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():

from fastapi._compat import (
    ModelField,
    Undefined,
    _get_model_config,
    is_bytes_sequence_annotation,
    is_uploadfile_sequence_annotation,
)
from fastapi.testclient import TestClient
from pydantic import BaseConfig, BaseModel, ConfigDict
from pydantic.fields import FieldInfo

from .utils import needs_pydanticv1, needs_pydanticv2


@needs_pydanticv2
def test_model_field_default_required():
    # For coverage

    name: str,
    type_: Type[Any],
    class_validators: Optional[Dict[str, Validator]] = None,
    default: Optional[Any] = Undefined,
    required: Union[bool, UndefinedType] = Undefined,
    model_config: Type[BaseConfig] = BaseConfig,
    field_info: Optional[FieldInfo] = None,
    alias: Optional[str] = None,
    mode: Literal["validation", "serialization"] = "validation",
) -> ModelField:
    """