268 
1269  std::vector<float> recurrentToForgetWeightsData(tensorInfo20x16.GetNumElements(), 0.0f);
1270  armnn::ConstTensor recurrentToForgetWeights(tensorInfo20x16, recurrentToForgetWeightsData);
1271 
1272  std::vector<float> recurrentToCellWeightsData(tensorInfo20x16.GetNumElements(), 0.0f);
1273  armnn::ConstTensor recurrentToCellWeights(tensorInfo20x16, recurrentToCellWeightsData);
1274 
1275  std::vector<float> recurrentToOutputWeightsData(tensorInfo20x16.GetNumElements(), 0.0f);
1276  armnn::ConstTensor recurrentToOutputWeights(tensorInfo20x16, recurrentToOutputWeightsData);
1277 
1278  std::vector<float> cellToInputWeightsData(tensorInfo20.GetNumElements(), 0.0f);
1279  armnn::ConstTensor cellToInputWeights(tensorInfo20, cellToInputWeightsData);
1280 
1281  std::vector<float> cellToForgetWeightsData(tensorInfo20.GetNumElements(), 0.0f);
1282  armnn::ConstTensor cellToForgetWeights(tensorInfo20, cellToForgetWeightsData);
1283 
1284  std::vector<float> cellToOutputWeightsData(tensorInfo20.GetNumElements(), 0.0f);
1285  armnn::ConstTensor cellToOutputWeights(tensorInfo20, cellToOutputWeightsData);
1286 
1287  armnn::TensorInfo tensorInfo16x20({outputSize, numUnits}, armnn::DataType::Float32);
1288  std::vector<float> projectionWeightsData(tensorInfo16x20.GetNumElements(), 0.0f);
1289  armnn::ConstTensor projectionWeights(tensorInfo16x20, projectionWeightsData);
1290 
1291  armnn::TensorInfo tensorInfo16({outputSize}, armnn::DataType::Float32);
1292  std::vector<float> projectionBiasData(outputSize, 0.0f);
1293  armnn::ConstTensor projectionBias(tensorInfo16, projectionBiasData);
1294 
1295  armnn::LstmInputParams params;
1296  params.m_InputToForgetWeights = &inputToForgetWeights;
1297  params.m_InputToCellWeights = &inputToCellWeights;
1298  params.m_InputToOutputWeights = &inputToOutputWeights;
1299  params.m_RecurrentToForgetWeights = &recurrentToForgetWeights;
1300  params.m_RecurrentToCellWeights = &recurrentToCellWeights;
1301  params.m_RecurrentToOutputWeights = &recurrentToOutputWeights;
1302  params.m_ForgetGateBias = &forgetGateBias;
1303  params.m_CellBias = &cellBias;
1304  params.m_OutputGateBias = &outputGateBias;
1305 
1306  // additional params because: descriptor.m_CifgEnabled = false
1307  params.m_InputToInputWeights = &inputToInputWeights;
1308  params.m_RecurrentToInputWeights = &recurrentToInputWeights;
1309  params.m_CellToInputWeights = &cellToInputWeights;
1310  params.m_InputGateBias = &inputGateBias;
1311 
1312  // additional params because: descriptor.m_ProjectionEnabled = true
1313  params.m_ProjectionWeights = &projectionWeights;
1314  params.m_ProjectionBias = &projectionBias;
1315 
1316  // additional params because: descriptor.m_PeepholeEnabled = true
1317  params.m_CellToForgetWeights = &cellToForgetWeights;
1318  params.m_CellToOutputWeights = &cellToOutputWeights;
1319 
1320  const std::string layerName("lstm");
1321  armnn::TensorInfo inputTensorInfo({ batchSize, inputSize }, armnn::DataType::Float32);
1322  armnn::TensorInfo cellStateTensorInfo({ batchSize, numUnits}, armnn::DataType::Float32);
1323  armnn::TensorInfo outputStateTensorInfo({ batchSize, outputSize }, armnn::DataType::Float32);
1324  armnn::TensorInfo lstmTensorInfoScratchBuff({ batchSize, numUnits * 4 }, armnn::DataType::Float32);
1325 
1326  VerifyLstmLayer<armnn::LstmDescriptor> checker(
1327  layerName,
1328  {inputTensorInfo, outputStateTensorInfo, cellStateTensorInfo},
1329  {lstmTensorInfoScratchBuff, outputStateTensorInfo, cellStateTensorInfo, outputStateTensorInfo},
1330  descriptor,
1331  params);
1332  deserializedNetwork->ExecuteStrategy(checker);
1333 }
1334 
1335 armnn::QuantizedLstmInputParams ConstantsVector2QuantizedLstmInputParams(
1336  const std::vector<armnn::ConstTensor>& constants)
1337 {
1338  armnn::QuantizedLstmInputParams params;
1339 
1340  // index for constants vector
1341  size_t i = 0;
1342 
1343  // Get input parameters
1344  params.m_InputToInputWeights = &constants[i++];
1345  params.m_InputToForgetWeights = &constants[i++];
1346  params.m_InputToCellWeights = &constants[i++];
1347  params.m_InputToOutputWeights = &constants[i++];
1348 
1349  params.m_RecurrentToInputWeights = &constants[i++];
1350  params.m_RecurrentToForgetWeights = &constants[i++];
1351  params.m_RecurrentToCellWeights = &constants[i++];
1352  params.m_RecurrentToOutputWeights = &constants[i++];
1353 
1354  params.m_InputGateBias = &constants[i++];
1355  params.m_ForgetGateBias = &constants[i++];
1356  params.m_CellBias = &constants[i++];
1357  params.m_OutputGateBias = &constants[i++];
1358 
1359  return params;
1360 }
1361 
1362 class VerifyQuantizedLstmLayer : public LayerVerifierBase
1363 {
1364 
1365 public:
1366  VerifyQuantizedLstmLayer(const std::string& layerName,
1367  const std::vector<armnn::TensorInfo>& inputInfos,
1368  const std::vector<armnn::TensorInfo>& outputInfos,
1369  const armnn::QuantizedLstmInputParams& inputParams)
1370  : LayerVerifierBase(layerName, inputInfos, outputInfos), m_InputParams(inputParams) {}
1371 
1372  void ExecuteStrategy(const armnn::IConnectableLayer* layer,
1373  const armnn::BaseDescriptor& descriptor,
1374  const std::vector<armnn::ConstTensor>& constants,
1375  const char* name,
1376  const armnn::LayerBindingId id = 0) override
1377  {
1378  armnn::IgnoreUnused(descriptor, constants, id);
1379  switch (layer->GetType())
1380  {
1381  case armnn::LayerType::Input: break;
1382  case armnn::LayerType::Output: break;
1383  case armnn::LayerType::QuantizedLstm:
1384  {
1385  VerifyNameAndConnections(layer, name);
1386  armnn::QuantizedLstmInputParams params = ConstantsVector2QuantizedLstmInputParams(constants);
1387  VerifyInputParameters(params);
1388  break;
1389  }
1390  default:
1391  {
1392  throw armnn::Exception(fmt::format("Unexpected layer type in QuantizedLstm test model:",
1393  layer->GetName()));
1394  }
1395  }
1396  }
1397 
1398 protected:
1399  void VerifyInputParameters(const armnn::QuantizedLstmInputParams& params)
1400  {
1401  VerifyConstTensors("m_InputToInputWeights",
1402  m_InputParams.m_InputToInputWeights, params.m_InputToInputWeights);
1403  VerifyConstTensors("m_InputToForgetWeights",
1404  m_InputParams.m_InputToForgetWeights, params.m_InputToForgetWeights);
1405  VerifyConstTensors("m_InputToCellWeights",
1406  m_InputParams.m_InputToCellWeights, params.m_InputToCellWeights);
1407  VerifyConstTensors("m_InputToOutputWeights",
1408  m_InputParams.m_InputToOutputWeights, params.m_InputToOutputWeights);
1409  VerifyConstTensors("m_RecurrentToInputWeights",
1410  m_InputParams.m_RecurrentToInputWeights, params.m_RecurrentToInputWeights);
1411  VerifyConstTensors("m_RecurrentToForgetWeights",
1412  m_InputParams.m_RecurrentToForgetWeights, params.m_RecurrentToForgetWeights);
1413  VerifyConstTensors("m_RecurrentToCellWeights",
1414  m_InputParams.m_RecurrentToCellWeights, params.m_RecurrentToCellWeights);
1415  VerifyConstTensors("m_RecurrentToOutputWeights",
1416  m_InputParams.m_RecurrentToOutputWeights, params.m_RecurrentToOutputWeights);
1417  VerifyConstTensors("m_InputGateBias",
1418  m_InputParams.m_InputGateBias, params.m_InputGateBias);
1419  VerifyConstTensors("m_ForgetGateBias",
1420  m_InputParams.m_ForgetGateBias, params.m_ForgetGateBias);
1421  VerifyConstTensors("m_CellBias",
1422  m_InputParams.m_CellBias, params.m_CellBias);
1423  VerifyConstTensors("m_OutputGateBias",
1424  m_InputParams.m_OutputGateBias, params.m_OutputGateBias);
1425  }
1426 
1427 private:
1428  armnn::QuantizedLstmInputParams m_InputParams;
1429 };
1430 
1431 TEST_CASE("SerializeDeserializeQuantizedLstm")
1432 {
1433  const uint32_t batchSize = 1;
1434  const uint32_t inputSize = 2;
1435  const uint32_t numUnits = 4;
1436  const uint32_t outputSize = numUnits;
1437 
1438  // Scale/Offset for input/output, cellState In/Out, weights, bias
1439  float inputOutputScale = 0.0078125f;
1440  int32_t inputOutputOffset = 128;
1441 
1442  float cellStateScale = 0.00048828125f;
1443  int32_t cellStateOffset = 0;
1444 
1445  float weightsScale = 0.00408021f;
1446  int32_t weightsOffset = 100;
1447 
1448  float biasScale = 3.1876640625e-05f;
1449  int32_t biasOffset = 0;
1450 
1451  // The shape of weight data is {outputSize, inputSize} = {4, 2}
1452  armnn::TensorShape inputToInputWeightsShape = {4, 2};
1453  std::vector<uint8_t> inputToInputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8};
1454  armnn::TensorInfo inputToInputWeightsInfo(inputToInputWeightsShape,
1455  armnn::DataType::QAsymmU8,
1456  weightsScale,
1457  weightsOffset);
1458  armnn::ConstTensor inputToInputWeights(inputToInputWeightsInfo, inputToInputWeightsData);
1459 
1460  armnn::TensorShape inputToForgetWeightsShape = {4, 2};
1461  std::vector<uint8_t> inputToForgetWeightsData = {1, 2, 3, 4, 5, 6, 7, 8};
1462  armnn::TensorInfo inputToForgetWeightsInfo(inputToForgetWeightsShape,
1463  armnn::DataType::QAsymmU8,
1464  weightsScale,
1465  weightsOffset);
1466  armnn::ConstTensor inputToForgetWeights(inputToForgetWeightsInfo, inputToForgetWeightsData);
1467 
1468  armnn::TensorShape inputToCellWeightsShape = {4, 2};
1469  std::vector<uint8_t> inputToCellWeightsData = {1, 2, 3, 4, 5, 6, 7, 8};
1470  armnn::TensorInfo inputToCellWeightsInfo(inputToCellWeightsShape,
1471  armnn::DataType::QAsymmU8,
1472  weightsScale,
1473  weightsOffset);
1474  armnn::ConstTensor inputToCellWeights(inputToCellWeightsInfo, inputToCellWeightsData);
1475 
1476  armnn::TensorShape inputToOutputWeightsShape = {4, 2};
1477  std::vector<uint8_t> inputToOutputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8};
1478  armnn::TensorInfo inputToOutputWeightsInfo(inputToOutputWeightsShape,
1479  armnn::DataType::QAsymmU8,
1480  weightsScale,
1481  weightsOffset);
1482  armnn::ConstTensor inputToOutputWeights(inputToOutputWeightsInfo, inputToOutputWeightsData);
