| // Generated from conv_3_h3_w2_SAME.mod.py |
| // DO NOT EDIT |
| // clang-format off |
| #include "GeneratedTests.h" |
| |
| namespace android::hardware::neuralnetworks::V1_1::generated_tests::conv_3_h3_w2_SAME { |
| |
| Model createTestModel() { |
| const std::vector<Operand> operands = { |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1, 8, 8, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_INPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {3, 3, 2, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 0, .length = 216}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 216, .length = 12}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 228, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 232, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 236, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 240, .length = 4}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1, 8, 8, 3}, |
| .numberOfConsumers = 0, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_OUTPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| } |
| }; |
| |
| const std::vector<Operation> operations = { |
| { |
| .type = OperationType::CONV_2D, |
| .inputs = {0, 1, 2, 3, 4, 5, 6}, |
| .outputs = {7}, |
| } |
| }; |
| |
| const std::vector<uint32_t> inputIndexes = {0}; |
| const std::vector<uint32_t> outputIndexes = {7}; |
| std::vector<uint8_t> operandValues = { |
| 188, 89, 119, 191, 42, 87, 20, 191, 153, 43, 47, 191, 185, 251, 60, 63, 177, 191, 60, 62, 8, 105, 199, 61, 147, 27, 53, 190, 202, 26, 117, 190, 233, 189, 116, 185, 52, 132, 99, 61, 230, 61, 110, 190, 181, 255, 161, 190, 76, 107, 83, 188, 114, 51, 164, 62, 150, 63, 167, 190, 193, 111, 107, 191, 142, 58, 94, 63, 131, 25, 83, 191, 193, 88, 239, 190, 124, 102, 228, 60, 94, 48, 16, 63, 177, 167, 197, 62, 228, 135, 138, 190, 144, 249, 112, 191, 108, 123, 71, 191, 72, 226, 133, 190, 142, 89, 70, 191, 65, 241, 75, 191, 159, 31, 102, 62, 180, 32, 212, 190, 242, 150, 47, 63, 90, 212, 167, 190, 150, 33, 70, 63, 149, 238, 54, 191, 234, 236, 120, 191, 163, 143, 142, 61, 143, 112, 82, 191, 105, 169, 76, 191, 112, 235, 190, 62, 77, 243, 106, 191, 47, 134, 82, 63, 207, 45, 20, 190, 85, 51, 43, 190, 108, 63, 137, 62, 72, 224, 51, 63, 229, 14, 211, 190, 108, 121, 65, 63, 78, 183, 56, 63, 227, 107, 223, 190, 89, 192, 140, 190, 255, 207, 137, 190, 109, 226, 36, 62, 38, 226, 81, 63, 131, 191, 159, 190, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0 |
| }; |
| const std::vector<hidl_memory> pools = {}; |
| |
| return { |
| .operands = operands, |
| .operations = operations, |
| .inputIndexes = inputIndexes, |
| .outputIndexes = outputIndexes, |
| .operandValues = operandValues, |
| .pools = pools, |
| }; |
| } |
| |
| bool is_ignored(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |
| } // namespace android::hardware::neuralnetworks::V1_1::generated_tests::conv_3_h3_w2_SAME |
| namespace android::hardware::neuralnetworks::V1_1::generated_tests::conv_3_h3_w2_SAME { |
| |
| Model createTestModel_all_inputs_as_internal() { |
| const std::vector<Operand> operands = { |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1, 8, 8, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::TEMPORARY_VARIABLE, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {3, 3, 2, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 0, .length = 216}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 216, .length = 12}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 228, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 232, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 236, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 240, .length = 4}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1, 8, 8, 3}, |
| .numberOfConsumers = 0, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_OUTPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1, 8, 8, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_INPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 244, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 248, .length = 4}, |
| } |
| }; |
| |
| const std::vector<Operation> operations = { |
| { |
| .type = OperationType::ADD, |
| .inputs = {8, 9, 10}, |
| .outputs = {0}, |
| }, |
| { |
| .type = OperationType::CONV_2D, |
| .inputs = {0, 1, 2, 3, 4, 5, 6}, |
