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

/frameworks/ml/nn/common/operations/
DUnidirectionalSequenceRNN.cpp80 int32_t timeMajor = context->getInputValue<int32_t>(kTimeMajorParam); in executeTyped() local
86 if (!timeMajor) { in executeTyped()
116 if (!timeMajor) { in executeTyped()
160 int32_t timeMajor = context->getInputValue<int32_t>(kTimeMajorParam); in prepare() local
161 NN_RET_CHECK(timeMajor == 0 || timeMajor == 1); in prepare()
163 timeMajor ? getSizeOfDimension(input, 1) : getSizeOfDimension(input, 0); in prepare()
165 timeMajor ? getSizeOfDimension(input, 0) : getSizeOfDimension(input, 1); in prepare()
184 output.dimensions[0] = timeMajor ? maxTime : batchSize; in prepare()
185 output.dimensions[1] = timeMajor ? batchSize : maxTime; in prepare()
DBidirectionalSequenceRNN.cpp161 const bool timeMajor = context->getInputValue<bool>(kTimeMajorParam); in executeTyped() local
180 if (!timeMajor) { in executeTyped()
306 if (!timeMajor) { in executeTyped()
385 bool timeMajor = context->getInputValue<bool>(kTimeMajorParam); in prepare() local
387 timeMajor ? getSizeOfDimension(input, 1) : getSizeOfDimension(input, 0); in prepare()
389 timeMajor ? getSizeOfDimension(input, 0) : getSizeOfDimension(input, 1); in prepare()
441 fwOutput.dimensions[0] = timeMajor ? maxTime : batchSize; in prepare()
442 fwOutput.dimensions[1] = timeMajor ? batchSize : maxTime; in prepare()
448 bwOutput.dimensions[0] = timeMajor ? maxTime : batchSize; in prepare()
449 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 …]
DLSTM.h130 bool timeMajor = true, bool forwardSequence = true);
158 _Float16* scratch_buffer_buffer, bool timeMajor = true, bool forwardSequence = true);
/frameworks/ml/nn/runtime/test/
DTestValidateOperations.cpp2872 ANeuralNetworksOperandType timeMajor = boolScalar; in lstmBidirectionalSequence() local
2939 timeMajor, in lstmBidirectionalSequence()
3982 ANeuralNetworksOperandType timeMajor = boolScalar; in bidirectionlSequenceRNNTest() local
3988 fwWeights, bwWeights, activation, timeMajor, mergeOutputs}, in bidirectionlSequenceRNNTest()
4050 ANeuralNetworksOperandType timeMajor = intScalar; in unidirectionlSequenceRNNTest() local
4054 {input, weights, recurrentWeights, bias, hiddenState, activation, timeMajor}, {output}); in unidirectionlSequenceRNNTest()
4165 ANeuralNetworksOperandType timeMajor = boolScalar; in unidirectionalSequenceLSTMTest() local
4205 timeMajor, in unidirectionalSequenceLSTMTest()
/frameworks/ml/nn/tools/api/
Dtypes.spec3492 * A 3-D tensor. The shape is defined by the input 6 (timeMajor). If
3516 * A 3-D tensor. The shape is defined by the input 6 (timeMajor). If
3538 * * 13:timeMajor
3548 * the input 6 (timeMajor) and the third dimension is defined by the
3549 * input 14 (mergeOutputs). If timeMajor is set to true, then the first
3557 * (timeMajor). If it is set to true, then the shape is set to