1483 
1484  // The shape of recurrent weight data is {outputSize, outputSize} = {4, 4}
1485  armnn::TensorShape recurrentToInputWeightsShape = {4, 4};
1486  std::vector<uint8_t> recurrentToInputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16};
1487  armnn::TensorInfo recurrentToInputWeightsInfo(recurrentToInputWeightsShape,
1488  armnn::DataType::QAsymmU8,
1489  weightsScale,
1490  weightsOffset);
1491  armnn::ConstTensor recurrentToInputWeights(recurrentToInputWeightsInfo, recurrentToInputWeightsData);
1492 
1493  armnn::TensorShape recurrentToForgetWeightsShape = {4, 4};
1494  std::vector<uint8_t> recurrentToForgetWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16};
1495  armnn::TensorInfo recurrentToForgetWeightsInfo(recurrentToForgetWeightsShape,
1496  armnn::DataType::QAsymmU8,
1497  weightsScale,
1498  weightsOffset);
1499  armnn::ConstTensor recurrentToForgetWeights(recurrentToForgetWeightsInfo, recurrentToForgetWeightsData);
1500 
1501  armnn::TensorShape recurrentToCellWeightsShape = {4, 4};
1502  std::vector<uint8_t> recurrentToCellWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16};
1503  armnn::TensorInfo recurrentToCellWeightsInfo(recurrentToCellWeightsShape,
1504  armnn::DataType::QAsymmU8,
1505  weightsScale,
1506  weightsOffset);
1507  armnn::ConstTensor recurrentToCellWeights(recurrentToCellWeightsInfo, recurrentToCellWeightsData);
1508 
1509  armnn::TensorShape recurrentToOutputWeightsShape = {4, 4};
1510  std::vector<uint8_t> recurrentToOutputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16};
1511  armnn::TensorInfo recurrentToOutputWeightsInfo(recurrentToOutputWeightsShape,
1512  armnn::DataType::QAsymmU8,
1513  weightsScale,
1514  weightsOffset);
1515  armnn::ConstTensor recurrentToOutputWeights(recurrentToOutputWeightsInfo, recurrentToOutputWeightsData);
1516 
1517  // The shape of bias data is {outputSize} = {4}
1518  armnn::TensorShape inputGateBiasShape = {4};
1519  std::vector<int32_t> inputGateBiasData = {1, 2, 3, 4};
1520  armnn::TensorInfo inputGateBiasInfo(inputGateBiasShape,
1521  armnn::DataType::Signed32,
1522  biasScale,
1523  biasOffset);
1524  armnn::ConstTensor inputGateBias(inputGateBiasInfo, inputGateBiasData);
1525 
1526  armnn::TensorShape forgetGateBiasShape = {4};
1527  std::vector<int32_t> forgetGateBiasData = {1, 2, 3, 4};
1528  armnn::TensorInfo forgetGateBiasInfo(forgetGateBiasShape,
1529  armnn::DataType::Signed32,
1530  biasScale,
1531  biasOffset);
1532  armnn::ConstTensor forgetGateBias(forgetGateBiasInfo, forgetGateBiasData);
1533 
1534  armnn::TensorShape cellBiasShape = {4};
1535  std::vector<int32_t> cellBiasData = {1, 2, 3, 4};
1536  armnn::TensorInfo cellBiasInfo(cellBiasShape,
1537  armnn::DataType::Signed32,
1538  biasScale,
1539  biasOffset);
1540  armnn::ConstTensor cellBias(cellBiasInfo, cellBiasData);
1541 
1542  armnn::TensorShape outputGateBiasShape = {4};
1543  std::vector<int32_t> outputGateBiasData = {1, 2, 3, 4};
1544  armnn::TensorInfo outputGateBiasInfo(outputGateBiasShape,
1545  armnn::DataType::Signed32,
1546  biasScale,
1547  biasOffset);
1548  armnn::ConstTensor outputGateBias(outputGateBiasInfo, outputGateBiasData);
1549 
1550  armnn::QuantizedLstmInputParams params;
1551  params.m_InputToInputWeights = &inputToInputWeights;
1552  params.m_InputToForgetWeights = &inputToForgetWeights;
1553  params.m_InputToCellWeights = &inputToCellWeights;
1554  params.m_InputToOutputWeights = &inputToOutputWeights;
1555  params.m_RecurrentToInputWeights = &recurrentToInputWeights;
1556  params.m_RecurrentToForgetWeights = &recurrentToForgetWeights;
1557  params.m_RecurrentToCellWeights = &recurrentToCellWeights;
1558  params.m_RecurrentToOutputWeights = &recurrentToOutputWeights;
1559  params.m_InputGateBias = &inputGateBias;
1560  params.m_ForgetGateBias = &forgetGateBias;
1561  params.m_CellBias = &cellBias;
1562  params.m_OutputGateBias = &outputGateBias;
1563 
1564  armnn::INetworkPtr network = armnn::INetwork::Create();
1565  armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
1566  armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(1);
1567  armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(2);
1568  const std::string layerName("QuantizedLstm");
1569  armnn::IConnectableLayer* const quantizedLstmLayer = network->AddQuantizedLstmLayer(params, layerName.c_str());
1570  armnn::IConnectableLayer* const cellStateOut = network->AddOutputLayer(0);
1571  armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(1);
1572 
1573  // Connect up
1574  armnn::TensorInfo inputTensorInfo({ batchSize, inputSize },
1575  armnn::DataType::QAsymmU8,
1576  inputOutputScale,
1577  inputOutputOffset);
1578  armnn::TensorInfo cellStateTensorInfo({ batchSize, numUnits },
1579  armnn::DataType::QSymmS16,
1580  cellStateScale,
1581  cellStateOffset);
1582  armnn::TensorInfo outputStateTensorInfo({ batchSize, outputSize },
1583  armnn::DataType::QAsymmU8,
1584  inputOutputScale,
1585  inputOutputOffset);
1586 
1587  inputLayer->GetOutputSlot(0).Connect(quantizedLstmLayer->GetInputSlot(0));
1588  inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
1589 
1590  cellStateIn->GetOutputSlot(0).Connect(quantizedLstmLayer->GetInputSlot(1));
1591  cellStateIn->GetOutputSlot(0).SetTensorInfo(cellStateTensorInfo);
1592 
1593  outputStateIn->GetOutputSlot(0).Connect(quantizedLstmLayer->GetInputSlot(2));
1594  outputStateIn->GetOutputSlot(0).SetTensorInfo(outputStateTensorInfo);
1595 
1596  quantizedLstmLayer->GetOutputSlot(0).Connect(cellStateOut->GetInputSlot(0));
1597  quantizedLstmLayer->GetOutputSlot(0).SetTensorInfo(cellStateTensorInfo);
1598 
1599  quantizedLstmLayer->GetOutputSlot(1).Connect(outputLayer->GetInputSlot(0));
1600  quantizedLstmLayer->GetOutputSlot(1).SetTensorInfo(outputStateTensorInfo);
1601 
1602  armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
1603  CHECK(deserializedNetwork);
1604 
1605  VerifyQuantizedLstmLayer checker(layerName,
1606  {inputTensorInfo, cellStateTensorInfo, outputStateTensorInfo},
1607  {cellStateTensorInfo, outputStateTensorInfo},
1608  params);
1609 
1610  deserializedNetwork->ExecuteStrategy(checker);
1611 }
1612 
1613 TEST_CASE("SerializeDeserializeQLstmBasic")
1614 {
1615  armnn::QLstmDescriptor descriptor;
1616 
1617  descriptor.m_CifgEnabled = true;
1618  descriptor.m_ProjectionEnabled = false;
1619  descriptor.m_PeepholeEnabled = false;
1620  descriptor.m_LayerNormEnabled = false;
1621 
1622  descriptor.m_CellClip = 0.0f;
1623  descriptor.m_ProjectionClip = 0.0f;
1624 
1625  descriptor.m_InputIntermediateScale = 0.00001f;
1626  descriptor.m_ForgetIntermediateScale = 0.00001f;
1627  descriptor.m_CellIntermediateScale = 0.00001f;
1628  descriptor.m_OutputIntermediateScale = 0.00001f;
1629 
1630  descriptor.m_HiddenStateScale = 0.07f;
1631  descriptor.m_HiddenStateZeroPoint = 0;
1632 
1633  const unsigned int numBatches = 2;
1634  const unsigned int inputSize = 5;
1635  const unsigned int outputSize = 4;
1636  const unsigned int numUnits = 4;
1637 
1638  // Scale/Offset quantization info
1639  float inputScale = 0.0078f;
1640  int32_t inputOffset = 0;
1641 
1642  float outputScale = 0.0078f;
1643  int32_t outputOffset = 0;
1644 
1645  float cellStateScale = 3.5002e-05f;
1646  int32_t cellStateOffset = 0;
1647 
1648  float weightsScale = 0.007f;
1649  int32_t weightsOffset = 0;
1650 
1651  float biasScale = 3.5002e-05f / 1024;
1652  int32_t biasOffset = 0;
1653 
1654  // Weights and bias tensor and quantization info
1655  armnn::TensorInfo inputWeightsInfo({numUnits, inputSize},
1656  armnn::DataType::QSymmS8,
1657  weightsScale,
1658  weightsOffset);
1659 
1660  armnn::TensorInfo recurrentWeightsInfo({numUnits, outputSize},
1661  armnn::DataType::QSymmS8,
1662  weightsScale,
1663  weightsOffset);
1664 
1665  armnn::TensorInfo biasInfo({numUnits}, armnn::DataType::Signed32, biasScale, biasOffset);
1666 
1667  std::vector<int8_t> inputToForgetWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements());
1668  std::vector<int8_t> inputToCellWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements());
1669  std::vector<int8_t> inputToOutputWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements());
1670 
1671  armnn::ConstTensor inputToForgetWeights(inputWeightsInfo, inputToForgetWeightsData);
1672  armnn::ConstTensor inputToCellWeights(inputWeightsInfo, inputToCellWeightsData);
1673  armnn::ConstTensor inputToOutputWeights(inputWeightsInfo, inputToOutputWeightsData);
1674 
1675  std::vector<int8_t> recurrentToForgetWeightsData =
1676  GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements());
1677  std::vector<int8_t> recurrentToCellWeightsData =
1678  GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements());
1679  std::vector<int8_t> recurrentToOutputWeightsData =
1680  GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements());
1681 
1682  armnn::ConstTensor recurrentToForgetWeights(recurrentWeightsInfo, recurrentToForgetWeightsData);
1683  armnn::ConstTensor recurrentToCellWeights(recurrentWeightsInfo, recurrentToCellWeightsData);
1684  armnn::ConstTensor recurrentToOutputWeights(recurrentWeightsInfo, recurrentToOutputWeightsData);
1685 
1686  std::vector<int32_t> forgetGateBiasData(numUnits, 1);
1687  std::vector<int32_t> cellBiasData(numUnits, 0);
1688  std::vector<int32_t> outputGateBiasData(numUnits, 0);
1689 
1690  armnn::ConstTensor forgetGateBias(biasInfo, forgetGateBiasData);
1691  armnn::ConstTensor cellBias(biasInfo, cellBiasData);
1692  armnn::ConstTensor outputGateBias(biasInfo, outputGateBiasData);
1693 
1694  // Set up params
1695  armnn::LstmInputParams params;
1696  params.m_InputToForgetWeights = &inputToForgetWeights;
1697  params.m_InputToCellWeights = &inputToCellWeights;
1698  params.m_InputToOutputWeights = &inputToOutputWeights;
