ArmNN
 21.02
Functions
LstmSerializationTests.cpp File Reference
#include "../Serializer.hpp"
#include "SerializerTestUtils.hpp"
#include <armnn/Descriptors.hpp>
#include <armnn/INetwork.hpp>
#include <armnn/IRuntime.hpp>
#include <armnnDeserializer/IDeserializer.hpp>
#include <armnn/utility/IgnoreUnused.hpp>
#include <armnn/LstmParams.hpp>
#include <armnn/QuantizedLstmParams.hpp>
#include <boost/test/unit_test.hpp>
#include <fmt/format.h>

Go to the source code of this file.

Functions

template<typename Descriptor >
armnn::LstmInputParams ConstantVector2LstmInputParams (const std::vector< armnn::ConstTensor > &constants, Descriptor &descriptor)
 
 BOOST_AUTO_TEST_CASE (SerializeDeserializeLstmCifgPeepholeNoProjection)
 
 BOOST_AUTO_TEST_CASE (SerializeDeserializeLstmNoCifgWithPeepholeAndProjection)
 
 BOOST_AUTO_TEST_CASE (SerializeDeserializeLstmNoCifgWithPeepholeWithProjectionWithLayerNorm)
 
 BOOST_AUTO_TEST_CASE (EnsureLstmLayersBackwardCompatibility)
 
armnn::QuantizedLstmInputParams ConstantsVector2QuantizedLstmInputParams (const std::vector< armnn::ConstTensor > &constants)
 
 BOOST_AUTO_TEST_CASE (SerializeDeserializeQuantizedLstm)
 
 BOOST_AUTO_TEST_CASE (SerializeDeserializeQLstmBasic)
 
 BOOST_AUTO_TEST_CASE (SerializeDeserializeQLstmCifgLayerNorm)
 
 BOOST_AUTO_TEST_CASE (SerializeDeserializeQLstmAdvanced)
 

Function Documentation

◆ BOOST_AUTO_TEST_CASE() [1/8]

BOOST_AUTO_TEST_CASE ( SerializeDeserializeLstmCifgPeepholeNoProjection  )

Definition at line 178 of file LstmSerializationTests.cpp.

References IOutputSlot::Connect(), INetwork::Create(), DeserializeNetwork(), armnn::Float32, IConnectableLayer::GetInputSlot(), IConnectableLayer::GetOutputSlot(), LstmDescriptor::m_ActivationFunc, LstmInputParams::m_CellBias, LstmInputParams::m_CellToForgetWeights, LstmInputParams::m_CellToOutputWeights, LstmDescriptor::m_CifgEnabled, LstmDescriptor::m_ClippingThresCell, LstmDescriptor::m_ClippingThresProj, LstmInputParams::m_ForgetGateBias, LstmInputParams::m_InputToCellWeights, LstmInputParams::m_InputToForgetWeights, LstmInputParams::m_InputToOutputWeights, LstmInputParams::m_OutputGateBias, LstmDescriptor::m_PeepholeEnabled, LstmDescriptor::m_ProjectionEnabled, LstmInputParams::m_RecurrentToCellWeights, LstmInputParams::m_RecurrentToForgetWeights, LstmInputParams::m_RecurrentToOutputWeights, SerializeNetwork(), and IOutputSlot::SetTensorInfo().

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  BOOST_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 }
armnn::LstmDescriptor::m_ProjectionEnabled
bool m_ProjectionEnabled
Enable/disable the projection layer.
Definition: Descriptors.hpp:945
armnn::IConnectableLayer
Interface for a layer that is connectable to other layers via InputSlots and OutputSlots.
Definition: INetwork.hpp:62
armnn::LstmInputParams::m_CellBias
const ConstTensor * m_CellBias
Definition: LstmParams.hpp:53
armnn::LstmDescriptor::m_ClippingThresProj
float m_ClippingThresProj
Clipping threshold value for the projection.
Definition: Descriptors.hpp:939
DeserializeNetwork
armnn::INetworkPtr DeserializeNetwork(const std::string &serializerString)
Definition: SerializerTestUtils.cpp:146
armnn::LstmInputParams::m_CellToOutputWeights
const ConstTensor * m_CellToOutputWeights
Definition: LstmParams.hpp:50
armnn::LstmInputParams::m_RecurrentToCellWeights
const ConstTensor * m_RecurrentToCellWeights
Definition: LstmParams.hpp:46
armnn::LstmInputParams::m_CellToForgetWeights
const ConstTensor * m_CellToForgetWeights
Definition: LstmParams.hpp:49
armnn::LstmInputParams::m_OutputGateBias
const ConstTensor * m_OutputGateBias
Definition: LstmParams.hpp:54
armnn::IOutputSlot::SetTensorInfo
virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0
armnn::LstmInputParams::m_RecurrentToOutputWeights
const ConstTensor * m_RecurrentToOutputWeights
Definition: LstmParams.hpp:47
armnn::LstmDescriptor
An LstmDescriptor for the LstmLayer.
Definition: Descriptors.hpp:911
armnn::ConstTensor
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
Definition: Tensor.hpp:314
armnn::LstmDescriptor::m_PeepholeEnabled
bool m_PeepholeEnabled
Enable/disable peephole.
Definition: Descriptors.hpp:943
armnn::LstmDescriptor::m_ActivationFunc
uint32_t m_ActivationFunc
The activation function to use.
Definition: Descriptors.hpp:935
armnn::LstmDescriptor::m_ClippingThresCell
float m_ClippingThresCell
Clipping threshold value for the cell state.
Definition: Descriptors.hpp:937
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::LstmDescriptor::m_CifgEnabled
bool m_CifgEnabled
Enable/disable cifg (coupled input & forget gate).
Definition: Descriptors.hpp:941
armnn::LstmInputParams::m_RecurrentToForgetWeights
const ConstTensor * m_RecurrentToForgetWeights
Definition: LstmParams.hpp:45
armnn::IConnectableLayer::GetInputSlot
virtual const IInputSlot & GetInputSlot(unsigned int index) const =0
Get a const input slot handle by slot index.
armnn::IConnectableLayer::GetOutputSlot
virtual const IOutputSlot & GetOutputSlot(unsigned int index) const =0
Get the const output slot handle by slot index.
armnn::INetworkPtr
std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr
Definition: INetwork.hpp:173
armnn::IOutputSlot::Connect
virtual int Connect(IInputSlot &destination)=0
SerializeNetwork
std::string SerializeNetwork(const armnn::INetwork &network)
Definition: SerializerTestUtils.cpp:152
armnn::INetwork::Create
static INetworkPtr Create(NetworkOptions networkOptions={})
Definition: Network.cpp:510
armnn::LstmInputParams::m_InputToForgetWeights
const ConstTensor * m_InputToForgetWeights
Definition: LstmParams.hpp:41

◆ BOOST_AUTO_TEST_CASE() [2/8]

BOOST_AUTO_TEST_CASE ( SerializeDeserializeLstmNoCifgWithPeepholeAndProjection  )

Definition at line 292 of file LstmSerializationTests.cpp.

