nn/tools/test_generator/tests/P_quantized_avgpool/stdout.txt.expect

// Generated file (from: averpoolfloat.mod.py). Do not edit
void CreateModel(Model *model) {
  OperandType type1(Type::INT32, {});
  OperandType type0(Type::TENSOR_QUANT8_ASYMM, 0.0f, 127.5f, {1, 2, 2, 1});
  // Phase 1, operands
  auto op1 = model->addOperand(&type0);
  auto cons1 = model->addOperand(&type1);
  auto act = model->addOperand(&type1);
  auto op3 = model->addOperand(&type0);
  // Phase 2, operations
  static int32_t cons1_init[] = {1};
  model->setOperandValue(cons1, cons1_init, sizeof(int32_t) * 1);
  static int32_t act_init[] = {0};
  model->setOperandValue(act, act_init, sizeof(int32_t) * 1);
  model->addOperation(ANEURALNETWORKS_AVERAGE_POOL, {op1, cons1, cons1, cons1, cons1, cons1, 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();
}
// Generated file (from: averpoolfloat.mod.py). Do not edit
// Begin of an example
{
//Input(s)
{ // See tools/test_generator/include/TestHarness.h:MixedTyped
  // int -> FLOAT32 map
  {},
  // int -> INT32 map
  {},
  // int -> QUANT8_ASYMM map
  {{0, {1, 2, 3, 4}}}
},
//Output(s)
{ // See tools/test_generator/include/TestHarness.h:MixedTyped
  // int -> FLOAT32 map
  {},
  // int -> INT32 map
  {},
  // int -> QUANT8_ASYMM map
  {{0, {1, 2, 3, 4}}}
}
}, // End of an example