1699 
1700  params.m_RecurrentToForgetWeights = &recurrentToForgetWeights;
1701  params.m_RecurrentToCellWeights = &recurrentToCellWeights;
1702  params.m_RecurrentToOutputWeights = &recurrentToOutputWeights;
1703 
1704  params.m_ForgetGateBias = &forgetGateBias;
1705  params.m_CellBias = &cellBias;
1706  params.m_OutputGateBias = &outputGateBias;
1707 
1708  // Create network
1709  armnn::INetworkPtr network = armnn::INetwork::Create();
1710  const std::string layerName("qLstm");
1711 
1712  armnn::IConnectableLayer* const input = network->AddInputLayer(0);
1713  armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(1);
1714  armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(2);
1715 
1716  armnn::IConnectableLayer* const qLstmLayer = network->AddQLstmLayer(descriptor, params, layerName.c_str());
1717 
1718  armnn::IConnectableLayer* const outputStateOut = network->AddOutputLayer(0);
1719  armnn::IConnectableLayer* const cellStateOut = network->AddOutputLayer(1);
1720  armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(2);
1721 
1722  // Input/Output tensor info
1723  armnn::TensorInfo inputInfo({numBatches , inputSize},
1724  armnn::DataType::QAsymmS8,
1725  inputScale,
1726  inputOffset);
1727 
1728  armnn::TensorInfo cellStateInfo({numBatches , numUnits},
1729  armnn::DataType::QSymmS16,
1730  cellStateScale,
1731  cellStateOffset);
1732 
1733  armnn::TensorInfo outputStateInfo({numBatches , outputSize},
1734  armnn::DataType::QAsymmS8,
1735  outputScale,
1736  outputOffset);
1737 
1738  // Connect input/output slots
1739  input->GetOutputSlot(0).Connect(qLstmLayer->GetInputSlot(0));
1740  input->GetOutputSlot(0).SetTensorInfo(inputInfo);
1741 
1742  outputStateIn->GetOutputSlot(0).Connect(qLstmLayer->GetInputSlot(1));
1743  outputStateIn->GetOutputSlot(0).SetTensorInfo(cellStateInfo);
1744 
1745  cellStateIn->GetOutputSlot(0).Connect(qLstmLayer->GetInputSlot(2));
1746  cellStateIn->GetOutputSlot(0).SetTensorInfo(outputStateInfo);
1747 
1748  qLstmLayer->GetOutputSlot(0).Connect(outputStateOut->GetInputSlot(0));
1749  qLstmLayer->GetOutputSlot(0).SetTensorInfo(outputStateInfo);
1750 
1751  qLstmLayer->GetOutputSlot(1).Connect(cellStateOut->GetInputSlot(0));
1752  qLstmLayer->GetOutputSlot(1).SetTensorInfo(cellStateInfo);
1753 
1754  qLstmLayer->GetOutputSlot(2).Connect(outputLayer->GetInputSlot(0));
1755  qLstmLayer->GetOutputSlot(2).SetTensorInfo(outputStateInfo);
1756 
1757  armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
1758  CHECK(deserializedNetwork);
1759 
1760  VerifyLstmLayer<armnn::QLstmDescriptor> checker(
1761  layerName,
1762  {inputInfo, cellStateInfo, outputStateInfo},
1763  {outputStateInfo, cellStateInfo, outputStateInfo},
1764  descriptor,
1765  params);
1766 
1767  deserializedNetwork->ExecuteStrategy(checker);
1768 }
1769 
1770 TEST_CASE("SerializeDeserializeQLstmCifgLayerNorm")
1771 {
1772  armnn::QLstmDescriptor descriptor;
1773 
1774  // CIFG params are used when CIFG is disabled
1775  descriptor.m_CifgEnabled = true;
1776  descriptor.m_ProjectionEnabled = false;
1777  descriptor.m_PeepholeEnabled = false;
1778  descriptor.m_LayerNormEnabled = true;
1779 
1780  descriptor.m_CellClip = 0.0f;
1781  descriptor.m_ProjectionClip = 0.0f;
1782 
1783  descriptor.m_InputIntermediateScale = 0.00001f;
1784  descriptor.m_ForgetIntermediateScale = 0.00001f;
1785  descriptor.m_CellIntermediateScale = 0.00001f;
1786  descriptor.m_OutputIntermediateScale = 0.00001f;
1787 
1788  descriptor.m_HiddenStateScale = 0.07f;
1789  descriptor.m_HiddenStateZeroPoint = 0;
1790 
1791  const unsigned int numBatches = 2;
1792  const unsigned int inputSize = 5;
1793  const unsigned int outputSize = 4;
1794  const unsigned int numUnits = 4;
1795 
1796  // Scale/Offset quantization info
1797  float inputScale = 0.0078f;
1798  int32_t inputOffset = 0;
1799 
1800  float outputScale = 0.0078f;
1801  int32_t outputOffset = 0;
1802 
1803  float cellStateScale = 3.5002e-05f;
1804  int32_t cellStateOffset = 0;
1805 
1806  float weightsScale = 0.007f;
1807  int32_t weightsOffset = 0;
1808 
1809  float layerNormScale = 3.5002e-05f;
1810  int32_t layerNormOffset = 0;
1811 
1812  float biasScale = layerNormScale / 1024;
1813  int32_t biasOffset = 0;
1814 
1815  // Weights and bias tensor and quantization info
1816  armnn::TensorInfo inputWeightsInfo({numUnits, inputSize},
1817  armnn::DataType::QSymmS8,
1818  weightsScale,
1819  weightsOffset);
1820 
1821  armnn::TensorInfo recurrentWeightsInfo({numUnits, outputSize},
1822  armnn::DataType::QSymmS8,
1823  weightsScale,
1824  weightsOffset);
1825 
1826  armnn::TensorInfo biasInfo({numUnits},
1827  armnn::DataType::Signed32,
1828  biasScale,
1829  biasOffset);
1830 
1831  armnn::TensorInfo layerNormWeightsInfo({numUnits},
1832  armnn::DataType::QSymmS16,
1833  layerNormScale,
1834  layerNormOffset);
1835 
1836  // Mandatory params
1837  std::vector<int8_t> inputToForgetWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements());
1838  std::vector<int8_t> inputToCellWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements());
1839  std::vector<int8_t> inputToOutputWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements());
1840 
1841  armnn::ConstTensor inputToForgetWeights(inputWeightsInfo, inputToForgetWeightsData);
1842  armnn::ConstTensor inputToCellWeights(inputWeightsInfo, inputToCellWeightsData);
1843  armnn::ConstTensor inputToOutputWeights(inputWeightsInfo, inputToOutputWeightsData);
1844 
1845  std::vector<int8_t> recurrentToForgetWeightsData =
1846  GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements());
1847  std::vector<int8_t> recurrentToCellWeightsData =
1848  GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements());
1849  std::vector<int8_t> recurrentToOutputWeightsData =
1850  GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements());
1851 
1852  armnn::ConstTensor recurrentToForgetWeights(recurrentWeightsInfo, recurrentToForgetWeightsData);
1853  armnn::ConstTensor recurrentToCellWeights(recurrentWeightsInfo, recurrentToCellWeightsData);
1854  armnn::ConstTensor recurrentToOutputWeights(recurrentWeightsInfo, recurrentToOutputWeightsData);
1855 
1856  std::vector<int32_t> forgetGateBiasData(numUnits, 1);
1857  std::vector<int32_t> cellBiasData(numUnits, 0);
1858  std::vector<int32_t> outputGateBiasData(numUnits, 0);
1859 
1860  armnn::ConstTensor forgetGateBias(biasInfo, forgetGateBiasData);
1861  armnn::ConstTensor cellBias(biasInfo, cellBiasData);
1862  armnn::ConstTensor outputGateBias(biasInfo, outputGateBiasData);
1863 
1864  // Layer Norm
1865  std::vector<int16_t> forgetLayerNormWeightsData =
1866  GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements());
1867  std::vector<int16_t> cellLayerNormWeightsData =
1868  GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements());
1869  std::vector<int16_t> outputLayerNormWeightsData =
1870  GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements());
1871 
1872  armnn::ConstTensor forgetLayerNormWeights(layerNormWeightsInfo, forgetLayerNormWeightsData);
1873  armnn::ConstTensor cellLayerNormWeights(layerNormWeightsInfo, cellLayerNormWeightsData);
1874  armnn::ConstTensor outputLayerNormWeights(layerNormWeightsInfo, outputLayerNormWeightsData);
1875 
1876  // Set up params
1877  armnn::LstmInputParams params;
1878 
1879  // Mandatory params
1880  params.m_InputToForgetWeights = &inputToForgetWeights;
1881  params.m_InputToCellWeights = &inputToCellWeights;
1882  params.m_InputToOutputWeights = &inputToOutputWeights;
1883 
1884  params.m_RecurrentToForgetWeights = &recurrentToForgetWeights;
1885  params.m_RecurrentToCellWeights = &recurrentToCellWeights;
1886  params.m_RecurrentToOutputWeights = &recurrentToOutputWeights;
1887 
1888  params.m_ForgetGateBias = &forgetGateBias;
1889  params.m_CellBias = &cellBias;
1890  params.m_OutputGateBias = &outputGateBias;
1891 
1892  // Layer Norm
1893  params.m_ForgetLayerNormWeights = &forgetLayerNormWeights;
1894  params.m_CellLayerNormWeights = &cellLayerNormWeights;
1895  params.m_OutputLayerNormWeights = &outputLayerNormWeights;
1896 
1897  // Create network
1898  armnn::INetworkPtr network = armnn::INetwork::Create();
1899  const std::string layerName("qLstm");
1900 
1901  armnn::IConnectableLayer* const input = network->AddInputLayer(0);
1902  armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(1);
1903  armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(2);
1904 
1905  armnn::IConnectableLayer* const qLstmLayer = network->AddQLstmLayer(descriptor, params, layerName.c_str());
1906 
1907  armnn::IConnectableLayer* const outputStateOut = network->AddOutputLayer(0);
1908  armnn::IConnectableLayer* const cellStateOut = network->AddOutputLayer(1);
1909  armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(2);
1910 
1911  // Input/Output tensor info
1912  armnn::TensorInfo inputInfo({numBatches , inputSize},
1913  armnn::DataType::QAsymmS8,
1914  inputScale,
1915  inputOffset);
1916 
1917  armnn::TensorInfo cellStateInfo({numBatches , numUnits},
1918  armnn::DataType::QSymmS16,
1919  cellStateScale,
1920  cellStateOffset);
1921 
1922  armnn::TensorInfo outputStateInfo({numBatches , outputSize},
1923  armnn::DataType::QAsymmS8,
1924  outputScale,
1925  outputOffset);
1926 
1927  // Connect input/output slots
1928  input->GetOutputSlot(0).Connect(qLstmLayer->GetInputSlot(0));
1929  input->GetOutputSlot(0).SetTensorInfo(inputInfo);
1930 
1931  outputStateIn->GetOutputSlot(0).Connect(qLstmLayer->GetInputSlot(1));
1932  outputStateIn->GetOutputSlot(0).SetTensorInfo(cellStateInfo);
1933 
1934  cellStateIn->GetOutputSlot(0).Connect(qLstmLayer->GetInputSlot(2));
1935  cellStateIn->GetOutputSlot(0).SetTensorInfo(outputStateInfo);
1936 
1937  qLstmLayer->GetOutputSlot(0).Connect(outputStateOut->GetInputSlot(0));