References IOutputSlot::Connect(), INetwork::Create(), DeserializeNetwork(), armnn::Float32, IConnectableLayer::GetInputSlot(), IConnectableLayer::GetOutputSlot(), LstmDescriptor::m_ActivationFunc, LstmInputParams::m_CellBias, LstmInputParams::m_CellToForgetWeights, LstmInputParams::m_CellToInputWeights, LstmInputParams::m_CellToOutputWeights, LstmDescriptor::m_CifgEnabled, LstmDescriptor::m_ClippingThresCell, LstmDescriptor::m_ClippingThresProj, LstmInputParams::m_ForgetGateBias, LstmInputParams::m_InputGateBias, LstmInputParams::m_InputToCellWeights, LstmInputParams::m_InputToForgetWeights, LstmInputParams::m_InputToInputWeights, LstmInputParams::m_InputToOutputWeights, LstmInputParams::m_OutputGateBias, LstmDescriptor::m_PeepholeEnabled, LstmInputParams::m_ProjectionBias, LstmDescriptor::m_ProjectionEnabled, LstmInputParams::m_ProjectionWeights, LstmInputParams::m_RecurrentToCellWeights, LstmInputParams::m_RecurrentToForgetWeights, LstmInputParams::m_RecurrentToInputWeights, LstmInputParams::m_RecurrentToOutputWeights, SerializeNetwork(), and IOutputSlot::SetTensorInfo().

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  BOOST_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 }
armnn::LstmDescriptor::m_ProjectionEnabled
bool m_ProjectionEnabled
Enable/disable the projection layer.
Definition: Descriptors.hpp:945
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:62
armnn::LstmInputParams::m_CellBias
const ConstTensor * m_CellBias
Definition: LstmParams.hpp:53
armnn::LstmDescriptor::m_ClippingThresProj
float m_ClippingThresProj
Clipping threshold value for the projection.
Definition: Descriptors.hpp:939
DeserializeNetwork
armnn::INetworkPtr DeserializeNetwork(const std::string &serializerString)
Definition: SerializerTestUtils.cpp:146
armnn::LstmInputParams::m_CellToOutputWeights
const ConstTensor * m_CellToOutputWeights
Definition: LstmParams.hpp:50
armnn::LstmInputParams::m_CellToInputWeights
const ConstTensor * m_CellToInputWeights
Definition: LstmParams.hpp:48
armnn::LstmInputParams::m_InputGateBias
const ConstTensor * m_InputGateBias
Definition: LstmParams.hpp:51
armnn::LstmInputParams::m_RecurrentToCellWeights
const ConstTensor * m_RecurrentToCellWeights
Definition: LstmParams.hpp:46
armnn::LstmInputParams::m_CellToForgetWeights
const ConstTensor * m_CellToForgetWeights
Definition: LstmParams.hpp:49
armnn::LstmInputParams::m_OutputGateBias
const ConstTensor * m_OutputGateBias
Definition: LstmParams.hpp:54
armnn::IOutputSlot::SetTensorInfo
virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0
armnn::LstmInputParams::m_RecurrentToOutputWeights
const ConstTensor * m_RecurrentToOutputWeights
Definition: LstmParams.hpp:47
armnn::LstmDescriptor
An LstmDescriptor for the LstmLayer.
Definition: Descriptors.hpp:911
armnn::LstmInputParams::m_ProjectionBias
const ConstTensor * m_ProjectionBias
Definition: LstmParams.hpp:56
armnn::ConstTensor
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
Definition: Tensor.hpp:314
armnn::LstmDescriptor::m_PeepholeEnabled
bool m_PeepholeEnabled
Enable/disable peephole.
Definition: Descriptors.hpp:943
armnn::LstmDescriptor::m_ActivationFunc
uint32_t m_ActivationFunc
The activation function to use.
Definition: Descriptors.hpp:935
armnn::LstmDescriptor::m_ClippingThresCell
float m_ClippingThresCell
Clipping threshold value for the cell state.
Definition: Descriptors.hpp:937
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::LstmDescriptor::m_CifgEnabled
bool m_CifgEnabled
Enable/disable cifg (coupled input & forget gate).
Definition: Descriptors.hpp:941
armnn::LstmInputParams::m_RecurrentToForgetWeights
const ConstTensor * m_RecurrentToForgetWeights
Definition: LstmParams.hpp:45
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::IConnectableLayer::GetOutputSlot
virtual const IOutputSlot & GetOutputSlot(unsigned int index) const =0
Get the const output slot handle by slot index.
armnn::INetworkPtr
std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr
Definition: INetwork.hpp:173
armnn::IOutputSlot::Connect
virtual int Connect(IInputSlot &destination)=0
SerializeNetwork
std::string SerializeNetwork(const armnn::INetwork &network)
Definition: SerializerTestUtils.cpp:152
armnn::INetwork::Create
static INetworkPtr Create(NetworkOptions networkOptions={})
Definition: Network.cpp:510
armnn::LstmInputParams::m_InputToForgetWeights
const ConstTensor * m_InputToForgetWeights
Definition: LstmParams.hpp:41
armnn::LstmInputParams::m_InputToInputWeights
const ConstTensor * m_InputToInputWeights
Definition: LstmParams.hpp:40

◆ BOOST_AUTO_TEST_CASE() [3/8]

BOOST_AUTO_TEST_CASE ( SerializeDeserializeLstmNoCifgWithPeepholeWithProjectionWithLayerNorm  )

Definition at line 438 of file LstmSerializationTests.cpp.