| .outputs = {7}, |
| } |
| }; |
| |
| const std::vector<uint32_t> inputIndexes = {8}; |
| const std::vector<uint32_t> outputIndexes = {7}; |
| std::vector<uint8_t> operandValues = { |
| 188, 89, 119, 191, 42, 87, 20, 191, 153, 43, 47, 191, 185, 251, 60, 63, 177, 191, 60, 62, 8, 105, 199, 61, 147, 27, 53, 190, 202, 26, 117, 190, 233, 189, 116, 185, 52, 132, 99, 61, 230, 61, 110, 190, 181, 255, 161, 190, 76, 107, 83, 188, 114, 51, 164, 62, 150, 63, 167, 190, 193, 111, 107, 191, 142, 58, 94, 63, 131, 25, 83, 191, 193, 88, 239, 190, 124, 102, 228, 60, 94, 48, 16, 63, 177, 167, 197, 62, 228, 135, 138, 190, 144, 249, 112, 191, 108, 123, 71, 191, 72, 226, 133, 190, 142, 89, 70, 191, 65, 241, 75, 191, 159, 31, 102, 62, 180, 32, 212, 190, 242, 150, 47, 63, 90, 212, 167, 190, 150, 33, 70, 63, 149, 238, 54, 191, 234, 236, 120, 191, 163, 143, 142, 61, 143, 112, 82, 191, 105, 169, 76, 191, 112, 235, 190, 62, 77, 243, 106, 191, 47, 134, 82, 63, 207, 45, 20, 190, 85, 51, 43, 190, 108, 63, 137, 62, 72, 224, 51, 63, 229, 14, 211, 190, 108, 121, 65, 63, 78, 183, 56, 63, 227, 107, 223, 190, 89, 192, 140, 190, 255, 207, 137, 190, 109, 226, 36, 62, 38, 226, 81, 63, 131, 191, 159, 190, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 |
| }; |
| const std::vector<hidl_memory> pools = {}; |
| |
| return { |
| .operands = operands, |
| .operations = operations, |
| .inputIndexes = inputIndexes, |
| .outputIndexes = outputIndexes, |
| .operandValues = operandValues, |
| .pools = pools, |
| }; |
| } |
| |
| bool is_ignored_all_inputs_as_internal(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |
| } // namespace android::hardware::neuralnetworks::V1_1::generated_tests::conv_3_h3_w2_SAME |
| namespace android::hardware::neuralnetworks::V1_1::generated_tests::conv_3_h3_w2_SAME { |
| |
| Model createTestModel_all_tensors_as_inputs() { |
| const std::vector<Operand> operands = { |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1, 8, 8, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_INPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {3, 3, 2, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_INPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_INPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 0, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 4, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 8, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 12, .length = 4}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1, 8, 8, 3}, |
| .numberOfConsumers = 0, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_OUTPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| } |
| }; |
| |
| const std::vector<Operation> operations = { |
| { |
| .type = OperationType::CONV_2D, |
| .inputs = {0, 1, 2, 3, 4, 5, 6}, |
| .outputs = {7}, |
| } |
| }; |
| |
| const std::vector<uint32_t> inputIndexes = {0, 1, 2}; |
| const std::vector<uint32_t> outputIndexes = {7}; |
| std::vector<uint8_t> operandValues = { |
| 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0 |
| }; |
| const std::vector<hidl_memory> pools = {}; |
| |
| return { |
| .operands = operands, |
| .operations = operations, |
| .inputIndexes = inputIndexes, |
| .outputIndexes = outputIndexes, |
| .operandValues = operandValues, |
| .pools = pools, |
| }; |
| } |
| |
| bool is_ignored_all_tensors_as_inputs(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |
| } // namespace android::hardware::neuralnetworks::V1_1::generated_tests::conv_3_h3_w2_SAME |
| namespace android::hardware::neuralnetworks::V1_1::generated_tests::conv_3_h3_w2_SAME { |
| |
| Model createTestModel_all_tensors_as_inputs_all_inputs_as_internal() { |
| const std::vector<Operand> operands = { |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1, 8, 8, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::TEMPORARY_VARIABLE, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {3, 3, 2, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::TEMPORARY_VARIABLE, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::TEMPORARY_VARIABLE, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 0, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 4, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 8, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 12, .length = 4}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1, 8, 8, 3}, |