1938  qLstmLayer->GetOutputSlot(0).SetTensorInfo(outputStateInfo);
1939 
1940  qLstmLayer->GetOutputSlot(1).Connect(cellStateOut->GetInputSlot(0));
1941  qLstmLayer->GetOutputSlot(1).SetTensorInfo(cellStateInfo);
1942 
1943  qLstmLayer->GetOutputSlot(2).Connect(outputLayer->GetInputSlot(0));
1944  qLstmLayer->GetOutputSlot(2).SetTensorInfo(outputStateInfo);
1945 
1946  armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
1947  CHECK(deserializedNetwork);
1948 
1949  VerifyLstmLayer<armnn::QLstmDescriptor> checker(layerName,
1950  {inputInfo, cellStateInfo, outputStateInfo},
1951  {outputStateInfo, cellStateInfo, outputStateInfo},
1952  descriptor,
1953  params);
1954 
1955  deserializedNetwork->ExecuteStrategy(checker);
1956 }
1957 
1958 TEST_CASE("SerializeDeserializeQLstmAdvanced")
1959 {
1960  armnn::QLstmDescriptor descriptor;
1961 
1962  descriptor.m_CifgEnabled = false;
1963  descriptor.m_ProjectionEnabled = true;
1964  descriptor.m_PeepholeEnabled = true;
1965  descriptor.m_LayerNormEnabled = true;
1966 
1967  descriptor.m_CellClip = 0.1f;
1968  descriptor.m_ProjectionClip = 0.1f;
1969 
1970  descriptor.m_InputIntermediateScale = 0.00001f;
1971  descriptor.m_ForgetIntermediateScale = 0.00001f;
1972  descriptor.m_CellIntermediateScale = 0.00001f;
1973  descriptor.m_OutputIntermediateScale = 0.00001f;
1974 
1975  descriptor.m_HiddenStateScale = 0.07f;
1976  descriptor.m_HiddenStateZeroPoint = 0;
1977 
1978  const unsigned int numBatches = 2;
1979  const unsigned int inputSize = 5;
1980  const unsigned int outputSize = 4;
1981  const unsigned int numUnits = 4;
1982 
1983  // Scale/Offset quantization info
1984  float inputScale = 0.0078f;
1985  int32_t inputOffset = 0;
1986 
1987  float outputScale = 0.0078f;
1988  int32_t outputOffset = 0;
1989 
1990  float cellStateScale = 3.5002e-05f;
1991  int32_t cellStateOffset = 0;
1992 
1993  float weightsScale = 0.007f;
1994  int32_t weightsOffset = 0;
1995 
1996  float layerNormScale = 3.5002e-05f;
1997  int32_t layerNormOffset = 0;
1998 
1999  float biasScale = layerNormScale / 1024;
2000  int32_t biasOffset = 0;
2001 
2002  // Weights and bias tensor and quantization info
2003  armnn::TensorInfo inputWeightsInfo({numUnits, inputSize},
2004  armnn::DataType::QSymmS8,
2005  weightsScale,
2006  weightsOffset);
2007 
2008  armnn::TensorInfo recurrentWeightsInfo({numUnits, outputSize},
2009  armnn::DataType::QSymmS8,
2010  weightsScale,
2011  weightsOffset);
2012 
2013  armnn::TensorInfo biasInfo({numUnits},
2014  armnn::DataType::Signed32,
2015  biasScale,
2016  biasOffset);
2017 
2018  armnn::TensorInfo peepholeWeightsInfo({numUnits},
2019  armnn::DataType::QSymmS16,
2020  weightsScale,
2021  weightsOffset);
2022 
2023  armnn::TensorInfo layerNormWeightsInfo({numUnits},
2024  armnn::DataType::QSymmS16,
2025  layerNormScale,
2026  layerNormOffset);
2027 
2028  armnn::TensorInfo projectionWeightsInfo({outputSize, numUnits},
2029  armnn::DataType::QSymmS8,
2030  weightsScale,
2031  weightsOffset);
2032 
2033  // Mandatory params
2034  std::vector<int8_t> inputToForgetWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements());
2035  std::vector<int8_t> inputToCellWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements());
2036  std::vector<int8_t> inputToOutputWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements());
2037 
2038  armnn::ConstTensor inputToForgetWeights(inputWeightsInfo, inputToForgetWeightsData);
2039  armnn::ConstTensor inputToCellWeights(inputWeightsInfo, inputToCellWeightsData);
2040  armnn::ConstTensor inputToOutputWeights(inputWeightsInfo, inputToOutputWeightsData);
2041 
2042  std::vector<int8_t> recurrentToForgetWeightsData =
2043  GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements());
2044  std::vector<int8_t> recurrentToCellWeightsData =
2045  GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements());
2046  std::vector<int8_t> recurrentToOutputWeightsData =
2047  GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements());
2048 
2049  armnn::ConstTensor recurrentToForgetWeights(recurrentWeightsInfo, recurrentToForgetWeightsData);
2050  armnn::ConstTensor recurrentToCellWeights(recurrentWeightsInfo, recurrentToCellWeightsData);
2051  armnn::ConstTensor recurrentToOutputWeights(recurrentWeightsInfo, recurrentToOutputWeightsData);
2052 
2053  std::vector<int32_t> forgetGateBiasData(numUnits, 1);
2054  std::vector<int32_t> cellBiasData(numUnits, 0);
2055  std::vector<int32_t> outputGateBiasData(numUnits, 0);
2056 
2057  armnn::ConstTensor forgetGateBias(biasInfo, forgetGateBiasData);
2058  armnn::ConstTensor cellBias(biasInfo, cellBiasData);
2059  armnn::ConstTensor outputGateBias(biasInfo, outputGateBiasData);
2060 
2061  // CIFG
2062  std::vector<int8_t> inputToInputWeightsData = GenerateRandomData<int8_t>(inputWeightsInfo.GetNumElements());
2063  std::vector<int8_t> recurrentToInputWeightsData =
2064  GenerateRandomData<int8_t>(recurrentWeightsInfo.GetNumElements());
2065  std::vector<int32_t> inputGateBiasData(numUnits, 1);
2066 
2067  armnn::ConstTensor inputToInputWeights(inputWeightsInfo, inputToInputWeightsData);
2068  armnn::ConstTensor recurrentToInputWeights(recurrentWeightsInfo, recurrentToInputWeightsData);
2069  armnn::ConstTensor inputGateBias(biasInfo, inputGateBiasData);
2070 
2071  // Peephole
2072  std::vector<int16_t> cellToInputWeightsData = GenerateRandomData<int16_t>(peepholeWeightsInfo.GetNumElements());
2073  std::vector<int16_t> cellToForgetWeightsData = GenerateRandomData<int16_t>(peepholeWeightsInfo.GetNumElements());
2074  std::vector<int16_t> cellToOutputWeightsData = GenerateRandomData<int16_t>(peepholeWeightsInfo.GetNumElements());
2075 
2076  armnn::ConstTensor cellToInputWeights(peepholeWeightsInfo, cellToInputWeightsData);
2077  armnn::ConstTensor cellToForgetWeights(peepholeWeightsInfo, cellToForgetWeightsData);
2078  armnn::ConstTensor cellToOutputWeights(peepholeWeightsInfo, cellToOutputWeightsData);
2079 
2080  // Projection
2081  std::vector<int8_t> projectionWeightsData = GenerateRandomData<int8_t>(projectionWeightsInfo.GetNumElements());
2082  std::vector<int32_t> projectionBiasData(outputSize, 1);
2083 
2084  armnn::ConstTensor projectionWeights(projectionWeightsInfo, projectionWeightsData);
2085  armnn::ConstTensor projectionBias(biasInfo, projectionBiasData);
2086 
2087  // Layer Norm
2088  std::vector<int16_t> inputLayerNormWeightsData =
2089  GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements());
2090  std::vector<int16_t> forgetLayerNormWeightsData =
2091  GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements());
2092  std::vector<int16_t> cellLayerNormWeightsData =
2093  GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements());
2094  std::vector<int16_t> outputLayerNormWeightsData =
2095  GenerateRandomData<int16_t>(layerNormWeightsInfo.GetNumElements());
2096 
2097  armnn::ConstTensor inputLayerNormWeights(layerNormWeightsInfo, inputLayerNormWeightsData);
2098  armnn::ConstTensor forgetLayerNormWeights(layerNormWeightsInfo, forgetLayerNormWeightsData);
2099  armnn::ConstTensor cellLayerNormWeights(layerNormWeightsInfo, cellLayerNormWeightsData);
2100  armnn::ConstTensor outputLayerNormWeights(layerNormWeightsInfo, outputLayerNormWeightsData);
2101 
2102  // Set up params
2103  armnn::LstmInputParams params;
2104 
2105  // Mandatory params
2106  params.m_InputToForgetWeights = &inputToForgetWeights;
2107  params.m_InputToCellWeights = &inputToCellWeights;
2108  params.m_InputToOutputWeights = &inputToOutputWeights;
2109 
2110  params.m_RecurrentToForgetWeights = &recurrentToForgetWeights;
2111  params.m_RecurrentToCellWeights = &recurrentToCellWeights;
2112  params.m_RecurrentToOutputWeights = &recurrentToOutputWeights;
2113 
2114  params.m_ForgetGateBias = &forgetGateBias;
2115  params.m_CellBias = &cellBias;
2116  params.m_OutputGateBias = &outputGateBias;
2117 
2118  // CIFG
2119  params.m_InputToInputWeights = &inputToInputWeights;
2120  params.m_RecurrentToInputWeights = &recurrentToInputWeights;
2121  params.m_InputGateBias = &inputGateBias;
2122 
2123  // Peephole
2124  params.m_CellToInputWeights = &cellToInputWeights;
2125  params.m_CellToForgetWeights = &cellToForgetWeights;
2126  params.m_CellToOutputWeights = &cellToOutputWeights;
2127 
2128  // Projection
2129  params.m_ProjectionWeights = &projectionWeights;
2130  params.m_ProjectionBias = &projectionBias;
2131 
2132  // Layer Norm
2133  params.m_InputLayerNormWeights = &inputLayerNormWeights;
2134  params.m_ForgetLayerNormWeights = &forgetLayerNormWeights;
2135  params.m_CellLayerNormWeights = &cellLayerNormWeights;
2136  params.m_OutputLayerNormWeights = &outputLayerNormWeights;
2137 
2138  // Create network
2139  armnn::INetworkPtr network = armnn::INetwork::Create();
2140  const std::string layerName("qLstm");
2141 
2142  armnn::IConnectableLayer* const input = network->AddInputLayer(0);
2143  armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(1);
2144  armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(2);
2145 
2146  armnn::IConnectableLayer* const qLstmLayer = network->AddQLstmLayer(descriptor, params, layerName.c_str());
2147 
2148  armnn::IConnectableLayer* const outputStateOut = network->AddOutputLayer(0);
2149  armnn::IConnectableLayer* const cellStateOut = network->AddOutputLayer(1);
2150  armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(2);
2151 
2152  // Input/Output tensor info
2153  armnn::TensorInfo inputInfo({numBatches , inputSize},
2154  armnn::DataType::QAsymmS8,
2155  inputScale,
2156  inputOffset);
2157 
2158  armnn::TensorInfo cellStateInfo({numBatches , numUnits},
2159  armnn::DataType::QSymmS16,
2160  cellStateScale,
2161  cellStateOffset);
2162 
2163  armnn::TensorInfo outputStateInfo({numBatches , outputSize},
2164  armnn::DataType::QAsymmS8,
2165  outputScale,
