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// Generated file (from: fully_connected_quant8_2.mod.py). Do not edit
void CreateModel(Model *model) {
OperandType type4(Type::INT32, {});
OperandType type2(Type::TENSOR_INT32, {3}, 0.25f, 0);
OperandType type3(Type::TENSOR_QUANT8_ASYMM, {2, 3}, 1.f, 127);
OperandType type1(Type::TENSOR_QUANT8_ASYMM, {3, 10}, 0.5f, 127);
OperandType type0(Type::TENSOR_QUANT8_ASYMM, {4, 1, 5, 1}, 0.5f, 127);
// Phase 1, operands
auto op1 = model->addOperand(&type0);
auto op2 = model->addOperand(&type1);
auto b0 = model->addOperand(&type2);
auto op3 = model->addOperand(&type3);
auto act_relu = model->addOperand(&type4);
// Phase 2, operations
static uint8_t op2_init[] = {129, 131, 133, 135, 137, 139, 141, 143, 145, 147, 129, 131, 133, 135, 137, 139, 141, 143, 145, 147, 129, 131, 133, 135, 137, 139, 141, 143, 145, 147};
model->setOperandValue(op2, op2_init, sizeof(uint8_t) * 30);
static int32_t b0_init[] = {4, 8, 12};
model->setOperandValue(b0, b0_init, sizeof(int32_t) * 3);
static int32_t act_relu_init[] = {1};
model->setOperandValue(act_relu, act_relu_init, sizeof(int32_t) * 1);
model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act_relu}, {op3});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op1},
{op3});
assert(model->isValid());
}
bool is_ignored(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
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