RNN.cpp - OpenGrok cross reference for /packages/modules/NeuralNetworks/common/operations/RNN.cpp

Lines Matching refs:Shape
45 bool RNN::Prepare(const Operation& operation, RunTimeOperandInfo* operands, Shape* hiddenStateShape,  in Prepare()
46                   Shape* outputShape) {  in Prepare()
68     const Shape& inputShape = input->shape();  in Prepare()
116 bool RNN::RNNStep(const T* inputData, const Shape& inputShape, const T* hiddenStateInputData,  in RNNStep()
117                   const T* biasData, const T* weightsData, const Shape& weightsShape,  in RNNStep()
118                   const T* recurrentWeightsData, const Shape& recurrentWeightsShape,  in RNNStep()
122     Shape dummyShape;  in RNNStep()
136 bool RNN::RNNStep(const T* inputData, const Shape& inputShape, const T* auxInputData,  in RNNStep()
137                   const Shape& auxInputShape, const T* hiddenStateInputData, const T* biasData,  in RNNStep()
138                   const T* weightsData, const Shape& weightsShape, const T* auxWeightsData,  in RNNStep()
139                   const Shape& auxWeightsShape, const T* recurrentWeightsData,  in RNNStep()
140                   const Shape& recurrentWeightsShape, const int32_t activation,  in RNNStep()
223 template bool RNN::RNNStep<_Float16>(const _Float16* inputData, const Shape& inputShape,
225                                      const _Float16* weightsData, const Shape& weightsShape,
227                                      const Shape& recurrentWeightsShape, int32_t activation,
229 template bool RNN::RNNStep<_Float16>(const _Float16* inputData, const Shape& inputShape,
230                                      const _Float16* auxInputData, const Shape& auxInputShape,
232                                      const _Float16* weightsData, const Shape& weightsShape,
233                                      const _Float16* auxWeightsData, const Shape& auxWeightsShape,
235                                      const Shape& recurrentWeightsShape, const int32_t activation,
239 template bool RNN::RNNStep<float>(const float* inputData, const Shape& inputShape,
241                                   const float* weightsData, const Shape& weightsShape,
243                                   const Shape& recurrentWeightsShape, int32_t activation,
245 template bool RNN::RNNStep<float>(const float* inputData, const Shape& inputShape,
246                                   const float* auxInputData, const Shape& auxInputShape,
248                                   const float* weightsData, const Shape& weightsShape,
249                                   const float* auxWeightsData, const Shape& auxWeightsShape,
251                                   const Shape& recurrentWeightsShape, int32_t activation,