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// Generated file (from: local_response_norm_float_3.mod.py). Do not edit
void CreateModel(Model *model) {
OperandType type2(Type::FLOAT32, {});
OperandType type1(Type::INT32, {});
OperandType type0(Type::TENSOR_FLOAT32, {1, 1, 1, 6});
// Phase 1, operands
auto input = model->addOperand(&type0);
auto radius = model->addOperand(&type1);
auto bias = model->addOperand(&type2);
auto alpha = model->addOperand(&type2);
auto beta = model->addOperand(&type2);
auto output = model->addOperand(&type0);
// Phase 2, operations
static int32_t radius_init[] = {20};
model->setOperandValue(radius, radius_init, sizeof(int32_t) * 1);
static float bias_init[] = {0.0f};
model->setOperandValue(bias, bias_init, sizeof(float) * 1);
static float alpha_init[] = {4.0f};
model->setOperandValue(alpha, alpha_init, sizeof(float) * 1);
static float beta_init[] = {0.5f};
model->setOperandValue(beta, beta_init, sizeof(float) * 1);
model->addOperation(ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION, {input, radius, bias, alpha, beta}, {output});
// Phase 3, inputs and outputs
model->identifyInputsAndOutputs(
{input},
{output});
assert(model->isValid());
}
bool is_ignored(int i) {
static std::set<int> ignore = {};
return ignore.find(i) != ignore.end();
}
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