| /hardware/qcom/neuralnetworks/hvxservice/1.0/ |
| D | HexagonModel.cpp | 35 const Operand& operand = model.operands[i]; in getOperandsInfo() local
37 .type = operand.type, in getOperandsInfo()
38 .dimensions = operand.dimensions, in getOperandsInfo()
39 .scale = operand.scale, in getOperandsInfo()
40 .zeroPoint = operand.zeroPoint, in getOperandsInfo()
41 .lifetime = operand.lifetime, in getOperandsInfo()
42 .buffer = const_cast<uint8_t*>(getData(operand, model.operandValues, pools)), in getOperandsInfo()
43 .length = operand.location.length, in getOperandsInfo()
104 const int32_t* Model::getPointer(uint32_t operand) { in getPointer() argument
105 return reinterpret_cast<const int32_t*>(mOperands[operand].buffer); in getPointer()
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| D | HexagonModel.h | 84 const int32_t* getPointer(uint32_t operand);
85 Shape getShape(uint32_t operand);
86 bool setShape(uint32_t operand, const Shape& shape);
87 bool isConstant(uint32_t operand);
90 const hexagon_nn_input& getTensor(uint32_t operand);
91 const hexagon_nn_input& getQuantizationMin(uint32_t operand);
92 const hexagon_nn_input& getQuantizationMax(uint32_t operand);
93 hexagon_nn_input createQuantizationValue(uint32_t operand, int32_t quant_value);
94 hexagon_nn_input createConvFilterTensor(uint32_t operand);
95 hexagon_nn_input createDepthwiseFilterTensor(uint32_t operand, int32_t depth_multiplier);
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| D | HexagonUtils.cpp | 152 const uint8_t* getData(const Operand& operand, const hidl_vec<uint8_t>& block, in getData() argument
154 switch (operand.lifetime) { in getData()
162 return getDataFromBlock(block, operand.location.offset, operand.location.length); in getData()
164 return getDataFromPool(pools[operand.location.poolIndex], operand.location.offset, in getData()
165 operand.location.length); in getData()
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| D | HexagonUtils.h | 78 const uint8_t* getData(const Operand& operand, const hidl_vec<uint8_t>& block,
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| /hardware/interfaces/neuralnetworks/1.0/vts/functional/ |
| D | ValidateModel.cpp | 124 for (size_t operand = 0; operand < model.operands.size(); ++operand) { in mutateOperandTypeTest() local
127 std::to_string(operand) + " set to value " + in mutateOperandTypeTest()
129 validate(device, message, model, [operand, invalidOperandType](Model* model) { in mutateOperandTypeTest()
130 model->operands[operand].type = static_cast<OperandType>(invalidOperandType); in mutateOperandTypeTest()
154 for (size_t operand = 0; operand < model.operands.size(); ++operand) { in mutateOperandRankTest() local
155 const uint32_t invalidRank = getInvalidRank(model.operands[operand].type); in mutateOperandRankTest()
156 const std::string message = "mutateOperandRankTest: operand " + std::to_string(operand) + in mutateOperandRankTest()
158 validate(device, message, model, [operand, invalidRank](Model* model) { in mutateOperandRankTest()
159 model->operands[operand].dimensions = std::vector<uint32_t>(invalidRank, 0); in mutateOperandRankTest()
183 for (size_t operand = 0; operand < model.operands.size(); ++operand) { in mutateOperandScaleTest() local
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| /hardware/interfaces/neuralnetworks/1.2/vts/functional/ |
| D | ValidateModel.cpp | 140 for (size_t operand = 0; operand < model.operands.size(); ++operand) { in mutateOperandTypeTest() local
143 std::to_string(operand) + " set to value " + in mutateOperandTypeTest()
145 validate(device, message, model, [operand, invalidOperandType](Model* model) { in mutateOperandTypeTest()
146 model->operands[operand].type = static_cast<OperandType>(invalidOperandType); in mutateOperandTypeTest()
178 for (size_t operand = 0; operand < model.operands.size(); ++operand) { in mutateOperandRankTest() local
179 const uint32_t invalidRank = getInvalidRank(model.operands[operand].type); in mutateOperandRankTest()
183 const std::string message = "mutateOperandRankTest: operand " + std::to_string(operand) + in mutateOperandRankTest()