2166  outputOffset);
2167 
2168  // Connect input/output slots
2169  input->GetOutputSlot(0).Connect(qLstmLayer->GetInputSlot(0));
2170  input->GetOutputSlot(0).SetTensorInfo(inputInfo);
2171 
2172  outputStateIn->GetOutputSlot(0).Connect(qLstmLayer->GetInputSlot(1));
2173  outputStateIn->GetOutputSlot(0).SetTensorInfo(cellStateInfo);
2174 
2175  cellStateIn->GetOutputSlot(0).Connect(qLstmLayer->GetInputSlot(2));
2176  cellStateIn->GetOutputSlot(0).SetTensorInfo(outputStateInfo);
2177 
2178  qLstmLayer->GetOutputSlot(0).Connect(outputStateOut->GetInputSlot(0));
2179  qLstmLayer->GetOutputSlot(0).SetTensorInfo(outputStateInfo);
2180 
2181  qLstmLayer->GetOutputSlot(1).Connect(cellStateOut->GetInputSlot(0));
2182  qLstmLayer->GetOutputSlot(1).SetTensorInfo(cellStateInfo);
2183 
2184  qLstmLayer->GetOutputSlot(2).Connect(outputLayer->GetInputSlot(0));
2185  qLstmLayer->GetOutputSlot(2).SetTensorInfo(outputStateInfo);
2186 
2187  armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2188  CHECK(deserializedNetwork);
2189 
2190  VerifyLstmLayer<armnn::QLstmDescriptor> checker(layerName,
2191  {inputInfo, cellStateInfo, outputStateInfo},
2192  {outputStateInfo, cellStateInfo, outputStateInfo},
2193  descriptor,
2194  params);
2195 
2196  deserializedNetwork->ExecuteStrategy(checker);
2197 }
2198 
2199 TEST_CASE("SerializeDeserializeUnidirectionalSequenceLstmCifgPeepholeNoProjection")
2200 {
2201  armnn::UnidirectionalSequenceLstmDescriptor descriptor;
2202  descriptor.m_ActivationFunc = 4;
2203  descriptor.m_ClippingThresProj = 0.0f;
2204  descriptor.m_ClippingThresCell = 0.0f;
2205  descriptor.m_CifgEnabled = true; // if this is true then we DON'T need to set the OptCifgParams
2206  descriptor.m_ProjectionEnabled = false;
2207  descriptor.m_PeepholeEnabled = true;
2208  descriptor.m_TimeMajor = false;
2209 
2210  const uint32_t batchSize = 1;
2211  const uint32_t timeSize = 2;
2212  const uint32_t inputSize = 2;
2213  const uint32_t numUnits = 4;
2214  const uint32_t outputSize = numUnits;
2215 
2216  armnn::TensorInfo inputWeightsInfo1({numUnits, inputSize}, armnn::DataType::Float32);
2217  std::vector<float> inputToForgetWeightsData = GenerateRandomData<float>(inputWeightsInfo1.GetNumElements());
2218  armnn::ConstTensor inputToForgetWeights(inputWeightsInfo1, inputToForgetWeightsData);
2219 
2220  std::vector<float> inputToCellWeightsData = GenerateRandomData<float>(inputWeightsInfo1.GetNumElements());
2221  armnn::ConstTensor inputToCellWeights(inputWeightsInfo1, inputToCellWeightsData);
2222 
2223  std::vector<float> inputToOutputWeightsData = GenerateRandomData<float>(inputWeightsInfo1.GetNumElements());
2224  armnn::ConstTensor inputToOutputWeights(inputWeightsInfo1, inputToOutputWeightsData);
2225 
2226  armnn::TensorInfo inputWeightsInfo2({numUnits, outputSize}, armnn::DataType::Float32);
2227  std::vector<float> recurrentToForgetWeightsData = GenerateRandomData<float>(inputWeightsInfo2.GetNumElements());
2228  armnn::ConstTensor recurrentToForgetWeights(inputWeightsInfo2, recurrentToForgetWeightsData);
2229 
2230  std::vector<float> recurrentToCellWeightsData = GenerateRandomData<float>(inputWeightsInfo2.GetNumElements());
2231  armnn::ConstTensor recurrentToCellWeights(inputWeightsInfo2, recurrentToCellWeightsData);
2232 
2233  std::vector<float> recurrentToOutputWeightsData = GenerateRandomData<float>(inputWeightsInfo2.GetNumElements());
2234  armnn::ConstTensor recurrentToOutputWeights(inputWeightsInfo2, recurrentToOutputWeightsData);
2235 
2236  armnn::TensorInfo inputWeightsInfo3({numUnits}, armnn::DataType::Float32);
2237  std::vector<float> cellToForgetWeightsData = GenerateRandomData<float>(inputWeightsInfo3.GetNumElements());
2238  armnn::ConstTensor cellToForgetWeights(inputWeightsInfo3, cellToForgetWeightsData);
2239 
2240  std::vector<float> cellToOutputWeightsData = GenerateRandomData<float>(inputWeightsInfo3.GetNumElements());
2241  armnn::ConstTensor cellToOutputWeights(inputWeightsInfo3, cellToOutputWeightsData);
2242 
2243  std::vector<float> forgetGateBiasData(numUnits, 1.0f);
2244  armnn::ConstTensor forgetGateBias(inputWeightsInfo3, forgetGateBiasData);
2245 
2246  std::vector<float> cellBiasData(numUnits, 0.0f);
2247  armnn::ConstTensor cellBias(inputWeightsInfo3, cellBiasData);
2248 
2249  std::vector<float> outputGateBiasData(numUnits, 0.0f);
2250  armnn::ConstTensor outputGateBias(inputWeightsInfo3, outputGateBiasData);
2251 
2252  armnn::LstmInputParams params;
2253  params.m_InputToForgetWeights = &inputToForgetWeights;
2254  params.m_InputToCellWeights = &inputToCellWeights;
2255  params.m_InputToOutputWeights = &inputToOutputWeights;
2256  params.m_RecurrentToForgetWeights = &recurrentToForgetWeights;
2257  params.m_RecurrentToCellWeights = &recurrentToCellWeights;
2258  params.m_RecurrentToOutputWeights = &recurrentToOutputWeights;
2259  params.m_ForgetGateBias = &forgetGateBias;
2260  params.m_CellBias = &cellBias;
2261  params.m_OutputGateBias = &outputGateBias;
2262  params.m_CellToForgetWeights = &cellToForgetWeights;
2263  params.m_CellToOutputWeights = &cellToOutputWeights;
2264 
2265  armnn::INetworkPtr network = armnn::INetwork::Create();
2266  armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
2267  armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(1);
2268  armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(2);
2269  const std::string layerName("UnidirectionalSequenceLstm");
2270  armnn::IConnectableLayer* const unidirectionalSequenceLstmLayer =
2271  network->AddUnidirectionalSequenceLstmLayer(descriptor, params, layerName.c_str());
2272  armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
2273 
2274  // connect up
2275  armnn::TensorInfo inputTensorInfo({ batchSize, timeSize, inputSize }, armnn::DataType::Float32);
2276  armnn::TensorInfo cellStateTensorInfo({ batchSize, numUnits}, armnn::DataType::Float32);
2277  armnn::TensorInfo outputStateTensorInfo({ batchSize, outputSize }, armnn::DataType::Float32);
2278  armnn::TensorInfo outputTensorInfo({ batchSize, timeSize, outputSize }, armnn::DataType::Float32);
2279 
2280  inputLayer->GetOutputSlot(0).Connect(unidirectionalSequenceLstmLayer->GetInputSlot(0));
2281  inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
2282 
2283  outputStateIn->GetOutputSlot(0).Connect(unidirectionalSequenceLstmLayer->GetInputSlot(1));
2284  outputStateIn->GetOutputSlot(0).SetTensorInfo(outputStateTensorInfo);
2285 
2286  cellStateIn->GetOutputSlot(0).Connect(unidirectionalSequenceLstmLayer->GetInputSlot(2));
2287  cellStateIn->GetOutputSlot(0).SetTensorInfo(cellStateTensorInfo);
2288 
2289  unidirectionalSequenceLstmLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
2290  unidirectionalSequenceLstmLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
2291 
2292  armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2293  CHECK(deserializedNetwork);
2294 
2295  VerifyLstmLayer<armnn::UnidirectionalSequenceLstmDescriptor> checker(
2296  layerName,
2297  {inputTensorInfo, outputStateTensorInfo, cellStateTensorInfo},
2298  {outputTensorInfo},
2299  descriptor,
2300  params);
2301  deserializedNetwork->ExecuteStrategy(checker);
2302 }
2303 
2304 TEST_CASE("SerializeDeserializeUnidirectionalSequenceLstmNoCifgWithPeepholeAndProjection")
2305 {
2306  armnn::UnidirectionalSequenceLstmDescriptor descriptor;
2307  descriptor.m_ActivationFunc = 4;
2308  descriptor.m_ClippingThresProj = 0.0f;
2309  descriptor.m_ClippingThresCell = 0.0f;
2310  descriptor.m_CifgEnabled = false; // if this is true then we DON'T need to set the OptCifgParams
2311  descriptor.m_ProjectionEnabled = true;
2312  descriptor.m_PeepholeEnabled = true;
2313  descriptor.m_TimeMajor = false;
2314 
2315  const uint32_t batchSize = 2;
2316  const uint32_t timeSize = 2;
2317  const uint32_t inputSize = 5;
2318  const uint32_t numUnits = 20;
2319  const uint32_t outputSize = 16;
2320 
2321  armnn::TensorInfo tensorInfo20x5({numUnits, inputSize}, armnn::DataType::Float32);
2322  std::vector<float> inputToInputWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
2323  armnn::ConstTensor inputToInputWeights(tensorInfo20x5, inputToInputWeightsData);
2324 
2325  std::vector<float> inputToForgetWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
2326  armnn::ConstTensor inputToForgetWeights(tensorInfo20x5, inputToForgetWeightsData);
2327 
2328  std::vector<float> inputToCellWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
2329  armnn::ConstTensor inputToCellWeights(tensorInfo20x5, inputToCellWeightsData);
2330 
2331  std::vector<float> inputToOutputWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
2332  armnn::ConstTensor inputToOutputWeights(tensorInfo20x5, inputToOutputWeightsData);
2333 
2334  armnn::TensorInfo tensorInfo20({numUnits}, armnn::DataType::Float32);
2335  std::vector<float> inputGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
2336  armnn::ConstTensor inputGateBias(tensorInfo20, inputGateBiasData);
2337 
2338  std::vector<float> forgetGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
2339  armnn::ConstTensor forgetGateBias(tensorInfo20, forgetGateBiasData);
2340 
2341  std::vector<float> cellBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
2342  armnn::ConstTensor cellBias(tensorInfo20, cellBiasData);
2343 
2344  std::vector<float> outputGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
2345  armnn::ConstTensor outputGateBias(tensorInfo20, outputGateBiasData);
2346 
2347  armnn::TensorInfo tensorInfo20x16({numUnits, outputSize}, armnn::DataType::Float32);
2348  std::vector<float> recurrentToInputWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
2349  armnn::ConstTensor recurrentToInputWeights(tensorInfo20x16, recurrentToInputWeightsData);
2350 
2351  std::vector<float> recurrentToForgetWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