| .numberOfConsumers = 0, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_OUTPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1, 8, 8, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_INPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 16, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 20, .length = 4}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {3, 3, 2, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_INPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 24, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 28, .length = 4}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_INPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 32, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 36, .length = 4}, |
| } |
| }; |
| |
| const std::vector<Operation> operations = { |
| { |
| .type = OperationType::ADD, |
| .inputs = {8, 9, 10}, |
| .outputs = {0}, |
| }, |
| { |
| .type = OperationType::ADD, |
| .inputs = {11, 12, 13}, |
| .outputs = {1}, |
| }, |
| { |
| .type = OperationType::ADD, |
| .inputs = {14, 15, 16}, |
| .outputs = {2}, |
| }, |
| { |
| .type = OperationType::CONV_2D, |
| .inputs = {0, 1, 2, 3, 4, 5, 6}, |
| .outputs = {7}, |
| } |
| }; |
| |
| const std::vector<uint32_t> inputIndexes = {8, 11, 14}; |
| const std::vector<uint32_t> outputIndexes = {7}; |
| std::vector<uint8_t> operandValues = { |
| 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 |
| }; |
| const std::vector<hidl_memory> pools = {}; |
| |
| return { |
| .operands = operands, |
| .operations = operations, |
| .inputIndexes = inputIndexes, |
| .outputIndexes = outputIndexes, |
| .operandValues = operandValues, |
| .pools = pools, |
| }; |
| } |
| |
| bool is_ignored_all_tensors_as_inputs_all_inputs_as_internal(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |
| } // namespace android::hardware::neuralnetworks::V1_1::generated_tests::conv_3_h3_w2_SAME |
| namespace android::hardware::neuralnetworks::V1_1::generated_tests::conv_3_h3_w2_SAME { |
| |
| Model createTestModel_2() { |
| const std::vector<Operand> operands = { |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1, 8, 8, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_INPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {3, 3, 2, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 0, .length = 216}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 216, .length = 12}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 228, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 232, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 236, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 240, .length = 4}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1, 8, 8, 3}, |
| .numberOfConsumers = 0, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_OUTPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| } |
| }; |
| |
| const std::vector<Operation> operations = { |
| { |
| .type = OperationType::CONV_2D, |
| .inputs = {0, 1, 2, 3, 4, 5, 6}, |
| .outputs = {7}, |
| } |
| }; |
| |
| const std::vector<uint32_t> inputIndexes = {0}; |
| const std::vector<uint32_t> outputIndexes = {7}; |
| std::vector<uint8_t> operandValues = { |
| 188, 89, 119, 191, 42, 87, 20, 191, 153, 43, 47, 191, 185, 251, 60, 63, 177, 191, 60, 62, 8, 105, 199, 61, 147, 27, 53, 190, 202, 26, 117, 190, 233, 189, 116, 185, 52, 132, 99, 61, 230, 61, 110, 190, 181, 255, 161, 190, 76, 107, 83, 188, 114, 51, 164, 62, 150, 63, 167, 190, 193, 111, 107, 191, 142, 58, 94, 63, 131, 25, 83, 191, 193, 88, 239, 190, 124, 102, 228, 60, 94, 48, 16, 63, 177, 167, 197, 62, 228, 135, 138, 190, 144, 249, 112, 191, 108, 123, 71, 191, 72, 226, 133, 190, 142, 89, 70, 191, 65, 241, 75, 191, 159, 31, 102, 62, 180, 32, 212, 190, 242, 150, 47, 63, 90, 212, 167, 190, 150, 33, 70, 63, 149, 238, 54, 191, 234, 236, 120, 191, 163, 143, 142, 61, 143, 112, 82, 191, 105, 169, 76, 191, 112, 235, 190, 62, 77, 243, 106, 191, 47, 134, 82, 63, 207, 45, 20, 190, 85, 51, 43, 190, 108, 63, 137, 62, 72, 224, 51, 63, 229, 14, 211, 190, 108, 121, 65, 63, 78, 183, 56, 63, 227, 107, 223, 190, 89, 192, 140, 190, 255, 207, 137, 190, 109, 226, 36, 62, 38, 226, 81, 63, 131, 191, 159, 190, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0 |