References IOutputSlot::Connect(), INetwork::Create(), DeserializeNetwork(), armnn::Float32, IConnectableLayer::GetInputSlot(), IConnectableLayer::GetOutputSlot(), LstmDescriptor::m_ActivationFunc, LstmInputParams::m_CellBias, LstmInputParams::m_CellLayerNormWeights, LstmInputParams::m_CellToForgetWeights, LstmInputParams::m_CellToInputWeights, LstmInputParams::m_CellToOutputWeights, LstmDescriptor::m_CifgEnabled, LstmDescriptor::m_ClippingThresCell, LstmDescriptor::m_ClippingThresProj, LstmInputParams::m_ForgetGateBias, LstmInputParams::m_ForgetLayerNormWeights, LstmInputParams::m_InputGateBias, LstmInputParams::m_InputLayerNormWeights, LstmInputParams::m_InputToCellWeights, LstmInputParams::m_InputToForgetWeights, LstmInputParams::m_InputToInputWeights, LstmInputParams::m_InputToOutputWeights, LstmDescriptor::m_LayerNormEnabled, LstmInputParams::m_OutputGateBias, LstmInputParams::m_OutputLayerNormWeights, LstmDescriptor::m_PeepholeEnabled, LstmInputParams::m_ProjectionBias, LstmDescriptor::m_ProjectionEnabled, LstmInputParams::m_ProjectionWeights, LstmInputParams::m_RecurrentToCellWeights, LstmInputParams::m_RecurrentToForgetWeights, LstmInputParams::m_RecurrentToInputWeights, LstmInputParams::m_RecurrentToOutputWeights, SerializeNetwork(), and IOutputSlot::SetTensorInfo().

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  BOOST_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 }
armnn::LstmDescriptor::m_ProjectionEnabled
bool m_ProjectionEnabled
Enable/disable the projection layer.
Definition: Descriptors.hpp:945
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:62
armnn::LstmInputParams::m_CellBias
const ConstTensor * m_CellBias
Definition: LstmParams.hpp:53
armnn::LstmDescriptor::m_ClippingThresProj
float m_ClippingThresProj
Clipping threshold value for the projection.
Definition: Descriptors.hpp:939
DeserializeNetwork
armnn::INetworkPtr DeserializeNetwork(const std::string &serializerString)
Definition: SerializerTestUtils.cpp:146
armnn::LstmInputParams::m_CellToOutputWeights
const ConstTensor * m_CellToOutputWeights
Definition: LstmParams.hpp:50
armnn::LstmInputParams::m_CellToInputWeights
const ConstTensor * m_CellToInputWeights
Definition: LstmParams.hpp:48
armnn::LstmInputParams::m_InputGateBias
const ConstTensor * m_InputGateBias
Definition: LstmParams.hpp:51
armnn::LstmInputParams::m_RecurrentToCellWeights
const ConstTensor * m_RecurrentToCellWeights
Definition: LstmParams.hpp:46
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::LstmInputParams::m_OutputGateBias
const ConstTensor * m_OutputGateBias
Definition: LstmParams.hpp:54
armnn::IOutputSlot::SetTensorInfo
virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0
armnn::LstmInputParams::m_InputLayerNormWeights
const ConstTensor * m_InputLayerNormWeights
Definition: LstmParams.hpp:57
armnn::LstmInputParams::m_RecurrentToOutputWeights
const ConstTensor * m_RecurrentToOutputWeights
Definition: LstmParams.hpp:47
armnn::LstmDescriptor
An LstmDescriptor for the LstmLayer.
Definition: Descriptors.hpp:911
armnn::LstmInputParams::m_ProjectionBias
const ConstTensor * m_ProjectionBias
Definition: LstmParams.hpp:56
armnn::ConstTensor
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
Definition: Tensor.hpp:314
armnn::LstmDescriptor::m_PeepholeEnabled
bool m_PeepholeEnabled
Enable/disable peephole.
Definition: Descriptors.hpp:943
armnn::LstmDescriptor::m_ActivationFunc
uint32_t m_ActivationFunc
The activation function to use.
Definition: Descriptors.hpp:935
armnn::LstmDescriptor::m_ClippingThresCell
float m_ClippingThresCell
Clipping threshold value for the cell state.
Definition: Descriptors.hpp:937
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::LstmDescriptor::m_CifgEnabled
bool m_CifgEnabled
Enable/disable cifg (coupled input & forget gate).
Definition: Descriptors.hpp:941
armnn::LstmInputParams::m_RecurrentToForgetWeights
const ConstTensor * m_RecurrentToForgetWeights
Definition: LstmParams.hpp:45
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::LstmDescriptor::m_LayerNormEnabled
bool m_LayerNormEnabled
Enable/disable layer normalization.
Definition: Descriptors.hpp:947
armnn::IConnectableLayer::GetOutputSlot
virtual const IOutputSlot & GetOutputSlot(unsigned int index) const =0
Get the const output slot handle by slot index.
armnn::INetworkPtr
std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr
Definition: INetwork.hpp:173
armnn::IOutputSlot::Connect
virtual int Connect(IInputSlot &destination)=0
SerializeNetwork
std::string SerializeNetwork(const armnn::INetwork &network)
Definition: SerializerTestUtils.cpp:152
armnn::LstmInputParams::m_OutputLayerNormWeights
const ConstTensor * m_OutputLayerNormWeights
Definition: LstmParams.hpp:60
armnn::INetwork::Create
static INetworkPtr Create(NetworkOptions networkOptions={})
Definition: Network.cpp:510
armnn::LstmInputParams::m_InputToForgetWeights
const ConstTensor * m_InputToForgetWeights
Definition: LstmParams.hpp:41
armnn::LstmInputParams::m_InputToInputWeights
const ConstTensor * m_InputToInputWeights
Definition: LstmParams.hpp:40

◆ BOOST_AUTO_TEST_CASE() [4/8]

BOOST_AUTO_TEST_CASE ( EnsureLstmLayersBackwardCompatibility  )

Definition at line 603 of file LstmSerializationTests.cpp.

References DeserializeNetwork(), armnn::Float32, LstmDescriptor::m_ActivationFunc, LstmInputParams::m_CellBias, LstmInputParams::m_CellToForgetWeights, LstmInputParams::m_CellToInputWeights, LstmInputParams::m_CellToOutputWeights, LstmDescriptor::m_CifgEnabled, LstmDescriptor::m_ClippingThresCell, LstmDescriptor::m_ClippingThresProj, LstmInputParams::m_ForgetGateBias, LstmInputParams::m_InputGateBias, LstmInputParams::m_InputToCellWeights, LstmInputParams::m_InputToForgetWeights, LstmInputParams::m_InputToInputWeights, LstmInputParams::m_InputToOutputWeights, LstmInputParams::m_OutputGateBias, LstmDescriptor::m_PeepholeEnabled, LstmInputParams::m_ProjectionBias, LstmDescriptor::m_ProjectionEnabled, LstmInputParams::m_ProjectionWeights, LstmInputParams::m_RecurrentToCellWeights, LstmInputParams::m_RecurrentToForgetWeights, LstmInputParams::m_RecurrentToInputWeights, and LstmInputParams::m_RecurrentToOutputWeights.

