code: def check_duplicate(point: np.ndarray, points: np.ndarray) -> bool:
      """Check if a point exists in another array.
  
      Args:
          point: Newly generated point to check.
          points: Points previously generated.
  
      Returns:
          True if the point is contained in points, else False
      """
      for p in points:
          if np.array_equal(p, point):
              return True
      return False
  
imports: from __future__ import annotations
  import itertools
  import warnings
  from typing import Callable, Dict, List, Optional, Protocol, Set, Tuple, Union
  import numpy
  import torch
  from ax.core.search_space import SearchSpaceDigest
  from ax.exceptions.core import SearchSpaceExhausted, UnsupportedError
  from ax.models.types import TConfig
  from ax.utils.common.typeutils import checked_cast
  from botorch.acquisition.risk_measures import RiskMeasureMCObjective
  from torch import Tensor
label_desc: Use image node_id 2 for calling a global function with example usage: check_duplicate(point, points) and returns: False, True