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// Generated file (from: fully_connected_float_4d_simple.mod.py). Do not edit
void CreateModel(Model *model) {
OperandType type4(Type::INT32, {});
OperandType type3(Type::TENSOR_FLOAT32, {2, 3});
OperandType type1(Type::TENSOR_FLOAT32, {3, 10});
OperandType type2(Type::TENSOR_FLOAT32, {3});
OperandType type0(Type::TENSOR_FLOAT32, {4, 1, 5, 1});
// 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 = model->addOperand(&type4);
// Phase 2, operations
static float op2_init[] = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f};
model->setOperandValue(op2, op2_init, sizeof(float) * 30);
static float b0_init[] = {1.0f, 2.0f, 3.0f};
model->setOperandValue(b0, b0_init, sizeof(float) * 3);
static int32_t act_init[] = {0};
model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
model->addOperation(ANEURALNETWORKS_FULLY_CONNECTED, {op1, op2, b0, act}, {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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