blob: 493fd535af7f75d7f406b600a93a85c5cdd7b734 [file] [log] [blame]
// Generated from svdf_state.mod.py
// DO NOT EDIT
// clang-format off
#include "GeneratedTests.h"
namespace android::hardware::neuralnetworks::V1_0::generated_tests::svdf_state {
Model createTestModel() {
const std::vector<Operand> operands = {
{
.type = OperandType::TENSOR_FLOAT32,
.dimensions = {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 = {4, 3},
.numberOfConsumers = 1,
.scale = 0.0f,
.zeroPoint = 0,
.lifetime = OperandLifeTime::MODEL_INPUT,
.location = {.poolIndex = 0, .offset = 0, .length = 0},
},
{
.type = OperandType::TENSOR_FLOAT32,
.dimensions = {4, 10},
.numberOfConsumers = 1,
.scale = 0.0f,
.zeroPoint = 0,
.lifetime = OperandLifeTime::MODEL_INPUT,
.location = {.poolIndex = 0, .offset = 0, .length = 0},
},
{
.type = OperandType::TENSOR_FLOAT32,
.dimensions = {4},
.numberOfConsumers = 1,
.scale = 0.0f,
.zeroPoint = 0,
.lifetime = OperandLifeTime::MODEL_INPUT,
.location = {.poolIndex = 0, .offset = 0, .length = 0},
},
{
.type = OperandType::TENSOR_FLOAT32,
.dimensions = {2, 40},
.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::TENSOR_FLOAT32,
.dimensions = {2, 40},
.numberOfConsumers = 0,
.scale = 0.0f,
.zeroPoint = 0,
.lifetime = OperandLifeTime::MODEL_OUTPUT,
.location = {.poolIndex = 0, .offset = 0, .length = 0},
},
{
.type = OperandType::TENSOR_FLOAT32,
.dimensions = {2, 4},
.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::SVDF,
.inputs = {0, 1, 2, 3, 4, 5, 6},
.outputs = {7, 8},
}
};
const std::vector<uint32_t> inputIndexes = {0, 1, 2, 3, 4};
const std::vector<uint32_t> outputIndexes = {7, 8};
std::vector<uint8_t> operandValues = {
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_0::generated_tests::svdf_state
namespace android::hardware::neuralnetworks::V1_0::generated_tests::svdf_state {
Model createTestModel_all_inputs_as_internal() {
const std::vector<Operand> operands = {
{
.type = OperandType::TENSOR_FLOAT32,
.dimensions = {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 = {4, 3},
.numberOfConsumers = 1,
.scale = 0.0f,
.zeroPoint = 0,
.lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
.location = {.poolIndex = 0, .offset = 0, .length = 0},
},
{
.type = OperandType::TENSOR_FLOAT32,
.dimensions = {4, 10},
.numberOfConsumers = 1,
.scale = 0.0f,
.zeroPoint = 0,
.lifetime = OperandLifeTime::TEMPORARY_VARIABLE,
.location = {.poolIndex = 0, .offset = 0, .length = 0},
},
{
.type = OperandType::TENSOR_FLOAT32,
.dimensions = {4},
.numberOfConsumers = 1,
.scale = 0.0f,
.zeroPoint = 0,
.lifetime = OperandLifeTime::MODEL_INPUT,
.location = {.poolIndex = 0, .offset = 0, .length = 0},
},
{
.type = OperandType::TENSOR_FLOAT32,
.dimensions = {2, 40},
.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::TENSOR_FLOAT32,
.dimensions = {2, 40},
.numberOfConsumers = 0,
.scale = 0.0f,
.zeroPoint = 0,
.lifetime = OperandLifeTime::MODEL_OUTPUT,
.location = {.poolIndex = 0, .offset = 0, .length = 0},
},
{
.type = OperandType::TENSOR_FLOAT32,
.dimensions = {2, 4},
.numberOfConsumers = 0,
.scale = 0.0f,
.zeroPoint = 0,
.lifetime = OperandLifeTime::MODEL_OUTPUT,
.location = {.poolIndex = 0, .offset = 0, .length = 0},
},
{
.type = OperandType::TENSOR_FLOAT32,
.dimensions = {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 = 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 = {4, 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 = {4, 10},
.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 = {2, 40},
.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 = {9, 10, 11},
.outputs = {0},
},
{
.type = OperationType::ADD,
.inputs = {12, 13, 14},
.outputs = {1},
},
{
.type = OperationType::ADD,
.inputs = {15, 16, 17},
.outputs = {2},
},
{
.type = OperationType::ADD,
.inputs = {18, 19, 20},
.outputs = {4},
},
{
.type = OperationType::SVDF,
.inputs = {0, 1, 2, 3, 4, 5, 6},
.outputs = {7, 8},
}
};
const std::vector<uint32_t> inputIndexes = {3, 9, 12, 15, 18};
const std::vector<uint32_t> outputIndexes = {7, 8};
std::vector<uint8_t> operandValues = {
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, 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_0::generated_tests::svdf_state