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,
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729  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
730  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
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732  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
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735  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
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969  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
970  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
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973  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
974  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
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976  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
977  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
978  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
979  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
980  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
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984  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
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987  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
988  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
989  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
990  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
991  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
992  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
993  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
994  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
995  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
996  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
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,
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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,
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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,
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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,
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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,
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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,
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1105  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
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1111  0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
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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,
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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,
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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,
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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  BOOST_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 }
armnn::LstmDescriptor::m_ProjectionEnabled
bool m_ProjectionEnabled
Enable/disable the projection layer.
Definition: Descriptors.hpp:945
armnn::LstmInputParams::m_ProjectionWeights
const ConstTensor * m_ProjectionWeights
Definition: LstmParams.hpp:55
armnn::LstmInputParams::m_CellBias
const ConstTensor * m_CellBias
Definition: LstmParams.hpp:53
armnn::LstmDescriptor::m_ClippingThresProj
float m_ClippingThresProj
Clipping threshold value for the projection.
Definition: Descriptors.hpp:939
DeserializeNetwork
armnn::INetworkPtr DeserializeNetwork(const std::string &serializerString)
Definition: SerializerTestUtils.cpp:146
armnn::LstmInputParams::m_CellToOutputWeights
const ConstTensor * m_CellToOutputWeights
Definition: LstmParams.hpp:50
armnn::LstmInputParams::m_CellToInputWeights
const ConstTensor * m_CellToInputWeights
Definition: LstmParams.hpp:48
armnn::LstmInputParams::m_InputGateBias
const ConstTensor * m_InputGateBias
Definition: LstmParams.hpp:51
armnn::LstmInputParams::m_RecurrentToCellWeights
const ConstTensor * m_RecurrentToCellWeights
Definition: LstmParams.hpp:46
armnn::LstmInputParams::m_CellToForgetWeights
const ConstTensor * m_CellToForgetWeights
Definition: LstmParams.hpp:49
armnn::LstmInputParams::m_OutputGateBias
const ConstTensor * m_OutputGateBias
Definition: LstmParams.hpp:54
armnn::LstmInputParams::m_RecurrentToOutputWeights
const ConstTensor * m_RecurrentToOutputWeights
Definition: LstmParams.hpp:47
armnn::LstmDescriptor
An LstmDescriptor for the LstmLayer.
Definition: Descriptors.hpp:911
armnn::LstmInputParams::m_ProjectionBias
const ConstTensor * m_ProjectionBias
Definition: LstmParams.hpp:56
armnn::ConstTensor
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
Definition: Tensor.hpp:314
armnn::LstmDescriptor::m_PeepholeEnabled
bool m_PeepholeEnabled
Enable/disable peephole.
Definition: Descriptors.hpp:943
armnn::LstmDescriptor::m_ActivationFunc
uint32_t m_ActivationFunc
The activation function to use.
Definition: Descriptors.hpp:935
armnn::LstmDescriptor::m_ClippingThresCell
float m_ClippingThresCell
Clipping threshold value for the cell state.
Definition: Descriptors.hpp:937
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::LstmDescriptor::m_CifgEnabled
bool m_CifgEnabled
Enable/disable cifg (coupled input & forget gate).
Definition: Descriptors.hpp:941
armnn::LstmInputParams::m_RecurrentToForgetWeights
const ConstTensor * m_RecurrentToForgetWeights
Definition: LstmParams.hpp:45
armnn::LstmInputParams::m_RecurrentToInputWeights
const ConstTensor * m_RecurrentToInputWeights
Definition: LstmParams.hpp:44
armnn::INetworkPtr
std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr
Definition: INetwork.hpp:173
armnn::LstmInputParams::m_InputToForgetWeights
const ConstTensor * m_InputToForgetWeights
Definition: LstmParams.hpp:41
armnn::LstmInputParams::m_InputToInputWeights
const ConstTensor * m_InputToInputWeights
Definition: LstmParams.hpp:40

◆ BOOST_AUTO_TEST_CASE() [5/8]

BOOST_AUTO_TEST_CASE ( SerializeDeserializeQuantizedLstm  )

Definition at line 1431 of file LstmSerializationTests.cpp.

References IOutputSlot::Connect(), INetwork::Create(), DeserializeNetwork(), IConnectableLayer::GetInputSlot(), IConnectableLayer::GetOutputSlot(), QuantizedLstmInputParams::m_CellBias, QuantizedLstmInputParams::m_ForgetGateBias, QuantizedLstmInputParams::m_InputGateBias, QuantizedLstmInputParams::m_InputToCellWeights, QuantizedLstmInputParams::m_InputToForgetWeights, QuantizedLstmInputParams::m_InputToInputWeights, QuantizedLstmInputParams::m_InputToOutputWeights, QuantizedLstmInputParams::m_OutputGateBias, QuantizedLstmInputParams::m_RecurrentToCellWeights, QuantizedLstmInputParams::m_RecurrentToForgetWeights, QuantizedLstmInputParams::m_RecurrentToInputWeights, QuantizedLstmInputParams::m_RecurrentToOutputWeights, armnn::QAsymmU8, armnn::QSymmS16, SerializeNetwork(), IOutputSlot::SetTensorInfo(), and armnn::Signed32.

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  BOOST_CHECK(deserializedNetwork);
1604 
1605  VerifyQuantizedLstmLayer checker(layerName,
1606  {inputTensorInfo, cellStateTensorInfo, outputStateTensorInfo},
1607  {cellStateTensorInfo, outputStateTensorInfo},
1608  params);
1609 
1610  deserializedNetwork->ExecuteStrategy(checker);
1611 }
armnn::IConnectableLayer
Interface for a layer that is connectable to other layers via InputSlots and OutputSlots.
Definition: INetwork.hpp:62
armnn::QuantizedLstmInputParams::m_RecurrentToOutputWeights
const ConstTensor * m_RecurrentToOutputWeights
Definition: QuantizedLstmParams.hpp:41
DeserializeNetwork
armnn::INetworkPtr DeserializeNetwork(const std::string &serializerString)
Definition: SerializerTestUtils.cpp:146
armnn::QuantizedLstmInputParams::m_RecurrentToForgetWeights
const ConstTensor * m_RecurrentToForgetWeights
Definition: QuantizedLstmParams.hpp:39
armnn::IOutputSlot::SetTensorInfo
virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0
armnn::QuantizedLstmInputParams::m_InputToForgetWeights
const ConstTensor * m_InputToForgetWeights
Definition: QuantizedLstmParams.hpp:34
armnn::ConstTensor
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
Definition: Tensor.hpp:314
armnn::QuantizedLstmInputParams::m_RecurrentToInputWeights
const ConstTensor * m_RecurrentToInputWeights
Definition: QuantizedLstmParams.hpp:38
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::QuantizedLstmInputParams::m_InputToOutputWeights
const ConstTensor * m_InputToOutputWeights
Definition: QuantizedLstmParams.hpp:36
armnn::IConnectableLayer::GetOutputSlot
virtual const IOutputSlot & GetOutputSlot(unsigned int index) const =0
Get the const output slot handle by slot index.
armnn::INetworkPtr
std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr
Definition: INetwork.hpp:173
armnn::IOutputSlot::Connect
virtual int Connect(IInputSlot &destination)=0
SerializeNetwork
std::string SerializeNetwork(const armnn::INetwork &network)
Definition: SerializerTestUtils.cpp:152
armnn::INetwork::Create
static INetworkPtr Create(NetworkOptions networkOptions={})
Definition: Network.cpp:510

◆ BOOST_AUTO_TEST_CASE() [6/8]

BOOST_AUTO_TEST_CASE ( SerializeDeserializeQLstmBasic  )

Definition at line 1613 of file LstmSerializationTests.cpp.

