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Searched refs:timeMajor (Results 1 – 6 of 6) sorted by relevance

/packages/modules/NeuralNetworks/common/cpu_operations/
DUnidirectionalSequenceRNN.cpp67 int32_t timeMajor = context->getInputValue<int32_t>(kTimeMajorParam); in executeTyped() local
73 if (!timeMajor) { in executeTyped()
103 if (!timeMajor) { in executeTyped()
125 int32_t timeMajor = context->getInputValue<int32_t>(kTimeMajorParam); in prepare() local
126 NN_RET_CHECK(timeMajor == 0 || timeMajor == 1); in prepare()
128 timeMajor ? getSizeOfDimension(input, 1) : getSizeOfDimension(input, 0); in prepare()
130 timeMajor ? getSizeOfDimension(input, 0) : getSizeOfDimension(input, 1); in prepare()
149 output.dimensions[0] = timeMajor ? maxTime : batchSize; in prepare()
150 output.dimensions[1] = timeMajor ? batchSize : maxTime; in prepare()
DBidirectionalSequenceRNN.cpp130 const bool timeMajor = context->getInputValue<bool>(kTimeMajorParam); in executeTyped() local
149 if (!timeMajor) { in executeTyped()
275 if (!timeMajor) { in executeTyped()
325 bool timeMajor = context->getInputValue<bool>(kTimeMajorParam); in prepare() local
327 timeMajor ? getSizeOfDimension(input, 1) : getSizeOfDimension(input, 0); in prepare()
329 timeMajor ? getSizeOfDimension(input, 0) : getSizeOfDimension(input, 1); in prepare()
381 fwOutput.dimensions[0] = timeMajor ? maxTime : batchSize; in prepare()
382 fwOutput.dimensions[1] = timeMajor ? batchSize : maxTime; in prepare()
388 bwOutput.dimensions[0] = timeMajor ? maxTime : batchSize; in prepare()
389 bwOutput.dimensions[1] = timeMajor ? batchSize : maxTime; in prepare()
DLSTM.cpp426 bool timeMajor, bool forwardSequence) { in LSTMEvalFloat32() argument
433 (inputRank == 3) ? getSizeOfDimension(input_shape, timeMajor ? 0 : 1) : 1; in LSTMEvalFloat32()
434 const uint32_t batchSize = (inputRank == 3) ? getSizeOfDimension(input_shape, timeMajor ? 1 : 0) in LSTMEvalFloat32()
451 if (!timeMajor) { in LSTMEvalFloat32()
464 const float* inputData = timeMajor ? input_buffer : transposedInput.data(); in LSTMEvalFloat32()
466 hasAuxInput ? (timeMajor ? aux_input_buffer : transposedAuxInput.data()) : nullptr; in LSTMEvalFloat32()
467 float* outputData = timeMajor ? output_buffer : transposedOutput.data(); in LSTMEvalFloat32()
512 if (!timeMajor) { in LSTMEvalFloat32()
546 bool timeMajor, bool forwardSequence) { in LSTMEvalFloat16()
553 (inputRank == 3) ? getSizeOfDimension(input_shape, timeMajor ? 0 : 1) : 1; in LSTMEvalFloat16()
[all …]
/packages/modules/NeuralNetworks/common/types/operations/include/
DLSTM.h129 bool timeMajor = true, bool forwardSequence = true);
157 _Float16* scratch_buffer_buffer, bool timeMajor = true, bool forwardSequence = true);
/packages/modules/NeuralNetworks/runtime/test/
DTestValidateOperations.cpp2910 ANeuralNetworksOperandType timeMajor = boolScalar; in lstmBidirectionalSequence() local
2977 timeMajor, in lstmBidirectionalSequence()
4020 ANeuralNetworksOperandType timeMajor = boolScalar; in bidirectionlSequenceRNNTest() local
4026 fwWeights, bwWeights, activation, timeMajor, mergeOutputs}, in bidirectionlSequenceRNNTest()
4088 ANeuralNetworksOperandType timeMajor = intScalar; in unidirectionlSequenceRNNTest() local
4092 {input, weights, recurrentWeights, bias, hiddenState, activation, timeMajor}, {output}); in unidirectionlSequenceRNNTest()
4203 ANeuralNetworksOperandType timeMajor = boolScalar; in unidirectionalSequenceLSTMTest() local
4243 timeMajor, in unidirectionalSequenceLSTMTest()
/packages/modules/NeuralNetworks/tools/api/
Dtypes.spec3655 * A 3-D tensor. The shape is defined by the input 6 (timeMajor). If
3679 * A 3-D tensor. The shape is defined by the input 6 (timeMajor). If
3701 * * 13:timeMajor
3711 * the input 6 (timeMajor) and the third dimension is defined by the
3712 * input 14 (mergeOutputs). If timeMajor is set to true, then the first
3720 * (timeMajor). If it is set to true, then the shape is set to
6042 * A 3-D tensor. The shape is defined by the input 6 (timeMajor). If
6058 * * 6: timeMajor
6063 * A 3-D tensor. The shape is defined by the input 6 (timeMajor). If