async def METHOD_NAME(
    self,
    location: str,
    **kwargs: Any
) -> "_models.VirtualMachineSizeListResult":
    """Returns supported VM Sizes in a location.
    :param location: The location upon which virtual-machine-sizes is queried.
    :type location: str
    :keyword callable cls: A custom type or function that will be passed the direct response
    :return: VirtualMachineSizeListResult, or the result of cls(response)
    :rtype: ~azure.mgmt.machinelearningservices.models.VirtualMachineSizeListResult
    :raises: ~azure.core.exceptions.HttpResponseError
    """
    cls = kwargs.pop('cls', None)  # type: ClsType["_models.VirtualMachineSizeListResult"]
    error_map = {
        401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
    }
    error_map.update(kwargs.pop('error_map', {}))
    api_version = kwargs.pop('api_version', "2022-10-01-preview")  # type: str
    request = build_list_request(
        location=location,
        subscription_id=self._config.subscription_id,
        api_version=api_version,
        template_url=self.METHOD_NAME.metadata['url'],
    )
    request = _convert_request(request)
    request.url = self._client.format_url(request.url)
    pipeline_response = await self._client._pipeline.run(  # pylint: disable=protected-access
        request,
        stream=False,
        **kwargs
    )
    response = pipeline_response.http_response
    if response.status_code not in [200]:
        map_error(status_code=response.status_code, response=response, error_map=error_map)
        error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
        raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
    deserialized = self._deserialize('VirtualMachineSizeListResult', pipeline_response)
    if cls:
        return cls(pipeline_response, deserialized, {})
    return deserialized