References IOutputSlot::Connect(), INetwork::Create(), DeserializeNetwork(), IConnectableLayer::GetInputSlot(), IConnectableLayer::GetOutputSlot(), LstmInputParams::m_CellBias, QLstmDescriptor::m_CellClip, QLstmDescriptor::m_CellIntermediateScale, QLstmDescriptor::m_CifgEnabled, LstmInputParams::m_ForgetGateBias, QLstmDescriptor::m_ForgetIntermediateScale, QLstmDescriptor::m_HiddenStateScale, QLstmDescriptor::m_HiddenStateZeroPoint, QLstmDescriptor::m_InputIntermediateScale, LstmInputParams::m_InputToCellWeights, LstmInputParams::m_InputToForgetWeights, LstmInputParams::m_InputToOutputWeights, QLstmDescriptor::m_LayerNormEnabled, LstmInputParams::m_OutputGateBias, QLstmDescriptor::m_OutputIntermediateScale, QLstmDescriptor::m_PeepholeEnabled, QLstmDescriptor::m_ProjectionClip, QLstmDescriptor::m_ProjectionEnabled, LstmInputParams::m_RecurrentToCellWeights, LstmInputParams::m_RecurrentToForgetWeights, LstmInputParams::m_RecurrentToOutputWeights, armnn::QAsymmS8, armnn::QSymmS16, armnn::QSymmS8, SerializeNetwork(), IOutputSlot::SetTensorInfo(), and armnn::Signed32.

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  BOOST_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 }
armnn::IConnectableLayer
Interface for a layer that is connectable to other layers via InputSlots and OutputSlots.
Definition: INetwork.hpp:62
armnn::LstmInputParams::m_CellBias
const ConstTensor * m_CellBias
Definition: LstmParams.hpp:53
DeserializeNetwork
armnn::INetworkPtr DeserializeNetwork(const std::string &serializerString)
Definition: SerializerTestUtils.cpp:146
armnn::QLstmDescriptor::m_PeepholeEnabled
bool m_PeepholeEnabled
Enable/disable peephole.
Definition: Descriptors.hpp:1193
armnn::QLstmDescriptor::m_HiddenStateScale
float m_HiddenStateScale
Hidden State quantization scale.
Definition: Descriptors.hpp:1209
armnn::QLstmDescriptor::m_OutputIntermediateScale
float m_OutputIntermediateScale
Output intermediate quantization scale.
Definition: Descriptors.hpp:1205
armnn::LstmInputParams::m_RecurrentToCellWeights
const ConstTensor * m_RecurrentToCellWeights
Definition: LstmParams.hpp:46
armnn::LstmInputParams::m_OutputGateBias
const ConstTensor * m_OutputGateBias
Definition: LstmParams.hpp:54
armnn::IOutputSlot::SetTensorInfo
virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0
armnn::QLstmDescriptor::m_LayerNormEnabled
bool m_LayerNormEnabled
Enable/disable layer normalization.
Definition: Descriptors.hpp:1197
armnn::LstmInputParams::m_RecurrentToOutputWeights
const ConstTensor * m_RecurrentToOutputWeights
Definition: LstmParams.hpp:47
armnn::QLstmDescriptor::m_ProjectionClip
float m_ProjectionClip
Clipping threshold value for the projection.
Definition: Descriptors.hpp:1189
armnn::ConstTensor
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
Definition: Tensor.hpp:314
armnn::QLstmDescriptor::m_InputIntermediateScale
float m_InputIntermediateScale
Input intermediate quantization scale.
Definition: Descriptors.hpp:1199
armnn::QLstmDescriptor
A QLstmDescriptor for the QLstmLayer.
Definition: Descriptors.hpp:1153
armnn::QLstmDescriptor::m_ForgetIntermediateScale
float m_ForgetIntermediateScale
Forget intermediate quantization scale.
Definition: Descriptors.hpp:1201
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:1187
armnn::LstmInputParams::m_RecurrentToForgetWeights
const ConstTensor * m_RecurrentToForgetWeights
Definition: LstmParams.hpp:45
armnn::QLstmDescriptor::m_ProjectionEnabled
bool m_ProjectionEnabled
Enable/disable the projection layer.
Definition: Descriptors.hpp:1195
armnn::IConnectableLayer::GetInputSlot
virtual const IInputSlot & GetInputSlot(unsigned int index) const =0
Get a const input slot handle by slot index.
armnn::IConnectableLayer::GetOutputSlot
virtual const IOutputSlot & GetOutputSlot(unsigned int index) const =0
Get the const output slot handle by slot index.
armnn::INetworkPtr
std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr
Definition: INetwork.hpp:173
armnn::IOutputSlot::Connect
virtual int Connect(IInputSlot &destination)=0
SerializeNetwork
std::string SerializeNetwork(const armnn::INetwork &network)
Definition: SerializerTestUtils.cpp:152
armnn::QLstmDescriptor::m_CellIntermediateScale
float m_CellIntermediateScale
Cell intermediate quantization scale.
Definition: Descriptors.hpp:1203
armnn::INetwork::Create
static INetworkPtr Create(NetworkOptions networkOptions={})
Definition: Network.cpp:510
armnn::QLstmDescriptor::m_CifgEnabled
bool m_CifgEnabled
Enable/disable CIFG (coupled input & forget gate).
Definition: Descriptors.hpp:1191
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:1207

◆ BOOST_AUTO_TEST_CASE() [7/8]

BOOST_AUTO_TEST_CASE ( SerializeDeserializeQLstmCifgLayerNorm  )

Definition at line 1770 of file LstmSerializationTests.cpp.

