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// Generated file (from: conv_quant8_large.mod.py). Do not edit
void CreateModel(Model *model) {
OperandType type3(Type::INT32, {});
OperandType type2(Type::TENSOR_INT32, {3}, 0.25, 0);
OperandType type0(Type::TENSOR_QUANT8_ASYMM, {1, 2, 3, 3}, 0.5, 0);
OperandType type4(Type::TENSOR_QUANT8_ASYMM, {1, 2, 3, 3}, 1.0, 0);
OperandType type1(Type::TENSOR_QUANT8_ASYMM, {3, 1, 1, 3}, 0.5, 0);
// Phase 1, operands
auto op1 = model->addOperand(&type0);
auto op2 = model->addOperand(&type1);
auto op3 = model->addOperand(&type2);
auto pad0 = model->addOperand(&type3);
auto act = model->addOperand(&type3);
auto stride = model->addOperand(&type3);
auto op4 = model->addOperand(&type4);
// Phase 2, operations
static uint8_t op2_init[] = {1, 4, 7, 2, 5, 8, 3, 6, 9};
model->setOperandValue(op2, op2_init, sizeof(uint8_t) * 9);
static int32_t op3_init[] = {0, 0, 0};
model->setOperandValue(op3, op3_init, sizeof(int32_t) * 3);
static int32_t pad0_init[] = {0};
model->setOperandValue(pad0, pad0_init, sizeof(int32_t) * 1);
static int32_t act_init[] = {0};
model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
static int32_t stride_init[] = {1};
model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{op1},
{op4});
assert(model->isValid());
}
bool is_ignored(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
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