code: def __call__(
      self, v: Union[float, Sequence[float], torch.Tensor, np.ndarray]
  ) -> Union[float, Sequence[float], torch.Tensor, np.ndarray]:
      if isinstance(v, torch.Tensor):
          return v.clamp(self._min, self._max)
      elif isinstance(v, np.ndarray):
          return v.clip(self._min, self._max)
      elif isinstance(v, Sequence):
          return [max(self._min, min(self._max, float(i))) for i in v]
      else:
          return max(self._min, min(self._max, float(v)))
  
imports: import math
  from collections import OrderedDict
  from typing import Sequence, Union
  import numpy
  import torch
label_desc: Use image node_id 2 for calling the Clamper obj's underlying member method code with example usage: obj.__call__(v) and returns: v, v, unknown, max