ArmNN
 21.02
QuantizedLstmEndToEndTestImpl.cpp File Reference
#include "QuantizedLstmEndToEndTestImpl.hpp"
#include "CommonTestUtils.hpp"
#include "EndToEndTestImpl.hpp"
#include <ResolveType.hpp>
#include <armnn/INetwork.hpp>
#include <armnn/QuantizedLstmParams.hpp>
#include <armnn/utility/NumericCast.hpp>
#include <test/TensorHelpers.hpp>
#include <boost/test/unit_test.hpp>
#include <type_traits>

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Functions

void QuantizedLstmEndToEnd (const std::vector< armnn::BackendId > &backends)
 

Function Documentation

◆ QuantizedLstmEndToEnd()

void QuantizedLstmEndToEnd ( const std::vector< armnn::BackendId > &  backends)

Definition at line 181 of file QuantizedLstmEndToEndTestImpl.cpp.

References armnn::Optimize(), armnn::QAsymmU8, and armnn::QSymmS16.

Referenced by BOOST_AUTO_TEST_CASE().

182 {
183  std::vector<uint8_t> inputVector = {166, 179, 50, 150};
184  armnn::TensorInfo inputDesc({2, 2}, armnn::DataType::QAsymmU8);
185  boost::multi_array<uint8_t, 2> input = MakeTensor<uint8_t, 2>(inputDesc, inputVector);
186 
187  std::vector<int16_t> cellStateInVector = {876, 1034, 955, -909, 761, 1029, 796, -1036};
188  armnn::TensorInfo cellStateInDesc({2, 4}, armnn::DataType::QSymmS16);
189  boost::multi_array<int16_t, 2> cellStateIn = MakeTensor<int16_t, 2>(cellStateInDesc, cellStateInVector);
190 
191  std::vector<uint8_t> outputStateInVector = {136, 150, 140, 115, 135, 152, 138, 112};
192  armnn::TensorInfo outputStateInDesc({2, 4}, armnn::DataType::QAsymmU8);
193  boost::multi_array<uint8_t, 2> outputStateIn = MakeTensor<uint8_t, 2>(outputStateInDesc, outputStateInVector);
194 
195  std::vector<int16_t> cellStateOutVector = {1485, 1177, 1373, -1023, 1019, 1355, 1097, -1235};
196  armnn::TensorInfo cellStateOutVectorDesc({2, 4}, armnn::DataType::QSymmS16);
197  boost::multi_array<int16_t, 2> cellStateOut = MakeTensor<int16_t, 2>(cellStateOutVectorDesc, cellStateOutVector);
198 
199  std::vector<uint8_t> outputStateOutVector = {140, 151, 146, 112, 136, 156, 142, 112};
200  armnn::TensorInfo outputDesc({2, 4}, armnn::DataType::QAsymmU8);
201  boost::multi_array<uint8_t, 2> outputStateOut = MakeTensor<uint8_t, 2>(outputDesc, outputStateOutVector);
202 
203  // Builds up the structure of the network
204  armnn::INetworkPtr net = CreateQuantizedLstmNetwork(input, outputStateOut);
205 
206  BOOST_TEST_CHECKPOINT("create a network");
207 
209  IRuntimePtr runtime(IRuntime::Create(options));
210 
211  // optimize the network
212  IOptimizedNetworkPtr optNet = Optimize(*net, backends, runtime->GetDeviceSpec());
213 
214  // Loads it into the runtime.
215  NetworkId netId;
216  runtime->LoadNetwork(netId, std::move(optNet));
217 
218  InputTensors inputTensors;
219  inputTensors.reserve(3);
220 
221  // input
222  inputTensors.push_back({0, ConstTensor(runtime->GetInputTensorInfo(netId, 0), inputVector.data())});
223  inputTensors.push_back({1, ConstTensor(runtime->GetInputTensorInfo(netId, 1), cellStateInVector.data())});
224  inputTensors.push_back({2, ConstTensor(runtime->GetInputTensorInfo(netId, 2), outputStateInVector.data())});
225 
226  OutputTensors outputTensors;
227  outputTensors.reserve(2);
228 
229  //output
230  std::vector<int16_t > cellStateOutResult(cellStateOutVector.size());
231  std::vector<uint8_t > outputStateOutResult(outputStateOutVector.size());
232  outputTensors.push_back({0, Tensor(runtime->GetOutputTensorInfo(netId, 0), cellStateOutResult.data())});
233  outputTensors.push_back({1, Tensor(runtime->GetOutputTensorInfo(netId, 1), outputStateOutResult.data())});
234 
235  // Does the inference.
236  runtime->EnqueueWorkload(netId, inputTensors, outputTensors);
237 
238  // Checks the results
239  constexpr int16_t toleranceInt16 = 2;
240  for (unsigned int i = 0u; i < cellStateOutResult.size(); ++i)
241  {
242  BOOST_CHECK(IsCloseEnough(cellStateOutVector[i], cellStateOutResult[i], toleranceInt16));
243  }
244 
245  constexpr uint8_t toleranceUint8 = 1;
246  for (unsigned int i = 0u; i < outputStateOutResult.size(); ++i)
247  {
248  BOOST_TEST(IsCloseEnough(outputStateOutVector[i], outputStateOutResult[i], toleranceUint8));
249  }
250 }
std::unique_ptr< IRuntime, void(*)(IRuntime *runtime)> IRuntimePtr
Definition: IRuntime.hpp:26
std::vector< std::pair< LayerBindingId, class ConstTensor > > InputTensors
Definition: Tensor.hpp:340
int NetworkId
Definition: IRuntime.hpp:20
A tensor defined by a TensorInfo (shape and data type) and a mutable backing store.
Definition: Tensor.hpp:306
IOptimizedNetworkPtr Optimize(const INetwork &network, const std::vector< BackendId > &backendPreferences, const IDeviceSpec &deviceSpec, const OptimizerOptions &options=OptimizerOptions(), Optional< std::vector< std::string > &> messages=EmptyOptional())
Create an optimized version of the network.
Definition: Network.cpp:1502
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
Definition: Tensor.hpp:314
std::vector< std::pair< LayerBindingId, class Tensor > > OutputTensors
Definition: Tensor.hpp:341
std::unique_ptr< IOptimizedNetwork, void(*)(IOptimizedNetwork *network)> IOptimizedNetworkPtr
Definition: INetwork.hpp:174
std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr
Definition: INetwork.hpp:173