docstr: Simplified way to call the synthetic function and pass the argument
  numbers directly, e.g. `branin(2.0, 3.0)`.
code: def __call__(
      self,
      *args: Union[int, float, np.ndarray],
      **kwargs: Union[int, float, np.ndarray],
  ) -> Union[float, np.ndarray]:
      """Simplified way to call the synthetic function and pass the argument
      numbers directly, e.g. `branin(2.0, 3.0)`.
      """
      if kwargs:
          if self.required_dimensionality:
              assert (
                  len(kwargs) == self.required_dimensionality
                  or len(kwargs) == 1
              ), (
                  f"Function {self.name} expected either "
                  f"{self.required_dimensionality} arguments "
                  "or a single numpy array argument."
              )
          assert not args, (
              f"Function {self.name} expected either all anonymous "
              "arguments or all keyword arguments."
          )
          args = list(kwargs.values())  # pyre-ignore[9]
      for x in args:
          if isinstance(x, np.ndarray):
              return self.f(X=x)
          assert np.isscalar(
              x
          ), f"Expected numerical arguments or numpy arrays, got {type(x)}."
          if isinstance(x, int):
              x = float(x)
      return checked_cast(float, self.f(np.array(args)))
  
imports: from abc import ABC, abstractmethod
  from typing import Any, Callable, List, Optional, Tuple, Union
  import numpy
  import torch
  from ax.utils.common.docutils import copy_doc
  from ax.utils.common.typeutils import checked_cast, not_none
  from botorch.test_functions import synthetic
label_desc: Use image node_id 2 for calling the SyntheticFunction obj's underlying member method code with example usage: obj.__call__() and returns: checked_cast, self