2352  armnn::ConstTensor recurrentToForgetWeights(tensorInfo20x16, recurrentToForgetWeightsData);
2353 
2354  std::vector<float> recurrentToCellWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
2355  armnn::ConstTensor recurrentToCellWeights(tensorInfo20x16, recurrentToCellWeightsData);
2356 
2357  std::vector<float> recurrentToOutputWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
2358  armnn::ConstTensor recurrentToOutputWeights(tensorInfo20x16, recurrentToOutputWeightsData);
2359 
2360  std::vector<float> cellToInputWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
2361  armnn::ConstTensor cellToInputWeights(tensorInfo20, cellToInputWeightsData);
2362 
2363  std::vector<float> cellToForgetWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
2364  armnn::ConstTensor cellToForgetWeights(tensorInfo20, cellToForgetWeightsData);
2365 
2366  std::vector<float> cellToOutputWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
2367  armnn::ConstTensor cellToOutputWeights(tensorInfo20, cellToOutputWeightsData);
2368 
2369  armnn::TensorInfo tensorInfo16x20({outputSize, numUnits}, armnn::DataType::Float32);
2370  std::vector<float> projectionWeightsData = GenerateRandomData<float>(tensorInfo16x20.GetNumElements());
2371  armnn::ConstTensor projectionWeights(tensorInfo16x20, projectionWeightsData);
2372 
2373  armnn::TensorInfo tensorInfo16({outputSize}, armnn::DataType::Float32);
2374  std::vector<float> projectionBiasData(outputSize, 0.f);
2375  armnn::ConstTensor projectionBias(tensorInfo16, projectionBiasData);
2376 
2377  armnn::LstmInputParams params;
2378  params.m_InputToForgetWeights = &inputToForgetWeights;
2379  params.m_InputToCellWeights = &inputToCellWeights;
2380  params.m_InputToOutputWeights = &inputToOutputWeights;
2381  params.m_RecurrentToForgetWeights = &recurrentToForgetWeights;
2382  params.m_RecurrentToCellWeights = &recurrentToCellWeights;
2383  params.m_RecurrentToOutputWeights = &recurrentToOutputWeights;
2384  params.m_ForgetGateBias = &forgetGateBias;
2385  params.m_CellBias = &cellBias;
2386  params.m_OutputGateBias = &outputGateBias;
2387 
2388  // additional params because: descriptor.m_CifgEnabled = false
2389  params.m_InputToInputWeights = &inputToInputWeights;
2390  params.m_RecurrentToInputWeights = &recurrentToInputWeights;
2391  params.m_CellToInputWeights = &cellToInputWeights;
2392  params.m_InputGateBias = &inputGateBias;
2393 
2394  // additional params because: descriptor.m_ProjectionEnabled = true
2395  params.m_ProjectionWeights = &projectionWeights;
2396  params.m_ProjectionBias = &projectionBias;
2397 
2398  // additional params because: descriptor.m_PeepholeEnabled = true
2399  params.m_CellToForgetWeights = &cellToForgetWeights;
2400  params.m_CellToOutputWeights = &cellToOutputWeights;
2401 
2402  armnn::INetworkPtr network = armnn::INetwork::Create();
2403  armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
2404  armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(1);
2405  armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(2);
2406  const std::string layerName("unidirectionalSequenceLstm");
2407  armnn::IConnectableLayer* const unidirectionalSequenceLstmLayer =
2408  network->AddUnidirectionalSequenceLstmLayer(descriptor, params, layerName.c_str());
2409  armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
2410 
2411  // connect up
2412  armnn::TensorInfo inputTensorInfo({ batchSize, timeSize, inputSize }, armnn::DataType::Float32);
2413  armnn::TensorInfo cellStateTensorInfo({ batchSize, numUnits}, armnn::DataType::Float32);
2414  armnn::TensorInfo outputStateTensorInfo({ batchSize, outputSize }, armnn::DataType::Float32);
2415  armnn::TensorInfo outputTensorInfo({ batchSize, timeSize, outputSize }, armnn::DataType::Float32);
2416 
2417  inputLayer->GetOutputSlot(0).Connect(unidirectionalSequenceLstmLayer->GetInputSlot(0));
2418  inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
2419 
2420  outputStateIn->GetOutputSlot(0).Connect(unidirectionalSequenceLstmLayer->GetInputSlot(1));
2421  outputStateIn->GetOutputSlot(0).SetTensorInfo(outputStateTensorInfo);
2422 
2423  cellStateIn->GetOutputSlot(0).Connect(unidirectionalSequenceLstmLayer->GetInputSlot(2));
2424  cellStateIn->GetOutputSlot(0).SetTensorInfo(cellStateTensorInfo);
2425 
2426  unidirectionalSequenceLstmLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
2427  unidirectionalSequenceLstmLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
2428 
2429  armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2430  CHECK(deserializedNetwork);
2431 
2432  VerifyLstmLayer<armnn::UnidirectionalSequenceLstmDescriptor> checker(
2433  layerName,
2434  {inputTensorInfo, outputStateTensorInfo, cellStateTensorInfo},
2435  {outputTensorInfo},
2436  descriptor,
2437  params);
2438  deserializedNetwork->ExecuteStrategy(checker);
2439 }
2440 
2441 TEST_CASE("SerializeDeserializeUnidirectionalSequenceLstmNoCifgWithPeepholeWithProjectionWithLayerNorm")
2442 {
2443  armnn::UnidirectionalSequenceLstmDescriptor descriptor;
2444  descriptor.m_ActivationFunc = 4;
2445  descriptor.m_ClippingThresProj = 0.0f;
2446  descriptor.m_ClippingThresCell = 0.0f;
2447  descriptor.m_CifgEnabled = false; // if this is true then we DON'T need to set the OptCifgParams
2448  descriptor.m_ProjectionEnabled = true;
2449  descriptor.m_PeepholeEnabled = true;
2450  descriptor.m_LayerNormEnabled = true;
2451  descriptor.m_TimeMajor = false;
2452 
2453  const uint32_t batchSize = 2;
2454  const uint32_t timeSize = 2;
2455  const uint32_t inputSize = 5;
2456  const uint32_t numUnits = 20;
2457  const uint32_t outputSize = 16;
2458 
2459  armnn::TensorInfo tensorInfo20x5({numUnits, inputSize}, armnn::DataType::Float32);
2460  std::vector<float> inputToInputWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
2461  armnn::ConstTensor inputToInputWeights(tensorInfo20x5, inputToInputWeightsData);
2462 
2463  std::vector<float> inputToForgetWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
2464  armnn::ConstTensor inputToForgetWeights(tensorInfo20x5, inputToForgetWeightsData);
2465 
2466  std::vector<float> inputToCellWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
2467  armnn::ConstTensor inputToCellWeights(tensorInfo20x5, inputToCellWeightsData);
2468 
2469  std::vector<float> inputToOutputWeightsData = GenerateRandomData<float>(tensorInfo20x5.GetNumElements());
2470  armnn::ConstTensor inputToOutputWeights(tensorInfo20x5, inputToOutputWeightsData);
2471 
2472  armnn::TensorInfo tensorInfo20({numUnits}, armnn::DataType::Float32);
2473  std::vector<float> inputGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
2474  armnn::ConstTensor inputGateBias(tensorInfo20, inputGateBiasData);
2475 
2476  std::vector<float> forgetGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
2477  armnn::ConstTensor forgetGateBias(tensorInfo20, forgetGateBiasData);
2478 
2479  std::vector<float> cellBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
2480  armnn::ConstTensor cellBias(tensorInfo20, cellBiasData);
2481 
2482  std::vector<float> outputGateBiasData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
2483  armnn::ConstTensor outputGateBias(tensorInfo20, outputGateBiasData);
2484 
2485  armnn::TensorInfo tensorInfo20x16({numUnits, outputSize}, armnn::DataType::Float32);
2486  std::vector<float> recurrentToInputWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
2487  armnn::ConstTensor recurrentToInputWeights(tensorInfo20x16, recurrentToInputWeightsData);
2488 
2489  std::vector<float> recurrentToForgetWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
2490  armnn::ConstTensor recurrentToForgetWeights(tensorInfo20x16, recurrentToForgetWeightsData);
2491 
2492  std::vector<float> recurrentToCellWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
2493  armnn::ConstTensor recurrentToCellWeights(tensorInfo20x16, recurrentToCellWeightsData);
2494 
2495  std::vector<float> recurrentToOutputWeightsData = GenerateRandomData<float>(tensorInfo20x16.GetNumElements());
2496  armnn::ConstTensor recurrentToOutputWeights(tensorInfo20x16, recurrentToOutputWeightsData);
2497 
2498  std::vector<float> cellToInputWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
2499  armnn::ConstTensor cellToInputWeights(tensorInfo20, cellToInputWeightsData);
2500 
2501  std::vector<float> cellToForgetWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
2502  armnn::ConstTensor cellToForgetWeights(tensorInfo20, cellToForgetWeightsData);
2503 
2504  std::vector<float> cellToOutputWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
2505  armnn::ConstTensor cellToOutputWeights(tensorInfo20, cellToOutputWeightsData);
2506 
2507  armnn::TensorInfo tensorInfo16x20({outputSize, numUnits}, armnn::DataType::Float32);
2508  std::vector<float> projectionWeightsData = GenerateRandomData<float>(tensorInfo16x20.GetNumElements());
2509  armnn::ConstTensor projectionWeights(tensorInfo16x20, projectionWeightsData);
2510 
2511  armnn::TensorInfo tensorInfo16({outputSize}, armnn::DataType::Float32);
2512  std::vector<float> projectionBiasData(outputSize, 0.f);
2513  armnn::ConstTensor projectionBias(tensorInfo16, projectionBiasData);
2514 
2515  std::vector<float> inputLayerNormWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
2516  armnn::ConstTensor inputLayerNormWeights(tensorInfo20, forgetGateBiasData);
2517 
2518  std::vector<float> forgetLayerNormWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
2519  armnn::ConstTensor forgetLayerNormWeights(tensorInfo20, forgetGateBiasData);
2520 
2521  std::vector<float> cellLayerNormWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
2522  armnn::ConstTensor cellLayerNormWeights(tensorInfo20, forgetGateBiasData);
2523 