References IOutputSlot::Connect(), INetwork::Create(), DeserializeNetwork(), IConnectableLayer::GetInputSlot(), IConnectableLayer::GetOutputSlot(), LstmInputParams::m_CellBias, QLstmDescriptor::m_CellClip, QLstmDescriptor::m_CellIntermediateScale, LstmInputParams::m_CellLayerNormWeights, QLstmDescriptor::m_CifgEnabled, LstmInputParams::m_ForgetGateBias, QLstmDescriptor::m_ForgetIntermediateScale, LstmInputParams::m_ForgetLayerNormWeights, QLstmDescriptor::m_HiddenStateScale, QLstmDescriptor::m_HiddenStateZeroPoint, QLstmDescriptor::m_InputIntermediateScale, LstmInputParams::m_InputToCellWeights, LstmInputParams::m_InputToForgetWeights, LstmInputParams::m_InputToOutputWeights, QLstmDescriptor::m_LayerNormEnabled, LstmInputParams::m_OutputGateBias, QLstmDescriptor::m_OutputIntermediateScale, LstmInputParams::m_OutputLayerNormWeights, QLstmDescriptor::m_PeepholeEnabled, QLstmDescriptor::m_ProjectionClip, QLstmDescriptor::m_ProjectionEnabled, LstmInputParams::m_RecurrentToCellWeights, LstmInputParams::m_RecurrentToForgetWeights, LstmInputParams::m_RecurrentToOutputWeights, armnn::QAsymmS8, armnn::QSymmS16, armnn::QSymmS8, SerializeNetwork(), IOutputSlot::SetTensorInfo(), and armnn::Signed32.

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  BOOST_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 }
armnn::IConnectableLayer
Interface for a layer that is connectable to other layers via InputSlots and OutputSlots.
Definition: INetwork.hpp:62
armnn::LstmInputParams::m_CellBias
const ConstTensor * m_CellBias
Definition: LstmParams.hpp:53
DeserializeNetwork
armnn::INetworkPtr DeserializeNetwork(const std::string &serializerString)
Definition: SerializerTestUtils.cpp:146
armnn::QLstmDescriptor::m_PeepholeEnabled
bool m_PeepholeEnabled
Enable/disable peephole.
Definition: Descriptors.hpp:1193
armnn::QLstmDescriptor::m_HiddenStateScale
float m_HiddenStateScale
Hidden State quantization scale.
Definition: Descriptors.hpp:1209
armnn::QLstmDescriptor::m_OutputIntermediateScale
float m_OutputIntermediateScale
Output intermediate quantization scale.
Definition: Descriptors.hpp:1205
armnn::LstmInputParams::m_RecurrentToCellWeights
const ConstTensor * m_RecurrentToCellWeights
Definition: LstmParams.hpp:46
armnn::LstmInputParams::m_ForgetLayerNormWeights
const ConstTensor * m_ForgetLayerNormWeights
Definition: LstmParams.hpp:58
armnn::LstmInputParams::m_OutputGateBias
const ConstTensor * m_OutputGateBias
Definition: LstmParams.hpp:54
armnn::IOutputSlot::SetTensorInfo
virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0
armnn::QLstmDescriptor::m_LayerNormEnabled
bool m_LayerNormEnabled
Enable/disable layer normalization.
Definition: Descriptors.hpp:1197
armnn::LstmInputParams::m_RecurrentToOutputWeights
const ConstTensor * m_RecurrentToOutputWeights
Definition: LstmParams.hpp:47
armnn::QLstmDescriptor::m_ProjectionClip
float m_ProjectionClip
Clipping threshold value for the projection.
Definition: Descriptors.hpp:1189
armnn::ConstTensor
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
Definition: Tensor.hpp:314
armnn::QLstmDescriptor::m_InputIntermediateScale
float m_InputIntermediateScale
Input intermediate quantization scale.
Definition: Descriptors.hpp:1199
armnn::QLstmDescriptor
A QLstmDescriptor for the QLstmLayer.
Definition: Descriptors.hpp:1153
armnn::QLstmDescriptor::m_ForgetIntermediateScale
float m_ForgetIntermediateScale
Forget intermediate quantization scale.
Definition: Descriptors.hpp:1201
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:1187
armnn::LstmInputParams::m_RecurrentToForgetWeights
const ConstTensor * m_RecurrentToForgetWeights
Definition: LstmParams.hpp:45
armnn::QLstmDescriptor::m_ProjectionEnabled
bool m_ProjectionEnabled
Enable/disable the projection layer.
Definition: Descriptors.hpp:1195
armnn::IConnectableLayer::GetInputSlot
virtual const IInputSlot & GetInputSlot(unsigned int index) const =0
Get a const input slot handle by slot index.
armnn::IConnectableLayer::GetOutputSlot
virtual const IOutputSlot & GetOutputSlot(unsigned int index) const =0
Get the const output slot handle by slot index.
armnn::INetworkPtr
std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr
Definition: INetwork.hpp:173
armnn::IOutputSlot::Connect
virtual int Connect(IInputSlot &destination)=0
SerializeNetwork
std::string SerializeNetwork(const armnn::INetwork &network)
Definition: SerializerTestUtils.cpp:152
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:1203
armnn::INetwork::Create
static INetworkPtr Create(NetworkOptions networkOptions={})
Definition: Network.cpp:510
armnn::QLstmDescriptor::m_CifgEnabled
bool m_CifgEnabled
Enable/disable CIFG (coupled input & forget gate).
Definition: Descriptors.hpp:1191
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:1207

◆ BOOST_AUTO_TEST_CASE() [8/8]

BOOST_AUTO_TEST_CASE ( SerializeDeserializeQLstmAdvanced  )

Definition at line 1958 of file LstmSerializationTests.cpp.

References BOOST_AUTO_TEST_SUITE_END(), IOutputSlot::Connect(), INetwork::Create(), DeserializeNetwork(), IConnectableLayer::GetInputSlot(), IConnectableLayer::GetOutputSlot(), LstmInputParams::m_CellBias, QLstmDescriptor::m_CellClip, QLstmDescriptor::m_CellIntermediateScale, LstmInputParams::m_CellLayerNormWeights, LstmInputParams::m_CellToForgetWeights, LstmInputParams::m_CellToInputWeights, LstmInputParams::m_CellToOutputWeights, QLstmDescriptor::m_CifgEnabled, LstmInputParams::m_ForgetGateBias, QLstmDescriptor::m_ForgetIntermediateScale, LstmInputParams::m_ForgetLayerNormWeights, QLstmDescriptor::m_HiddenStateScale, QLstmDescriptor::m_HiddenStateZeroPoint, LstmInputParams::m_InputGateBias, QLstmDescriptor::m_InputIntermediateScale, LstmInputParams::m_InputLayerNormWeights, LstmInputParams::m_InputToCellWeights, LstmInputParams::m_InputToForgetWeights, LstmInputParams::m_InputToInputWeights, LstmInputParams::m_InputToOutputWeights, QLstmDescriptor::m_LayerNormEnabled, LstmInputParams::m_OutputGateBias, QLstmDescriptor::m_OutputIntermediateScale, LstmInputParams::m_OutputLayerNormWeights, QLstmDescriptor::m_PeepholeEnabled, LstmInputParams::m_ProjectionBias, QLstmDescriptor::m_ProjectionClip, QLstmDescriptor::m_ProjectionEnabled, LstmInputParams::m_ProjectionWeights, LstmInputParams::m_RecurrentToCellWeights, LstmInputParams::m_RecurrentToForgetWeights, LstmInputParams::m_RecurrentToInputWeights, LstmInputParams::m_RecurrentToOutputWeights, armnn::QAsymmS8, armnn::QSymmS16, armnn::QSymmS8, SerializeNetwork(), IOutputSlot::SetTensorInfo(), and armnn::Signed32.

