from pdm.backend.hooks import Context

TIANGOLO_BUILD_PACKAGE = os.getenv("TIANGOLO_BUILD_PACKAGE", "fastapi")


def pdm_build_initialize(context: Context) -> None:
    metadata = context.config.metadata
    # Get custom config for the current package, from the env var
    config: Dict[str, Any] = context.config.data["tool"]["tiangolo"][
        "_internal-slim-build"
    ]["packages"][TIANGOLO_BUILD_PACKAGE]

sub-modules, as described below.

Note that the file `__init__.py` in the TensorFlow source code tree is actually
only a placeholder to enable test cases to run. The TensorFlow build replaces
this file with a file generated from [`api_template.__init__.py`](https://www.github.com/tensorflow/tensorflow/blob/master/tensorflow/api_template.__init__.py)
"""

{!../../../docs/missing-translation.md!}
"""

docs_path = Path("docs")
en_docs_path = Path("docs/en")
en_config_path: Path = en_docs_path / mkdocs_name
site_path = Path("site").absolute()
build_site_path = Path("site_build").absolute()


@lru_cache
def is_mkdocs_insiders() -> bool:
    version = metadata.version("mkdocs-material")
    return "insiders" in version


def get_en_config() -> Dict[str, Any]:

  if is_windows():
    test_and_build_filters += ['-no_windows', '-windows_excluded']
    if ((environ_cp.get('TF_NEED_CUDA', None) == '1') or
        (environ_cp.get('TF_NEED_ROCM', None) == '1')):
      test_and_build_filters += ['-no_windows_gpu', '-no_gpu']
    else:
      test_and_build_filters.append('-gpu')
  elif is_macos():
    test_and_build_filters += ['-gpu', '-nomac', '-no_mac', '-mac_excluded']

    security: Optional[List[Dict[str, List[str]]]] = None
    tags: Optional[List[Tag]] = None
    externalDocs: Optional[ExternalDocumentation] = None


_model_rebuild(Schema)
_model_rebuild(Operation)

    ) -> Any:
        return annotation

    def _normalize_errors(errors: Sequence[Any]) -> List[Dict[str, Any]]:
        return errors  # type: ignore[return-value]

    def _model_rebuild(model: Type[BaseModel]) -> None:
        model.model_rebuild()

    def _model_dump(
        model: BaseModel, mode: Literal["json", "python"] = "json", **kwargs: Any
    ) -> Any:
        return model.model_dump(mode=mode, **kwargs)