)

# Add Keras module aliases
_losses = _KerasLazyLoader(globals(), submodule="losses", name="losses")
_metrics = _KerasLazyLoader(globals(), submodule="metrics", name="metrics")
_optimizers = _KerasLazyLoader(
    globals(), submodule="optimizers", name="optimizers")
_initializers = _KerasLazyLoader(
    globals(), submodule="initializers", name="initializers")
setattr(_current_module, "losses", _losses)

setattr(_current_module, "flags", flags)

_major_api_version = 1

# Add module aliases from Keras to TF.
# Some tf endpoints actually lives under Keras.
_current_module.layers = _KerasLazyLoader(
    globals(),
    submodule="__internal__.legacy.layers",
    name="layers",
    mode="v1")
if _tf_uses_legacy_keras:
  _module_dir = _module_util.get_parent_dir_for_name(
      "tf_keras.api._v1.keras.__internal__.legacy.layers")
else:

    assert response.status_code == 200, response.text
    assert response.json() == {
        "sub_items": [{"name": "subitem", "sub_items": []}],
        "name": "item",
    }

    response = client.get("/items/recursive-submodel")
    assert response.status_code == 200, response.text
    assert response.json() == {
        "name": "item",
        "sub_items1": [
            {
                "name": "subitem",
                "sub_items2": [

    assert response.status_code == 200, response.text
    assert response.json() == {
        "sub_items": [{"name": "subitem", "sub_items": []}],
        "name": "item",
    }

    response = client.get("/items/recursive-submodel")
    assert response.status_code == 200, response.text
    assert response.json() == {
        "name": "item",
        "sub_items1": [
            {
                "name": "subitem",
                "sub_items2": [

@app.get("/items/recursive", response_model=RecursiveItem)
def get_recursive():
    return {"name": "item", "sub_items": [{"name": "subitem", "sub_items": []}]}


@app.get("/items/recursive-submodel", response_model=RecursiveItemViaSubmodel)
def get_recursive_submodel():
    return {
        "name": "item",
        "sub_items1": [
            {
                "name": "subitem",
                "sub_items2": [
                    {

@app.get("/items/recursive", response_model=RecursiveItem)
def get_recursive():
    return {"name": "item", "sub_items": [{"name": "subitem", "sub_items": []}]}


@app.get("/items/recursive-submodel", response_model=RecursiveItemViaSubmodel)
def get_recursive_submodel():
    return {
        "name": "item",
        "sub_items1": [
            {
                "name": "subitem",
                "sub_items2": [
                    {

from fastapi import FastAPI
from fastapi.testclient import TestClient
from pydantic import BaseModel

app = FastAPI()


class SubModel(BaseModel):
    a: Optional[str] = "foo"


class Model(BaseModel):
    x: Optional[int] = None
    sub: SubModel


class ModelSubclass(Model):
    y: int
    z: int = 0
    w: Optional[int] = None


class ModelDefaults(BaseModel):

            },
            "/response_model_filtering_model-annotation_submodel-return_submodel": {
                "get": {
                    "summary": "Response Model Filtering Model Annotation Submodel Return Submodel",
                    "operationId": "response_model_filtering_model_annotation_submodel_return_submodel_response_model_filtering_model_annotation_submodel_return_submodel_get",
                    "responses": {

                name=response_name,
                type_=self.response_model,
                mode="serialization",
            )
            # Create a clone of the field, so that a Pydantic submodel is not returned
            # as is just because it's an instance of a subclass of a more limited class
            # e.g. UserInDB (containing hashed_password) could be a subclass of User