Searched refs:inputRank (Results 1 – 8 of 8) sorted by relevance
/frameworks/ml/nn/common/operations/ |
D | Reduce.cpp | 56 const uint32_t inputRank = getNumberOfDimensions(inputShape); in compute() local 62 reinterpret_cast<const int32_t*>(inputShape.dimensions.data()), inputRank, in compute() 130 const uint32_t inputRank = getNumberOfDimensions(inputShape); in prepare() local 131 NN_RET_CHECK_LE(inputRank, 4); in prepare() 133 std::vector<bool> shouldReduce(inputRank); in prepare() 140 NN_RET_CHECK(handleNegativeAxis(inputRank, &axis)); in prepare() 148 for (uint32_t axis = 0; axis < inputRank; ++axis) { in prepare()
|
D | Softmax.cpp | 250 const auto inputRank = getNumberOfDimensions(context->getInputShape(kInputTensor)); in validate() local 251 if (inputRank != 0) { in validate() 252 NN_RET_CHECK_LE(inputRank, 4); in validate() 258 if (inputRank != 2 && inputRank != 4 && inputRank != 0) { in validate()
|
D | LSTM.cpp | 429 const uint32_t inputRank = getNumberOfDimensions(input_shape); in LSTMEvalFloat32() local 430 NN_CHECK(inputRank == 2 || inputRank == 3); in LSTMEvalFloat32() 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() 436 const uint32_t inputSize = getSizeOfDimension(input_shape, inputRank - 1); in LSTMEvalFloat32() 549 const uint32_t inputRank = getNumberOfDimensions(input_shape); in LSTMEvalFloat16() local 550 NN_CHECK(inputRank == 2 || inputRank == 3); in LSTMEvalFloat16() 553 (inputRank == 3) ? getSizeOfDimension(input_shape, timeMajor ? 0 : 1) : 1; in LSTMEvalFloat16() 554 const uint32_t batchSize = (inputRank == 3) ? getSizeOfDimension(input_shape, timeMajor ? 1 : 0) in LSTMEvalFloat16() 556 const uint32_t inputSize = getSizeOfDimension(input_shape, inputRank - 1); in LSTMEvalFloat16()
|
D | Concatenation.cpp | 167 const uint32_t inputRank = getNumberOfDimensions(context->getInputShape(i)); in validate() local 168 if (inputRank != 0) { in validate() 169 NN_RET_CHECK_LE(inputRank, 4); in validate()
|
D | UnidirectionalSequenceLSTM.cpp | 198 const uint32_t inputRank = getNumberOfDimensions(inputShape); in prepare() local 199 NN_RET_CHECK_EQ(inputRank, 3) << "Invalid input tensor rank: " << inputRank; in prepare() 203 const uint32_t inputSize = getSizeOfDimension(inputShape, inputRank - 1); in prepare()
|
D | QLSTM.cpp | 179 const uint32_t inputRank = getNumberOfDimensions(inputShape); in prepare() local 180 NN_RET_CHECK_EQ(inputRank, 2) << "Invalid input tensor rank: " << inputRank; in prepare()
|
D | Conv2D.cpp | 537 const auto inputRank = getNumberOfDimensions(context->getInputShape(kInputTensor)); in validate() local 539 if (inputRank != 0) { in validate() 540 NN_RET_CHECK_EQ(inputRank, 4); in validate()
|
/frameworks/ml/nn/common/ |
D | Utils.cpp | 923 const auto inputRank = operands[inputIndexes[0]].dimensions.size(); in validateOperation() local 924 if (inputRank > 4) { in validateOperation() 1469 const auto inputRank = operands[inputIndexes[0]].dimensions.size(); in validateOperation() local 1470 if (inputRank > 4) { in validateOperation() 1521 const auto inputRank = operands[inputIndexes[0]].dimensions.size(); in validateOperation() local 1522 if (inputRank > 4) { in validateOperation() 1587 const auto inputRank = operands[inputIndexes[0]].dimensions.size(); in validateOperation() local 1588 if (inputRank > 4) { in validateOperation()
|