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  BOOST_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 }
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:62
armnn::LstmInputParams::m_CellBias
const ConstTensor * m_CellBias
Definition: LstmParams.hpp:53
DeserializeNetwork
armnn::INetworkPtr DeserializeNetwork(const std::string &serializerString)
Definition: SerializerTestUtils.cpp:146
armnn::LstmInputParams::m_CellToOutputWeights
const ConstTensor * m_CellToOutputWeights
Definition: LstmParams.hpp:50
armnn::QLstmDescriptor::m_PeepholeEnabled
bool m_PeepholeEnabled
Enable/disable peephole.
Definition: Descriptors.hpp:1193
armnn::QLstmDescriptor::m_HiddenStateScale
float m_HiddenStateScale
Hidden State quantization scale.
Definition: Descriptors.hpp:1209
armnn::LstmInputParams::m_CellToInputWeights
const ConstTensor * m_CellToInputWeights
Definition: LstmParams.hpp:48
armnn::QLstmDescriptor::m_OutputIntermediateScale
float m_OutputIntermediateScale
Output intermediate quantization scale.
Definition: Descriptors.hpp:1205
armnn::LstmInputParams::m_InputGateBias
const ConstTensor * m_InputGateBias
Definition: LstmParams.hpp:51
armnn::LstmInputParams::m_RecurrentToCellWeights
const ConstTensor * m_RecurrentToCellWeights
Definition: LstmParams.hpp:46
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::LstmInputParams::m_OutputGateBias
const ConstTensor * m_OutputGateBias
Definition: LstmParams.hpp:54
armnn::IOutputSlot::SetTensorInfo
virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0
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:1197
armnn::LstmInputParams::m_RecurrentToOutputWeights
const ConstTensor * m_RecurrentToOutputWeights
Definition: LstmParams.hpp:47
armnn::LstmInputParams::m_ProjectionBias
const ConstTensor * m_ProjectionBias
Definition: LstmParams.hpp:56
armnn::QLstmDescriptor::m_ProjectionClip
float m_ProjectionClip
Clipping threshold value for the projection.
Definition: Descriptors.hpp:1189
armnn::ConstTensor
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
Definition: Tensor.hpp:314
armnn::QLstmDescriptor::m_InputIntermediateScale
float m_InputIntermediateScale
Input intermediate quantization scale.
Definition: Descriptors.hpp:1199
armnn::QLstmDescriptor
A QLstmDescriptor for the QLstmLayer.
Definition: Descriptors.hpp:1153
armnn::QLstmDescriptor::m_ForgetIntermediateScale
float m_ForgetIntermediateScale
Forget intermediate quantization scale.
Definition: Descriptors.hpp:1201
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:1187
armnn::LstmInputParams::m_RecurrentToForgetWeights
const ConstTensor * m_RecurrentToForgetWeights
Definition: LstmParams.hpp:45
armnn::QLstmDescriptor::m_ProjectionEnabled
bool m_ProjectionEnabled
Enable/disable the projection layer.
Definition: Descriptors.hpp:1195
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::IConnectableLayer::GetOutputSlot
virtual const IOutputSlot & GetOutputSlot(unsigned int index) const =0
Get the const output slot handle by slot index.
armnn::INetworkPtr
std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr
Definition: INetwork.hpp:173
armnn::IOutputSlot::Connect
virtual int Connect(IInputSlot &destination)=0
SerializeNetwork
std::string SerializeNetwork(const armnn::INetwork &network)
Definition: SerializerTestUtils.cpp:152
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:1203
armnn::INetwork::Create
static INetworkPtr Create(NetworkOptions networkOptions={})
Definition: Network.cpp:510
armnn::QLstmDescriptor::m_CifgEnabled
bool m_CifgEnabled
Enable/disable CIFG (coupled input & forget gate).
Definition: Descriptors.hpp:1191
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:1207
armnn::LstmInputParams::m_InputToInputWeights
const ConstTensor * m_InputToInputWeights
Definition: LstmParams.hpp:40

◆ ConstantsVector2QuantizedLstmInputParams()

armnn::QuantizedLstmInputParams ConstantsVector2QuantizedLstmInputParams ( const std::vector< armnn::ConstTensor > &  constants)

Definition at line 1335 of file LstmSerializationTests.cpp.

References IConnectableLayer::GetName(), IConnectableLayer::GetType(), armnn::IgnoreUnused(), armnn::Input, QuantizedLstmInputParams::m_CellBias, QuantizedLstmInputParams::m_ForgetGateBias, QuantizedLstmInputParams::m_InputGateBias, QuantizedLstmInputParams::m_InputToCellWeights, QuantizedLstmInputParams::m_InputToForgetWeights, QuantizedLstmInputParams::m_InputToInputWeights, QuantizedLstmInputParams::m_InputToOutputWeights, QuantizedLstmInputParams::m_OutputGateBias, QuantizedLstmInputParams::m_RecurrentToCellWeights, QuantizedLstmInputParams::m_RecurrentToForgetWeights, QuantizedLstmInputParams::m_RecurrentToInputWeights, QuantizedLstmInputParams::m_RecurrentToOutputWeights, armnn::Output, and armnn::QuantizedLstm.

