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HardSwishOperator.hpp File Reference
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Functions

TosaSerializationBasicBlock * ConvertHardSwishToTosaOperator (const Layer *layer, const std::vector< const TensorInfo * > &inputs, const std::vector< const TensorInfo * > &outputs, const ActivationDescriptor *activationDescriptor)
 

Function Documentation

◆ ConvertHardSwishToTosaOperator()

TosaSerializationBasicBlock* ConvertHardSwishToTosaOperator ( const Layer layer,
const std::vector< const TensorInfo * > &  inputs,
const std::vector< const TensorInfo * > &  outputs,
const ActivationDescriptor activationDescriptor 
)

Definition at line 160 of file HardSwishOperator.cpp.

164 {
165  if (inputs.size() != 1)
166  {
167  throw armnn::Exception("ConvertHardSwishToTosaOperator: 1 input tensors required.");
168  }
169 
170  if (outputs.size() != 1)
171  {
172  throw armnn::Exception("ConvertHardSwishToTosaOperator: 1 output tensor required.");
173  }
174 
175  if (desc->m_Function != ActivationFunction::HardSwish)
176  {
177  throw armnn::Exception("ConvertHardSwishToTosaOperator ActivationDescriptor only supports function HardSwish.");
178  }
179 
180  std::string inputName = std::string("input_");
181  std::string outputName = std::string("output0_");
182  std::string blockName = std::string("Op_HARDSWISH_block_") + GetUniqueTosaMappingID();
183 
184  // If a layer is present then the block will be used for execution, so input and output names need to be determined
185  // using the previous and following layers so the graph is connected correctly. For validation this doesn't matter.
186  if (layer != nullptr)
187  {
188  inputName = GenerateUniqueInputName(layer->GetInputSlot(0));
189  outputName = GenerateUniqueOutputName(*layer);
190  }
191 
192  std::vector<TosaSerializationTensor*> tensors;
193  std::vector<TosaSerializationOperator*> operators;
194 
195  DataType inputDType = inputs[0]->GetDataType();
196 
197  bool isInt8 = (inputDType == DataType::QAsymmS8 || inputDType == DataType::QSymmS8);
198  if (isInt8)
199  {
200  float inputScale = inputs[0]->GetQuantizationScale();
201  float outputScale = outputs[0]->GetQuantizationScale();
202  int32_t inputZp = inputs[0]->GetQuantizationOffset();
203  int32_t outputZp = outputs[0]->GetQuantizationOffset();
204 
205  TosaTableAttribute attribute(
206  getTosaConstHardSwish8bitTable(inputScale, inputZp, outputScale, outputZp));
207  operators.push_back(new TosaSerializationOperator(tosa::Op_TABLE,
208  Attribute_TableAttribute,
209  &attribute,
210  {inputName},
211  {outputName}));
212  }
213  else
214  {
215  throw Exception("ConvertHardSwishToTosaOperator() type currently unimplemented.");
216  }
217 
218  // Only add input tensors if connected layer is an input layer.
219  // As intermediate or constant tensors will be created separately.
220  // There also can't be duplicate tensor.
221  std::vector<int32_t> inputShape0;
222  DType inputDType0 = ArmNNToDType(inputs[0]->GetDataType());
223  if(inputName.find("input_") != std::string::npos)
224  {
225  inputShape0 = GetTosaTensorShape(inputs[0]->GetShape());
226  tensors.push_back(new TosaSerializationTensor(inputName, inputShape0, inputDType0, {}));
227  }
228 
229  std::vector<int32_t> outputShape0 = GetTosaTensorShape(outputs[0]->GetShape());
230  DType outputDType0 = ArmNNToDType(outputs[0]->GetDataType());
231  tensors.push_back(new TosaSerializationTensor(outputName, outputShape0, outputDType0, {}));
232 
233  // operatorInputNames/operatorOutputNames ends up being the same as
234  // blockInputNames/blockOutputNames for one-to-one ArmNN to Tosa mappings
235  return new TosaSerializationBasicBlock(blockName, // name
236  mainName, // region name
237  operators, // operators
238  tensors, // tensors
239  {inputName}, // inputs
240  {outputName}); // outputs
241 }
std::vector< int16_t > getTosaConstHardSwish8bitTable(float inputScale, int32_t inputZp, float outputScale, int32_t outputZp)
std::string GenerateUniqueOutputName(const Layer &layer, uint32_t layerSlot=0)
const std::string mainName
DType ArmNNToDType(const DataType &type)
std::vector< int32_t > GetTosaTensorShape(const TensorShape &shape)
std::string GenerateUniqueInputName(const armnn::InputSlot &slot)
std::string GetUniqueTosaMappingID()
Base class for all ArmNN exceptions so that users can filter to just those.
Definition: Exceptions.hpp:47
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:337
DataType
Definition: Types.hpp:49

References ArmNNToDType(), GenerateUniqueInputName(), GenerateUniqueOutputName(), Layer::GetInputSlot(), getTosaConstHardSwish8bitTable(), GetTosaTensorShape(), GetUniqueTosaMappingID(), and ActivationDescriptor::m_Function.

Referenced by GetTosaMapping().