class_docstr: Track the min and max values of the observations in each batch.
docstr: Update the min and max values.
code: def update(self, predictions: Tensor, *args, **kwargs) -> None:
      """Update the min and max values."""
      del args, kwargs  # These variables are not used.
  
      self.max = torch.max(self.max, torch.max(predictions))
      self.min = torch.min(self.min, torch.min(predictions))
  
file_path: anomalib/src/anomalib/utils/metrics/min_max.py
imports: from __future__ import annotations
  import torch
  from torch import Tensor
  from torchmetrics import Metric
label_desc: Use image node_id 2 for calling the MinMax obj's underlying member method code with example usage: obj.update(predictions) without return types