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 }
armnn::QuantizedLstmInputParams::m_RecurrentToOutputWeights
const ConstTensor * m_RecurrentToOutputWeights
Definition: QuantizedLstmParams.hpp:41
armnn::QuantizedLstmInputParams::m_RecurrentToForgetWeights
const ConstTensor * m_RecurrentToForgetWeights
Definition: QuantizedLstmParams.hpp:39
armnn::QuantizedLstmInputParams::m_InputToForgetWeights
const ConstTensor * m_InputToForgetWeights
Definition: QuantizedLstmParams.hpp:34
armnn::QuantizedLstmInputParams::m_RecurrentToInputWeights
const ConstTensor * m_RecurrentToInputWeights
Definition: QuantizedLstmParams.hpp:38
armnn::QuantizedLstmInputParams::m_RecurrentToCellWeights
const ConstTensor * m_RecurrentToCellWeights
Definition: QuantizedLstmParams.hpp:40
armnn::QuantizedLstmInputParams::m_InputToOutputWeights
const ConstTensor * m_InputToOutputWeights
Definition: QuantizedLstmParams.hpp:36

◆ ConstantVector2LstmInputParams()

armnn::LstmInputParams ConstantVector2LstmInputParams ( const std::vector< armnn::ConstTensor > &  constants,
Descriptor &  descriptor 
)

Definition at line 25 of file LstmSerializationTests.cpp.

References LayerVerifierBaseWithDescriptor< Descriptor >::ExecuteStrategy(), IConnectableLayer::GetType(), armnn::IgnoreUnused(), armnn::Input, armnn::Lstm, LstmInputParams::m_CellBias, LstmInputParams::m_CellLayerNormWeights, LstmInputParams::m_CellToForgetWeights, LstmInputParams::m_CellToInputWeights, LstmInputParams::m_CellToOutputWeights, LstmInputParams::m_ForgetGateBias, LstmInputParams::m_ForgetLayerNormWeights, LstmInputParams::m_InputGateBias, LstmInputParams::m_InputLayerNormWeights, LstmInputParams::m_InputToCellWeights, LstmInputParams::m_InputToForgetWeights, LstmInputParams::m_InputToInputWeights, LstmInputParams::m_InputToOutputWeights, LstmInputParams::m_OutputGateBias, LstmInputParams::m_OutputLayerNormWeights, LstmInputParams::m_ProjectionBias, LstmInputParams::m_ProjectionWeights, LstmInputParams::m_RecurrentToCellWeights, LstmInputParams::m_RecurrentToForgetWeights, LstmInputParams::m_RecurrentToInputWeights, LstmInputParams::m_RecurrentToOutputWeights, armnn::Output, armnn::QLstm, LayerVerifierBase::VerifyConstTensors(), LayerVerifierBaseWithDescriptor< Descriptor >::VerifyDescriptor(), and LayerVerifierBase::VerifyNameAndConnections().

27 {
28  armnn::LstmInputParams lstmInputParams;
29  size_t i = 0;
30 
31  // Inserting basic paramters
32  lstmInputParams.m_InputToForgetWeights = &constants[i++];
33  lstmInputParams.m_InputToCellWeights = &constants[i++];
34  lstmInputParams.m_InputToOutputWeights = &constants[i++];
35  lstmInputParams.m_RecurrentToForgetWeights = &constants[i++];
36  lstmInputParams.m_RecurrentToCellWeights = &constants[i++];
37  lstmInputParams.m_RecurrentToOutputWeights = &constants[i++];
38  lstmInputParams.m_ForgetGateBias = &constants[i++];
39  lstmInputParams.m_CellBias = &constants[i++];
40  lstmInputParams.m_OutputGateBias = &constants[i++];
41  if (!descriptor.m_CifgEnabled)
42  {
43  lstmInputParams.m_InputToInputWeights = &constants[i++];
44  lstmInputParams.m_RecurrentToInputWeights = &constants[i++];
45  lstmInputParams.m_InputGateBias = &constants[i++];
46  }
47 
48  if (descriptor.m_PeepholeEnabled)
49  {
50  if (!descriptor.m_CifgEnabled)
51  {
52  lstmInputParams.m_CellToInputWeights = &constants[i++];
53  }
54  lstmInputParams.m_CellToForgetWeights = &constants[i++];
55  lstmInputParams.m_CellToOutputWeights = &constants[i++];
56  }
57 
58  if (descriptor.m_ProjectionEnabled)
59  {
60  lstmInputParams.m_ProjectionWeights = &constants[i++];
61  lstmInputParams.m_ProjectionBias = &constants[i++];
62  }
63 
64  if (descriptor.m_LayerNormEnabled)
65  {
66  if (!descriptor.m_CifgEnabled)
67  {
68  lstmInputParams.m_InputLayerNormWeights = &constants[i++];
69  }
70  lstmInputParams.m_ForgetLayerNormWeights = &constants[i++];
71  lstmInputParams.m_CellLayerNormWeights = &constants[i++];
72  lstmInputParams.m_OutputLayerNormWeights = &constants[i++];
73  }
74 
75  return lstmInputParams;
76 }
armnn::LstmInputParams::m_ProjectionWeights
const ConstTensor * m_ProjectionWeights
Definition: LstmParams.hpp:55
armnn::LstmInputParams::m_CellBias
const ConstTensor * m_CellBias
Definition: LstmParams.hpp:53
armnn::LstmInputParams::m_CellToOutputWeights
const ConstTensor * m_CellToOutputWeights
Definition: LstmParams.hpp:50
armnn::LstmInputParams::m_CellToInputWeights
const ConstTensor * m_CellToInputWeights
Definition: LstmParams.hpp:48
armnn::LstmInputParams::m_InputGateBias
const ConstTensor * m_InputGateBias
Definition: LstmParams.hpp:51
armnn::LstmInputParams::m_RecurrentToCellWeights
const ConstTensor * m_RecurrentToCellWeights
Definition: LstmParams.hpp:46
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::LstmInputParams::m_OutputGateBias
const ConstTensor * m_OutputGateBias
Definition: LstmParams.hpp:54
armnn::LstmInputParams::m_InputLayerNormWeights
const ConstTensor * m_InputLayerNormWeights
Definition: LstmParams.hpp:57
armnn::LstmInputParams::m_RecurrentToOutputWeights
const ConstTensor * m_RecurrentToOutputWeights
Definition: LstmParams.hpp:47
armnn::LstmInputParams::m_ProjectionBias
const ConstTensor * m_ProjectionBias
Definition: LstmParams.hpp:56
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::LstmInputParams::m_RecurrentToForgetWeights
const ConstTensor * m_RecurrentToForgetWeights
Definition: LstmParams.hpp:45
armnn::LstmInputParams::m_RecurrentToInputWeights
const ConstTensor * m_RecurrentToInputWeights
Definition: LstmParams.hpp:44
armnn::LstmInputParams::m_OutputLayerNormWeights
const ConstTensor * m_OutputLayerNormWeights
Definition: LstmParams.hpp:60
armnn::LstmInputParams::m_InputToForgetWeights
const ConstTensor * m_InputToForgetWeights
Definition: LstmParams.hpp:41
armnn::LstmInputParams::m_InputToInputWeights
const ConstTensor * m_InputToInputWeights
Definition: LstmParams.hpp:40