2524  std::vector<float> outLayerNormWeightsData = GenerateRandomData<float>(tensorInfo20.GetNumElements());
2525  armnn::ConstTensor outLayerNormWeights(tensorInfo20, forgetGateBiasData);
2526 
2527  armnn::LstmInputParams params;
2528  params.m_InputToForgetWeights = &inputToForgetWeights;
2529  params.m_InputToCellWeights = &inputToCellWeights;
2530  params.m_InputToOutputWeights = &inputToOutputWeights;
2531  params.m_RecurrentToForgetWeights = &recurrentToForgetWeights;
2532  params.m_RecurrentToCellWeights = &recurrentToCellWeights;
2533  params.m_RecurrentToOutputWeights = &recurrentToOutputWeights;
2534  params.m_ForgetGateBias = &forgetGateBias;
2535  params.m_CellBias = &cellBias;
2536  params.m_OutputGateBias = &outputGateBias;
2537 
2538  // additional params because: descriptor.m_CifgEnabled = false
2539  params.m_InputToInputWeights = &inputToInputWeights;
2540  params.m_RecurrentToInputWeights = &recurrentToInputWeights;
2541  params.m_CellToInputWeights = &cellToInputWeights;
2542  params.m_InputGateBias = &inputGateBias;
2543 
2544  // additional params because: descriptor.m_ProjectionEnabled = true
2545  params.m_ProjectionWeights = &projectionWeights;
2546  params.m_ProjectionBias = &projectionBias;
2547 
2548  // additional params because: descriptor.m_PeepholeEnabled = true
2549  params.m_CellToForgetWeights = &cellToForgetWeights;
2550  params.m_CellToOutputWeights = &cellToOutputWeights;
2551 
2552  // additional params because: despriptor.m_LayerNormEnabled = true
2553  params.m_InputLayerNormWeights = &inputLayerNormWeights;
2554  params.m_ForgetLayerNormWeights = &forgetLayerNormWeights;
2555  params.m_CellLayerNormWeights = &cellLayerNormWeights;
2556  params.m_OutputLayerNormWeights = &outLayerNormWeights;
2557 
2558  armnn::INetworkPtr network = armnn::INetwork::Create();
2559  armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
2560  armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(1);
2561  armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(2);
2562  const std::string layerName("unidirectionalSequenceLstm");
2563  armnn::IConnectableLayer* const unidirectionalSequenceLstmLayer =
2564  network->AddUnidirectionalSequenceLstmLayer(descriptor, params, layerName.c_str());
2565  armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
2566 
2567  // connect up
2568  armnn::TensorInfo inputTensorInfo({ batchSize, timeSize, inputSize }, armnn::DataType::Float32);
2569  armnn::TensorInfo cellStateTensorInfo({ batchSize, numUnits}, armnn::DataType::Float32);
2570  armnn::TensorInfo outputStateTensorInfo({ batchSize, outputSize }, armnn::DataType::Float32);
2571  armnn::TensorInfo outputTensorInfo({ batchSize, timeSize, outputSize }, armnn::DataType::Float32);
2572 
2573  inputLayer->GetOutputSlot(0).Connect(unidirectionalSequenceLstmLayer->GetInputSlot(0));
2574  inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
2575 
2576  outputStateIn->GetOutputSlot(0).Connect(unidirectionalSequenceLstmLayer->GetInputSlot(1));
2577  outputStateIn->GetOutputSlot(0).SetTensorInfo(outputStateTensorInfo);
2578 
2579  cellStateIn->GetOutputSlot(0).Connect(unidirectionalSequenceLstmLayer->GetInputSlot(2));
2580  cellStateIn->GetOutputSlot(0).SetTensorInfo(cellStateTensorInfo);
2581 
2582  unidirectionalSequenceLstmLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
2583  unidirectionalSequenceLstmLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
2584 
2585  armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2586  CHECK(deserializedNetwork);
2587 
2588  VerifyLstmLayer<armnn::UnidirectionalSequenceLstmDescriptor> checker(
2589  layerName,
2590  {inputTensorInfo, outputStateTensorInfo, cellStateTensorInfo},
2591  {outputTensorInfo},
2592  descriptor,
2593  params);
2594  deserializedNetwork->ExecuteStrategy(checker);
2595 }
2596 
2597 TEST_CASE("SerializeDeserializeUnidirectionalSequenceLstmCifgPeepholeNoProjectionTimeMajor")
2598 {
2599  armnn::UnidirectionalSequenceLstmDescriptor descriptor;
2600  descriptor.m_ActivationFunc = 4;
2601  descriptor.m_ClippingThresProj = 0.0f;
2602  descriptor.m_ClippingThresCell = 0.0f;
2603  descriptor.m_CifgEnabled = true; // if this is true then we DON'T need to set the OptCifgParams
2604  descriptor.m_ProjectionEnabled = false;
2605  descriptor.m_PeepholeEnabled = true;
2606  descriptor.m_TimeMajor = true;
2607 
2608  const uint32_t batchSize = 1;
2609  const uint32_t timeSize = 2;
2610  const uint32_t inputSize = 2;
2611  const uint32_t numUnits = 4;
2612  const uint32_t outputSize = numUnits;
2613 
2614  armnn::TensorInfo inputWeightsInfo1({numUnits, inputSize}, armnn::DataType::Float32);
2615  std::vector<float> inputToForgetWeightsData = GenerateRandomData<float>(inputWeightsInfo1.GetNumElements());
2616  armnn::ConstTensor inputToForgetWeights(inputWeightsInfo1, inputToForgetWeightsData);
2617 
2618  std::vector<float> inputToCellWeightsData = GenerateRandomData<float>(inputWeightsInfo1.GetNumElements());
2619  armnn::ConstTensor inputToCellWeights(inputWeightsInfo1, inputToCellWeightsData);
2620 
2621  std::vector<float> inputToOutputWeightsData = GenerateRandomData<float>(inputWeightsInfo1.GetNumElements());
2622  armnn::ConstTensor inputToOutputWeights(inputWeightsInfo1, inputToOutputWeightsData);
2623 
2624  armnn::TensorInfo inputWeightsInfo2({numUnits, outputSize}, armnn::DataType::Float32);
2625  std::vector<float> recurrentToForgetWeightsData = GenerateRandomData<float>(inputWeightsInfo2.GetNumElements());
2626  armnn::ConstTensor recurrentToForgetWeights(inputWeightsInfo2, recurrentToForgetWeightsData);
2627 
2628  std::vector<float> recurrentToCellWeightsData = GenerateRandomData<float>(inputWeightsInfo2.GetNumElements());
2629  armnn::ConstTensor recurrentToCellWeights(inputWeightsInfo2, recurrentToCellWeightsData);
2630 
2631  std::vector<float> recurrentToOutputWeightsData = GenerateRandomData<float>(inputWeightsInfo2.GetNumElements());
2632  armnn::ConstTensor recurrentToOutputWeights(inputWeightsInfo2, recurrentToOutputWeightsData);
2633 
2634  armnn::TensorInfo inputWeightsInfo3({numUnits}, armnn::DataType::Float32);
2635  std::vector<float> cellToForgetWeightsData = GenerateRandomData<float>(inputWeightsInfo3.GetNumElements());
2636  armnn::ConstTensor cellToForgetWeights(inputWeightsInfo3, cellToForgetWeightsData);
2637 
2638  std::vector<float> cellToOutputWeightsData = GenerateRandomData<float>(inputWeightsInfo3.GetNumElements());
2639  armnn::ConstTensor cellToOutputWeights(inputWeightsInfo3, cellToOutputWeightsData);
2640 
2641  std::vector<float> forgetGateBiasData(numUnits, 1.0f);
2642  armnn::ConstTensor forgetGateBias(inputWeightsInfo3, forgetGateBiasData);
2643 
2644  std::vector<float> cellBiasData(numUnits, 0.0f);
2645  armnn::ConstTensor cellBias(inputWeightsInfo3, cellBiasData);
2646 
2647  std::vector<float> outputGateBiasData(numUnits, 0.0f);
2648  armnn::ConstTensor outputGateBias(inputWeightsInfo3, outputGateBiasData);
2649 
2650  armnn::LstmInputParams params;
2651  params.m_InputToForgetWeights = &inputToForgetWeights;
2652  params.m_InputToCellWeights = &inputToCellWeights;
2653  params.m_InputToOutputWeights = &inputToOutputWeights;
2654  params.m_RecurrentToForgetWeights = &recurrentToForgetWeights;
2655  params.m_RecurrentToCellWeights = &recurrentToCellWeights;
2656  params.m_RecurrentToOutputWeights = &recurrentToOutputWeights;
2657  params.m_ForgetGateBias = &forgetGateBias;
2658  params.m_CellBias = &cellBias;
2659  params.m_OutputGateBias = &outputGateBias;
2660  params.m_CellToForgetWeights = &cellToForgetWeights;
2661  params.m_CellToOutputWeights = &cellToOutputWeights;
2662 
2663  armnn::INetworkPtr network = armnn::INetwork::Create();
2664  armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
2665  armnn::IConnectableLayer* const cellStateIn = network->AddInputLayer(1);
2666  armnn::IConnectableLayer* const outputStateIn = network->AddInputLayer(2);
2667  const std::string layerName("UnidirectionalSequenceLstm");
2668  armnn::IConnectableLayer* const unidirectionalSequenceLstmLayer =
2669  network->AddUnidirectionalSequenceLstmLayer(descriptor, params, layerName.c_str());
2670  armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
2671 
2672  // connect up
2673  armnn::TensorInfo inputTensorInfo({ timeSize, batchSize, inputSize }, armnn::DataType::Float32);
2674  armnn::TensorInfo cellStateTensorInfo({ batchSize, numUnits}, armnn::DataType::Float32);
2675  armnn::TensorInfo outputStateTensorInfo({ batchSize, outputSize }, armnn::DataType::Float32);
2676  armnn::TensorInfo outputTensorInfo({ timeSize, batchSize, outputSize }, armnn::DataType::Float32);
2677 
2678  inputLayer->GetOutputSlot(0).Connect(unidirectionalSequenceLstmLayer->GetInputSlot(0));
2679  inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
2680 
2681  outputStateIn->GetOutputSlot(0).Connect(unidirectionalSequenceLstmLayer->GetInputSlot(1));
2682  outputStateIn->GetOutputSlot(0).SetTensorInfo(outputStateTensorInfo);
2683 
2684  cellStateIn->GetOutputSlot(0).Connect(unidirectionalSequenceLstmLayer->GetInputSlot(2));
2685  cellStateIn->GetOutputSlot(0).SetTensorInfo(cellStateTensorInfo);
2686 
2687  unidirectionalSequenceLstmLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
2688  unidirectionalSequenceLstmLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
2689 
2690  armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
2691  CHECK(deserializedNetwork);
2692 
2693  VerifyLstmLayer<armnn::UnidirectionalSequenceLstmDescriptor> checker(
2694  layerName,
2695  {inputTensorInfo, outputStateTensorInfo, cellStateTensorInfo},
2696  {outputTensorInfo},
2697  descriptor,
2698  params);
2699  deserializedNetwork->ExecuteStrategy(checker);
2700 }
2701 
2702 }
IgnoreUnused.hpp
armnn::LstmDescriptor::m_ProjectionEnabled
bool m_ProjectionEnabled
Enable/disable the projection layer.
