const XlaCompilationResult& compilation_result, llvm::raw_ostream& output) {
  const xla::HloModuleConfig module_config(
      compilation_result.computation->GetProgramShape().value());
  auto status_or_hlo_module = xla::HloModule::CreateFromProto(
      compilation_result.computation->proto(), module_config);
  if (!status_or_hlo_module.ok()) {
    LOG(ERROR) << "Conversion to HLO module failed: "

            {
                "type_": type_,
                "class_validators": class_validators,
                "default": default,
                "required": required,
                "model_config": model_config,
                "alias": alias,
            }
        )
    try:
        return ModelField(**kwargs)  # type: ignore[arg-type]
    except (RuntimeError, PydanticSchemaGenerationError):

class RoleEnum(Enum):
    admin = "admin"
    normal = "normal"


class ModelWithConfig(BaseModel):
    role: Optional[RoleEnum] = None

    if PYDANTIC_V2:
        model_config = {"use_enum_values": True}
    else:

        class Config:
            use_enum_values = True


class ModelWithAlias(BaseModel):
    foo: str = Field(alias="Foo")

=== "Pydantic v2"

    ```Python hl_lines="9"
    {!> ../../../docs_src/settings/app03_an/config.py!}
    ```

    !!! tip
        The `model_config` attribute is used just for Pydantic configuration. You can read more at <a href="https://docs.pydantic.dev/latest/usage/model_config/" class="external-link" target="_blank">Pydantic Model Config</a>.

=== "Pydantic v1"

    ```Python hl_lines="9-10"

=== "Pydantic v2"

    In Pydantic version 2, you would use the attribute `model_config`, that takes a `dict` as described in <a href="https://docs.pydantic.dev/latest/usage/model_config/" class="external-link" target="_blank">Pydantic's docs: Model Config</a>.

!!! info

Diese zusätzlichen Informationen werden unverändert zum für dieses Modell ausgegebenen **JSON-Schema** hinzugefügt und in der API-Dokumentation verwendet.

=== "Pydantic v2"

    In Pydantic Version 2 würden Sie das Attribut `model_config` verwenden, das ein `dict` akzeptiert, wie beschrieben in <a href="https://docs.pydantic.dev/latest/api/config/" class="external-link" target="_blank">Pydantic-Dokumentation: Configuration</a>.

        ) -> CoreSchema:
            return with_info_plain_validator_function(cls._validate)


class BaseModelWithConfig(BaseModel):
    if PYDANTIC_V2:
        model_config = {"extra": "allow"}

    else:

        class Config:
            extra = "allow"


class Contact(BaseModelWithConfig):
    name: Optional[str] = None
    url: Optional[AnyUrl] = None

    ) -> Any:
        return model.model_dump(mode=mode, **kwargs)

    def _get_model_config(model: BaseModel) -> Any:
        return model.model_config

    def get_schema_from_model_field(
        *,
        field: ModelField,
        schema_generator: GenerateJsonSchema,
        model_name_map: ModelNameMap,
        field_mapping: Dict[

    * You can read more about it in the docs for [Declare Request Example Data](https://fastapi.tiangolo.com/tutorial/schema-extra-example/).
* The attribute `schema_extra` for the internal class `Config` has been replaced by the key `json_schema_extra` in the new `model_config` dict.