| }; |
| const std::vector<hidl_memory> pools = {}; |
| |
| return { |
| .operands = operands, |
| .operations = operations, |
| .inputIndexes = inputIndexes, |
| .outputIndexes = outputIndexes, |
| .operandValues = operandValues, |
| .pools = pools, |
| }; |
| } |
| |
| bool is_ignored_2(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |
| } // namespace android::hardware::neuralnetworks::V1_1::generated_tests::conv_3_h3_w2_SAME |
| namespace android::hardware::neuralnetworks::V1_1::generated_tests::conv_3_h3_w2_SAME { |
| |
| Model createTestModel_all_inputs_as_internal_2() { |
| const std::vector<Operand> operands = { |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1, 8, 8, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::TEMPORARY_VARIABLE, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {3, 3, 2, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 0, .length = 216}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 216, .length = 12}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 228, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 232, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 236, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 240, .length = 4}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1, 8, 8, 3}, |
| .numberOfConsumers = 0, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_OUTPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1, 8, 8, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_INPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 244, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 248, .length = 4}, |
| } |
| }; |
| |
| const std::vector<Operation> operations = { |
| { |
| .type = OperationType::ADD, |
| .inputs = {8, 9, 10}, |
| .outputs = {0}, |
| }, |
| { |
| .type = OperationType::CONV_2D, |
| .inputs = {0, 1, 2, 3, 4, 5, 6}, |
| .outputs = {7}, |
| } |
| }; |
| |
| const std::vector<uint32_t> inputIndexes = {8}; |
| const std::vector<uint32_t> outputIndexes = {7}; |
| std::vector<uint8_t> operandValues = { |
| 188, 89, 119, 191, 42, 87, 20, 191, 153, 43, 47, 191, 185, 251, 60, 63, 177, 191, 60, 62, 8, 105, 199, 61, 147, 27, 53, 190, 202, 26, 117, 190, 233, 189, 116, 185, 52, 132, 99, 61, 230, 61, 110, 190, 181, 255, 161, 190, 76, 107, 83, 188, 114, 51, 164, 62, 150, 63, 167, 190, 193, 111, 107, 191, 142, 58, 94, 63, 131, 25, 83, 191, 193, 88, 239, 190, 124, 102, 228, 60, 94, 48, 16, 63, 177, 167, 197, 62, 228, 135, 138, 190, 144, 249, 112, 191, 108, 123, 71, 191, 72, 226, 133, 190, 142, 89, 70, 191, 65, 241, 75, 191, 159, 31, 102, 62, 180, 32, 212, 190, 242, 150, 47, 63, 90, 212, 167, 190, 150, 33, 70, 63, 149, 238, 54, 191, 234, 236, 120, 191, 163, 143, 142, 61, 143, 112, 82, 191, 105, 169, 76, 191, 112, 235, 190, 62, 77, 243, 106, 191, 47, 134, 82, 63, 207, 45, 20, 190, 85, 51, 43, 190, 108, 63, 137, 62, 72, 224, 51, 63, 229, 14, 211, 190, 108, 121, 65, 63, 78, 183, 56, 63, 227, 107, 223, 190, 89, 192, 140, 190, 255, 207, 137, 190, 109, 226, 36, 62, 38, 226, 81, 63, 131, 191, 159, 190, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 |
| }; |
| const std::vector<hidl_memory> pools = {}; |
| |
| return { |
| .operands = operands, |
| .operations = operations, |
| .inputIndexes = inputIndexes, |
| .outputIndexes = outputIndexes, |
| .operandValues = operandValues, |
| .pools = pools, |
| }; |
| } |
| |
| bool is_ignored_all_inputs_as_internal_2(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |
| } // namespace android::hardware::neuralnetworks::V1_1::generated_tests::conv_3_h3_w2_SAME |
| namespace android::hardware::neuralnetworks::V1_1::generated_tests::conv_3_h3_w2_SAME { |
| |
| Model createTestModel_all_tensors_as_inputs_2() { |
| const std::vector<Operand> operands = { |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1, 8, 8, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_INPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {3, 3, 2, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_INPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_INPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 0, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 4, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 8, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 12, .length = 4}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1, 8, 8, 3}, |
