},
                {
                    "type": "int_parsing",
                    "loc": ["query", "skip"],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "a",
                },
                {
                    "type": "int_parsing",
                    "loc": ["query", "limit"],

import re
import warnings
from dataclasses import is_dataclass
from typing import (
    TYPE_CHECKING,
    Any,
    Dict,
    MutableMapping,
    Optional,
    Set,
    Type,
    Union,
    cast,
)
from weakref import WeakKeyDictionary

import fastapi
from fastapi._compat import (
    PYDANTIC_V2,
    BaseConfig,
    ModelField,
    PydanticSchemaGenerationError,
    Undefined,
    UndefinedType,

    assert response.status_code == 422, response.text
    assert response.json() == IsDict(
        {
            "detail": [
                {
                    "type": "int_parsing",
                    "loc": ["body", "size"],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "XL",
                }
            ],

_STS_NS = {'sts': 'https://sts.amazonaws.com/doc/2011-06-15/'}


class STSElement(object):
    """STS aware XML parsing class. Wraps a root element name and
    cElementTree.Element instance. Provides STS namespace aware parsing
    functions.

    """

    def __init__(self, root_name, element):
        self.root_name = root_name
        self.element = element

    @classmethod

client = TestClient(app)


def test_get_enums_alexnet():
    response = client.get("/models/alexnet")
    assert response.status_code == 200
    assert response.json() == {"model_name": "alexnet", "message": "Deep Learning FTW!"}


def test_get_enums_lenet():
    response = client.get("/models/lenet")
    assert response.status_code == 200
    assert response.json() == {"model_name": "lenet", "message": "LeCNN all the images"}

    response = client.put("/items/foo", json=None)
    assert response.status_code == 422
    assert response.json() == IsDict(
        {
            "detail": [
                {
                    "type": "int_parsing",
                    "loc": ["path", "item_id"],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "foo",
                }
            ]

from tensorflow.python.util.lazy_loader import KerasLazyLoader as _KerasLazyLoader

# API IMPORTS PLACEHOLDER

# WRAPPER_PLACEHOLDER

if "dev" in __version__:   # pylint: disable=undefined-variable
  _logging.warning("""

  TensorFlow's `tf-nightly` package will soon be updated to TensorFlow 2.0.

  Please upgrade your code to TensorFlow 2.0:
    * https://www.tensorflow.org/guide/migrate

        {
            "detail": [
                {
                    "type": "int_parsing",
                    "loc": ["query", "q", 0],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "five",
                },
                {
                    "type": "int_parsing",
                    "loc": ["query", "q", 1],

app = FastAPI()


@app.get("/models/{model_name}")
async def get_model(model_name: ModelName):
    if model_name is ModelName.alexnet:
        return {"model_name": model_name, "message": "Deep Learning FTW!"}

    if model_name.value == "lenet":
        return {"model_name": model_name, "message": "LeCNN all the images"}

                    "loc": ["body", 0, "name"],
                    "msg": "Field required",
                    "input": {"age": "five"},
                },
                {
                    "type": "decimal_parsing",
                    "loc": ["body", 0, "age"],
                    "msg": "Input should be a valid decimal",
                    "input": "five",
                },
                {