Definition: Descriptors.hpp:959
armnn::LstmInputParams::m_ProjectionWeights
const ConstTensor * m_ProjectionWeights
Definition: LstmParams.hpp:55
armnn::IConnectableLayer
Interface for a layer that is connectable to other layers via InputSlots and OutputSlots.
Definition: INetwork.hpp:61
armnn::LstmInputParams::m_CellBias
const ConstTensor * m_CellBias
Definition: LstmParams.hpp:53
armnn::QuantizedLstmInputParams::m_RecurrentToOutputWeights
const ConstTensor * m_RecurrentToOutputWeights
Definition: QuantizedLstmParams.hpp:41
armnn::LstmDescriptor::m_ClippingThresProj
float m_ClippingThresProj
Clipping threshold value for the projection.
Definition: Descriptors.hpp:953
DeserializeNetwork
armnn::INetworkPtr DeserializeNetwork(const std::string &serializerString)
Definition: SerializerTestUtils.cpp:147
armnn::LstmInputParams::m_CellToOutputWeights
const ConstTensor * m_CellToOutputWeights
Definition: LstmParams.hpp:50
armnn::QuantizedLstmInputParams::m_RecurrentToForgetWeights
const ConstTensor * m_RecurrentToForgetWeights
Definition: QuantizedLstmParams.hpp:39
armnn::QLstmDescriptor::m_PeepholeEnabled
bool m_PeepholeEnabled
Enable/disable peephole.
Definition: Descriptors.hpp:1211
armnn::QLstmDescriptor::m_HiddenStateScale
float m_HiddenStateScale
Hidden State quantization scale.
Definition: Descriptors.hpp:1227
armnn::LstmInputParams::m_CellToInputWeights
const ConstTensor * m_CellToInputWeights
Definition: LstmParams.hpp:48
QuantizedLstmParams.hpp
armnn::QLstmDescriptor::m_OutputIntermediateScale
float m_OutputIntermediateScale
Output intermediate quantization scale.
Definition: Descriptors.hpp:1223
armnn::LstmInputParams::m_InputGateBias
const ConstTensor * m_InputGateBias
Definition: LstmParams.hpp:51
IRuntime.hpp
LayerVerifierBaseWithDescriptor::VerifyDescriptor
void VerifyDescriptor(const Descriptor &descriptor)
Definition: SerializerTestUtils.hpp:83
armnn::LstmInputParams::m_RecurrentToCellWeights
const ConstTensor * m_RecurrentToCellWeights
Definition: LstmParams.hpp:46
LayerVerifierBaseWithDescriptor::ExecuteStrategy
void ExecuteStrategy(const armnn::IConnectableLayer *layer, const armnn::BaseDescriptor &descriptor, const std::vector< armnn::ConstTensor > &constants, const char *name, const armnn::LayerBindingId id=0) override
Definition: SerializerTestUtils.hpp:61
armnn::LstmInputParams::m_ForgetLayerNormWeights
const ConstTensor * m_ForgetLayerNormWeights
Definition: LstmParams.hpp:58
armnn::LstmInputParams::m_CellToForgetWeights
const ConstTensor * m_CellToForgetWeights
Definition: LstmParams.hpp:49
armnn::LstmDescriptor::m_TimeMajor
bool m_TimeMajor
Enable/disable time major.
Definition: Descriptors.hpp:963
armnn::IgnoreUnused
void IgnoreUnused(Ts &&...)
Definition: IgnoreUnused.hpp:14
LstmParams.hpp
armnn::LayerBindingId
int LayerBindingId
Type of identifiers for bindable layers (inputs, outputs).
Definition: Types.hpp:244
armnn::LstmInputParams::m_OutputGateBias
const ConstTensor * m_OutputGateBias
Definition: LstmParams.hpp:54
armnn::IOutputSlot::SetTensorInfo
virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0
armnn::BaseDescriptor
Base class for all descriptors.
Definition: Descriptors.hpp:22
armnn::LstmInputParams::m_InputLayerNormWeights
const ConstTensor * m_InputLayerNormWeights
Definition: LstmParams.hpp:57
armnn::QLstmDescriptor::m_LayerNormEnabled
bool m_LayerNormEnabled
Enable/disable layer normalization.
Definition: Descriptors.hpp:1215
armnn::LstmInputParams::m_RecurrentToOutputWeights
const ConstTensor * m_RecurrentToOutputWeights
Definition: LstmParams.hpp:47
armnn::LstmDescriptor
An LstmDescriptor for the LstmLayer.
Definition: Descriptors.hpp:923
armnn::LstmInputParams::m_ProjectionBias
const ConstTensor * m_ProjectionBias
Definition: LstmParams.hpp:56
LayerVerifierBase::VerifyNameAndConnections
void VerifyNameAndConnections(const armnn::IConnectableLayer *layer, const char *name)
Definition: SerializerTestUtils.cpp:40
armnn::QuantizedLstmInputParams::m_InputToForgetWeights
const ConstTensor * m_InputToForgetWeights
Definition: QuantizedLstmParams.hpp:34
armnn::QLstmDescriptor::m_ProjectionClip
float m_ProjectionClip
Clipping threshold value for the projection.
Definition: Descriptors.hpp:1207
armnn::ConstTensor
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
Definition: Tensor.hpp:327
armnn::QLstmDescriptor::m_InputIntermediateScale
float m_InputIntermediateScale
Input intermediate quantization scale.
Definition: Descriptors.hpp:1217
armnn::LstmDescriptor::m_PeepholeEnabled
bool m_PeepholeEnabled
Enable/disable peephole.
Definition: Descriptors.hpp:957
armnn::QLstmDescriptor
A QLstmDescriptor for the QLstmLayer.
Definition: Descriptors.hpp:1171
armnn::LstmDescriptor::m_ActivationFunc
uint32_t m_ActivationFunc
The activation function to use.
Definition: Descriptors.hpp:949
LayerVerifierBase::VerifyConstTensors
void VerifyConstTensors(const std::string &tensorName, const armnn::ConstTensor *expectedPtr, const armnn::ConstTensor *actualPtr)
Definition: SerializerTestUtils.cpp:72
armnn::IConnectableLayer::GetType
virtual LayerType GetType() const =0
Returns the armnn::LayerType of this layer.
armnn::QuantizedLstmInputParams::m_RecurrentToInputWeights
const ConstTensor * m_RecurrentToInputWeights
Definition: QuantizedLstmParams.hpp:38
armnn::LstmDescriptor::m_ClippingThresCell
float m_ClippingThresCell
Clipping threshold value for the cell state.
Definition: Descriptors.hpp:951
INetwork.hpp
armnn::QLstmDescriptor::m_ForgetIntermediateScale
float m_ForgetIntermediateScale
Forget intermediate quantization scale.
Definition: Descriptors.hpp:1219
armnn::LstmInputParams::m_CellLayerNormWeights
const ConstTensor * m_CellLayerNormWeights
Definition: LstmParams.hpp:59
armnn::LstmInputParams::m_ForgetGateBias
const ConstTensor * m_ForgetGateBias
Definition: LstmParams.hpp:52
armnn::LstmInputParams::m_InputToCellWeights
const ConstTensor * m_InputToCellWeights
Definition: LstmParams.hpp:42
armnn::LstmInputParams::m_InputToOutputWeights
const ConstTensor * m_InputToOutputWeights
Definition: LstmParams.hpp:43
armnn::QLstmDescriptor::m_CellClip
float m_CellClip
Clipping threshold value for the cell state.
Definition: Descriptors.hpp:1205
armnn::LstmDescriptor::m_CifgEnabled
bool m_CifgEnabled
Enable/disable cifg (coupled input & forget gate).
Definition: Descriptors.hpp:955
SerializerTestUtils.hpp
IDeserializer.hpp
armnn::LstmInputParams::m_RecurrentToForgetWeights
const ConstTensor * m_RecurrentToForgetWeights
Definition: LstmParams.hpp:45
armnn::Exception
Base class for all ArmNN exceptions so that users can filter to just those.
Definition: Exceptions.hpp:46
Descriptors.hpp
armnn::QLstmDescriptor::m_ProjectionEnabled
bool m_ProjectionEnabled
Enable/disable the projection layer.
Definition: Descriptors.hpp:1213
armnn::QuantizedLstmInputParams::m_RecurrentToCellWeights
const ConstTensor * m_RecurrentToCellWeights
Definition: QuantizedLstmParams.hpp:40
armnn::IConnectableLayer::GetInputSlot
virtual const IInputSlot & GetInputSlot(unsigned int index) const =0
Get a const input slot handle by slot index.
armnn::LstmInputParams::m_RecurrentToInputWeights
const ConstTensor * m_RecurrentToInputWeights
Definition: LstmParams.hpp:44
armnn::QuantizedLstmInputParams::m_InputToOutputWeights
const ConstTensor * m_InputToOutputWeights
Definition: QuantizedLstmParams.hpp:36
armnn::LstmDescriptor::m_LayerNormEnabled
bool m_LayerNormEnabled
Enable/disable layer normalization.
Definition: Descriptors.hpp:961
armnn::IConnectableLayer::GetOutputSlot
virtual const IOutputSlot & GetOutputSlot(unsigned int index) const =0
Get the const output slot handle by slot index.
armnn::IConnectableLayer::GetName
virtual const char * GetName() const =0
Returns the name of the layer.
armnn::INetworkPtr
std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr
Definition: INetwork.hpp:172
armnn::IOutputSlot::Connect
virtual int Connect(IInputSlot &destination)=0
SerializeNetwork
std::string SerializeNetwork(const armnn::INetwork &network)
Definition: SerializerTestUtils.cpp:153
armnn::LstmInputParams::m_OutputLayerNormWeights
const ConstTensor * m_OutputLayerNormWeights
Definition: LstmParams.hpp:60
armnn::QLstmDescriptor::m_CellIntermediateScale
float m_CellIntermediateScale
Cell intermediate quantization scale.
Definition: Descriptors.hpp:1221
armnn::INetwork::Create
static INetworkPtr Create(NetworkOptions networkOptions={})
Definition: Network.cpp:530
armnn::QLstmDescriptor::m_CifgEnabled
bool m_CifgEnabled
Enable/disable CIFG (coupled input & forget gate).
Definition: Descriptors.hpp:1209
armnn::LstmInputParams::m_InputToForgetWeights
const ConstTensor * m_InputToForgetWeights
Definition: LstmParams.hpp:41
armnn::QLstmDescriptor::m_HiddenStateZeroPoint
int32_t m_HiddenStateZeroPoint
Hidden State zero point.
Definition: Descriptors.hpp:1225
TEST_SUITE
TEST_SUITE("SerializerTests")
Definition: LstmSerializationTests.cpp:21
armnn::LstmInputParams::m_InputToInputWeights
const ConstTensor * m_InputToInputWeights
Definition: LstmParams.hpp:40