185 validate(device, message, model, [operand, invalidRank](Model* model) { in mutateOperandRankTest()
186 model->operands[operand].dimensions = std::vector<uint32_t>(invalidRank, 0); in mutateOperandRankTest()
218 for (size_t operand = 0; operand < model.operands.size(); ++operand) { in mutateOperandScaleTest() local
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| /hardware/interfaces/neuralnetworks/1.1/vts/functional/ |
| D | ValidateModel.cpp | 140 for (size_t operand = 0; operand < model.operands.size(); ++operand) { in mutateOperandTypeTest() local
143 std::to_string(operand) + " set to value " + in mutateOperandTypeTest()
145 validate(device, message, model, [operand, invalidOperandType](Model* model) { in mutateOperandTypeTest()
146 model->operands[operand].type = static_cast<OperandType>(invalidOperandType); in mutateOperandTypeTest()
170 for (size_t operand = 0; operand < model.operands.size(); ++operand) { in mutateOperandRankTest() local
171 const uint32_t invalidRank = getInvalidRank(model.operands[operand].type); in mutateOperandRankTest()
172 const std::string message = "mutateOperandRankTest: operand " + std::to_string(operand) + in mutateOperandRankTest()
174 validate(device, message, model, [operand, invalidRank](Model* model) { in mutateOperandRankTest()
175 model->operands[operand].dimensions = std::vector<uint32_t>(invalidRank, 0); in mutateOperandRankTest()
199 for (size_t operand = 0; operand < model.operands.size(); ++operand) { in mutateOperandScaleTest() local
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| /hardware/interfaces/neuralnetworks/1.0/ |
| D | types.hal | 22 * The type of an operand in a model.
1487 * How an operand is used.
1491 * The operand is internal to the model. It's created by an operation and
1492 * consumed by other operations. It must be an output operand of
1498 * The operand is an input of the model. It must not be an output
1499 * operand of any operation.
1501 * An operand can't be both input and output of a model.
1506 * The operand is an output of the model. It must be an output
1507 * operand of exactly one operation.
1509 * An operand can't be both input and output of a model.
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| /hardware/interfaces/neuralnetworks/1.2/ |
| D | IExecutionCallback.hal | 43 * operand buffer is not large enough to store the
49 * of the output operand in the Request outputs vector.
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| D | types.hal | 44 * Values of this operand type are either true or false. A zero value
71 * Values of this operand type are either true or false. A zero value
152 * The range of operand values in the OperandType enum.
4755 * Performance of an operation comes from the type of its first operand.
4756 * This represents performance for non extension operand types.
4778 * Performance by operand type. Must be sorted by OperandType.
4812 * Parameters for TENSOR_QUANT8_SYMM_PER_CHANNEL operand.
4822 * Describes one operand of the model's graph.
4835 * Dimensions of the operand.
4837 * For a scalar operand, dimensions.size() must be 0.
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| D | IPreparedModel.hal | 114 * operand buffer is not large enough to store the
120 * of the output operand in the Request outputs vector.
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| /hardware/interfaces/neuralnetworks/1.1/ |
| D | types.hal | 415 * The operations are sorted into execution order. Every operand
424 * Each value corresponds to the index of the operand in "operands".
431 * Each value corresponds to the index of the operand in "operands".
436 * A byte buffer containing operand data that were copied into the model.
438 * An operand's value must be located here if and only if Operand::lifetime
444 * A collection of shared memory pools containing operand values.
446 * An operand's value must be located here if and only if Operand::lifetime
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| /hardware/qcom/data/ipacfg-mgr/msm8998/ipacm/src/ |
| D | Android.mk | 44 -Wno-constant-logical-operand \
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