{
    AbstractContext* ctx_raw = nullptr;
    Status s =
        BuildImmediateExecutionContext(std::get<1>(GetParam()), &ctx_raw);
    ASSERT_EQ(errors::OK, s.code()) << s.message();
    ctx.reset(ctx_raw);
  }

  AbstractTensorHandlePtr x;
  {
    AbstractTensorHandle* x_raw = nullptr;
    Status s = TestScalarTensorHandle<float, TF_FLOAT>(ctx.get(), 1.0f, &x_raw);

//
// +k8s:deepcopy-gen=true
// +protobuf=true
// +k8s:openapi-gen=true
message RawExtension {
  // Raw is the underlying serialization of this object.
  //
  // TODO: Determine how to detect ContentType and ContentEncoding of 'Raw' data.
  optional bytes raw = 1;
}

// TypeMeta is shared by all top level objects. The proper way to use it is to inline it in your type,
// like this:
//

from fastapi import FastAPI, Request

app = FastAPI()


def magic_data_reader(raw_body: bytes):
    return {
        "size": len(raw_body),
        "content": {
            "name": "Maaaagic",
            "price": 42,
            "description": "Just kiddin', no magic here. ✨",
        },
    }


@app.post(
    "/items/",
    openapi_extra={
        "requestBody": {
            "content": {

     * undergone any updates by the model builder, e.g. reflects neither inheritance nor interpolation. The model
     * identifier should be from the collection obtained by {@link #getModelIds()}. As a special case, an empty string
     * can be used as the identifier for the super POM.
     *
     * @param modelId The identifier of the desired raw model, must not be {@code null}.

}

const (
	healthCapacityRawTotalBytes    = "capacity_raw_total_bytes"
	healthCapacityRawFreeBytes     = "capacity_raw_free_bytes"
	healthCapacityUsableTotalBytes = "capacity_usable_total_bytes"
	healthCapacityUsableFreeBytes  = "capacity_usable_free_bytes"
)

var (
	healthCapacityRawTotalBytesMD = NewGaugeMD(healthCapacityRawTotalBytes,
		"Total cluster raw storage capacity in bytes")

  std::vector<const char*> raw_strs;
  std::vector<size_t> lengths;
  raw_strs.reserve(values.size());
  lengths.reserve(values.size());
  for (const auto& s : values) {
    raw_strs.emplace_back(s.data());
    lengths.emplace_back(s.size());
  }
  return SetAttrStringList(attr_name,
                           reinterpret_cast<const void**>(raw_strs.data()),

      hpackWriter.writeHeaders(case.headersList)
      newCases += case.copy(wire = bytesOut.readByteString())
    }

    testDecoder(story.copy(cases = newCases))
  }

  companion object {
    private val RAW_DATA = arrayOf("raw-data")
  }

	b.ResetTimer()
	for x := 0; x < b.N; x++ {
		DB.Raw("select * from users where id = ?", user.ID).Scan(&u)
	}
}

func BenchmarkScanSlice(b *testing.B) {
	DB.Exec("delete from users")
	for i := 0; i < 10_000; i++ {
		user := *GetUser(fmt.Sprintf("scan-%d", i), Config{})
		DB.Create(&user)
	}

	var u []User
	b.ResetTimer()
	for x := 0; x < b.N; x++ {
		DB.Raw("select * from users").Scan(&u)
	}
}

            "content": {"application/x-yaml": {"schema": Item.schema()}},
            "required": True,
        },
    },
)
async def create_item(request: Request):
    raw_body = await request.body()
    try:
        data = yaml.safe_load(raw_body)
    except yaml.YAMLError:
        raise HTTPException(status_code=422, detail="Invalid YAML")
    try:
        item = Item.parse_obj(data)
    except ValidationError as e:

class UserIn(UserBase):
    password: str


class UserOut(UserBase):
    pass


class UserInDB(UserBase):
    hashed_password: str


def fake_password_hasher(raw_password: str):
    return "supersecret" + raw_password


def fake_save_user(user_in: UserIn):
    hashed_password = fake_password_hasher(user_in.password)
    user_in_db = UserInDB(**user_in.dict(), hashed_password=hashed_password)