return [pet1, pet2]


client = TestClient(app)


def test_filter_top_level_model():
    response = client.post(
        "/users", json={"email": "******@****.***", "password": "secret"}
    )
    assert response.json() == {"email": "******@****.***"}


def test_filter_second_level_model():
    response = client.get("/pets/1")
    assert response.json() == {
        "name": "Nibbler",

    name: str

    if PYDANTIC_V2:
        model_config = {
            "json_schema_extra": {
                "x-something-internal": {"level": 4},
            }
        }
    else:

        class Config:
            schema_extra = {
                "x-something-internal": {"level": 4},
            }


@app.get("/foo", response_model=Item)
def foo():
    return {"name": "Foo item"}

  Or install the latest stable TensorFlow 1.X release:
    * `pip install -U "tensorflow==1.*"`

  Otherwise your code may be broken by the change.

  """)

# Make sure directory containing top level submodules is in
# the __path__ so that "from tensorflow.foo import bar" works.
# We're using bitwise, but there's nothing special about that.
_API_MODULE = _sys.modules[__name__].bitwise  # pylint: disable=undefined-variable

    head_commit: PartialGithubEventHeadCommit


class PartialGithubEvent(BaseModel):
    workflow_run: PartialGithubEventWorkflowRun


if __name__ == "__main__":
    logging.basicConfig(level=logging.INFO)
    settings = Settings()
    logging.info(f"Using config: {settings.json()}")
    g = Github(settings.input_token.get_secret_value())
    repo = g.get_repo(settings.github_repository)
    try:

TensorFlow API v2 init files and is stored in the wheel file after the build.

See README.md file for "how to run" instruction.
"""

import logging
import unittest
import pkg_resources

logging.basicConfig(level=logging.INFO)


class ImportApiPackagesTest(unittest.TestCase):
  """ImportApiPackagesTest class. See description at the top of the file."""

  def setUp(self):
    def _get_api_packages_v2():