labels: 'TFLiteConverter'

---

### 1. System information

- OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
- TensorFlow installation (pip package or built from source):
- TensorFlow library (version, if pip package or github SHA, if built from source):

### 2. Code

Provide code to help us reproduce your issues using one of the following options:

#### Option A: Reference colab notebooks

    void flush();

    /**
     * Registers the specified cache record for usage with the given project. Integrators can use the information
     * collected from this method in combination with a custom cache implementation to dispose unused records from the
     * cache.
     *
     * @param project The project that employs the plugin realm, must not be {@code null}.

@SuppressWarnings("checkstyle:UnusedLocalVariable")
class ProjectInheritanceTest extends AbstractProjectInheritanceTestCase {
    // ----------------------------------------------------------------------
    //
    // p1 inherits from p0
    // p0 inherits from super model
    //
    // or we can show it graphically as:
    //
    // p1 ---> p0 --> super model
    //
    // ----------------------------------------------------------------------

    @Test

from fastapi.testclient import TestClient

from docs_src.generate_clients.tutorial003_py39 import app

client = TestClient(app)


def test_post_items():
    response = client.post("/items/", json={"name": "Foo", "price": 5})
    assert response.status_code == 200, response.text
    assert response.json() == {"message": "Item received"}


def test_post_users():
    response = client.post(

import importlib

import pytest
from fastapi.testclient import TestClient

from ...utils import needs_py310


@pytest.fixture(
    name="client",
    params=[
        pytest.param("tutorial006c_py39"),
        pytest.param("tutorial006c_py310", marks=needs_py310),
        pytest.param("tutorial006c_an_py39"),
        pytest.param("tutorial006c_an_py310", marks=needs_py310),
    ],
)
def get_client(request: pytest.FixtureRequest):

from fastapi import FastAPI, Response
from fastapi.responses import RedirectResponse

app = FastAPI()


@app.get("/portal", response_model=None)
async def get_portal(teleport: bool = False) -> Response | dict:
    if teleport:
        return RedirectResponse(url="https://www.youtube.com/watch?v=dQw4w9WgXcQ")

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str


items = [
    {"name": "Foo", "description": "There comes my hero"},
    {"name": "Red", "description": "It's my aeroplane"},
]


@app.get("/items/", response_model=list[Item])
async def read_items():

from enum import Enum

from fastapi import FastAPI

app = FastAPI()


class Tags(Enum):
    items = "items"
    users = "users"


@app.get("/items/", tags=[Tags.items])
async def get_items():
    return ["Portal gun", "Plumbus"]


@app.get("/users/", tags=[Tags.users])
async def read_users():

from typing import Annotated

from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(
    q: Annotated[
        str | None, Query(min_length=3, max_length=50, regex="^fixedquery$")
    ] = None,
):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})

from typing import Annotated

from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(
    q: Annotated[str | None, Query(title="Query string", min_length=3)] = None,
):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})