Searched refs:weightsShape (Results 1 – 5 of 5) sorted by relevance
| /packages/modules/NeuralNetworks/common/cpu_operations/ |
| D | FullyConnected.cpp | 53 const float* weightsData, const Shape& weightsShape, in fullyConnectedFloat32() argument
67 weightsData, convertShapeToDims(weightsShape), in fullyConnectedFloat32()
74 weightsData, convertShapeToDims(weightsShape), in fullyConnectedFloat32()
83 const _Float16* weightsData, const Shape& weightsShape, in fullyConnectedFloat16() argument
89 std::vector<float> weightsDataFloat32(getNumberOfElements(weightsShape)); in fullyConnectedFloat16()
96 weightsShape, biasDataFloat32.data(), biasShape, activation, in fullyConnectedFloat16()
104 const uint8_t* weightsData, const Shape& weightsShape, in fullyConnectedQuant8() argument
109 int32_t weightsOffset = -weightsShape.offset; in fullyConnectedQuant8()
118 NN_RET_CHECK(GetQuantizedConvolutionMultiplier(inputShape, weightsShape, biasShape, outputShape, in fullyConnectedQuant8()
135 weightsData, convertShapeToDims(weightsShape), in fullyConnectedQuant8()
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| D | RNN.cpp | 117 const T* biasData, const T* weightsData, const Shape& weightsShape, in RNNStep() argument
123 uint32_t numUnits = weightsShape.dimensions[0]; in RNNStep()
125 hiddenStateInputData, biasData, weightsData, weightsShape, in RNNStep()
138 const T* weightsData, const Shape& weightsShape, const T* auxWeightsData, in RNNStep() argument
146 const uint32_t num_units = weightsShape.dimensions[0]; in RNNStep()
148 const uint32_t input_weights_stride = weightsShape.dimensions[1]; in RNNStep()
225 const _Float16* weightsData, const Shape& weightsShape,
232 const _Float16* weightsData, const Shape& weightsShape,
241 const float* weightsData, const Shape& weightsShape,
248 const float* weightsData, const Shape& weightsShape,
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| D | QuantizedLSTM.cpp | 381 Shape weightsShape; in eval() local
382 weightsShape.dimensions = {4 * SizeOfDimension(prevOutput_, 1), in eval()
384 std::vector<uint8_t> weights(getNumberOfElements(weightsShape)); in eval()
385 concatenateWeights(weightsShape.dimensions, weights.data()); in eval()
388 biasShape.dimensions = {getSizeOfDimension(weightsShape, 0)}; in eval()
393 concatTempShape.dimensions = {SizeOfDimension(input_, 0), getSizeOfDimension(weightsShape, 1)}; in eval()
397 getSizeOfDimension(weightsShape, 0)}; in eval()
418 weights.data(), convertShapeToDims(weightsShape), bias.data(), in eval()
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| D | UnidirectionalSequenceRNN.cpp | 57 Shape weightsShape = context->getInputShape(kWeightsTensor); in executeTyped() local
87 const uint32_t numUnits = getSizeOfDimension(weightsShape, 0); in executeTyped()
96 RNN::RNNStep<T>(input, fixedTimeInputShape, hiddenState, bias, weights, weightsShape, in executeTyped()
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| /packages/modules/NeuralNetworks/common/types/operations/include/ |
| D | RNN.h | 57 const T* biasData, const T* weightsData, const Shape& weightsShape,
64 const T* biasData, const T* weightsData, const Shape& weightsShape,
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