| .numberOfConsumers = 0, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_OUTPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| } |
| }; |
| |
| const std::vector<Operation> operations = { |
| { |
| .type = OperationType::CONV_2D, |
| .inputs = {0, 1, 2, 3, 4, 5, 6}, |
| .outputs = {7}, |
| } |
| }; |
| |
| const std::vector<uint32_t> inputIndexes = {0, 1, 2}; |
| const std::vector<uint32_t> outputIndexes = {7}; |
| std::vector<uint8_t> operandValues = { |
| 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0 |
| }; |
| const std::vector<hidl_memory> pools = {}; |
| |
| return { |
| .operands = operands, |
| .operations = operations, |
| .inputIndexes = inputIndexes, |
| .outputIndexes = outputIndexes, |
| .operandValues = operandValues, |
| .pools = pools, |
| }; |
| } |
| |
| bool is_ignored_all_tensors_as_inputs_2(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |
| } // namespace android::hardware::neuralnetworks::V1_1::generated_tests::conv_3_h3_w2_SAME |
| namespace android::hardware::neuralnetworks::V1_1::generated_tests::conv_3_h3_w2_SAME { |
| |
| Model createTestModel_all_tensors_as_inputs_all_inputs_as_internal_2() { |
| const std::vector<Operand> operands = { |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1, 8, 8, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::TEMPORARY_VARIABLE, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {3, 3, 2, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::TEMPORARY_VARIABLE, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::TEMPORARY_VARIABLE, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 0, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 4, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 8, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 12, .length = 4}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1, 8, 8, 3}, |
| .numberOfConsumers = 0, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_OUTPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1, 8, 8, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_INPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 16, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 20, .length = 4}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {3, 3, 2, 3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_INPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 24, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 28, .length = 4}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {3}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::MODEL_INPUT, |
| .location = {.poolIndex = 0, .offset = 0, .length = 0}, |
| }, |
| { |
| .type = OperandType::TENSOR_FLOAT32, |
| .dimensions = {1}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 32, .length = 4}, |
| }, |
| { |
| .type = OperandType::INT32, |
| .dimensions = {}, |
| .numberOfConsumers = 1, |
| .scale = 0.0f, |
| .zeroPoint = 0, |
| .lifetime = OperandLifeTime::CONSTANT_COPY, |
| .location = {.poolIndex = 0, .offset = 36, .length = 4}, |
| } |
| }; |
| |
| const std::vector<Operation> operations = { |
| { |
| .type = OperationType::ADD, |
| .inputs = {8, 9, 10}, |
| .outputs = {0}, |
| }, |
| { |
| .type = OperationType::ADD, |
| .inputs = {11, 12, 13}, |
| .outputs = {1}, |
| }, |
| { |
| .type = OperationType::ADD, |
| .inputs = {14, 15, 16}, |
| .outputs = {2}, |
| }, |
| { |
| .type = OperationType::CONV_2D, |
| .inputs = {0, 1, 2, 3, 4, 5, 6}, |
| .outputs = {7}, |
| } |
| }; |
| |
| const std::vector<uint32_t> inputIndexes = {8, 11, 14}; |
| const std::vector<uint32_t> outputIndexes = {7}; |
| std::vector<uint8_t> operandValues = { |
| 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 |
| }; |
| const std::vector<hidl_memory> pools = {}; |
| |
| return { |
| .operands = operands, |
| .operations = operations, |
| .inputIndexes = inputIndexes, |
| .outputIndexes = outputIndexes, |
| .operandValues = operandValues, |
| .pools = pools, |
| }; |
| } |
| |
| bool is_ignored_all_tensors_as_inputs_all_inputs_as_internal_2(int i) { |
| static std::set<int> ignore = {}; |
| return ignore.find(i) != ignore.end(); |
| } |
| |
| } // namespace android::hardware::neuralnetworks::V1_1::generated_tests::conv_3_h3_w2_SAME |
