code: def best_other_classes(
      logits: ep.Tensor, exclude: ep.Tensor
  ) -> ep.Tensor:
      other_logits = logits - ep.onehot_like(
          logits, exclude, value=ep.inf
      )
      return other_logits.argmax(axis=-1)
  
imports: from typing import Union, Tuple, Any, Optional
  from functools import partial
  import numpy
  import eagerpy
  from ..devutils import flatten
  from ..devutils import atleast_kd
  from ..types import Bounds
  from ..models import Model
  from ..distances import l2
  from ..criteria import Misclassification
  from ..criteria import TargetedMisclassification
  from .base import MinimizationAttack
  from .base import T
  from .base import get_criterion
  from .base import raise_if_kwargs
  from .base import verify_input_bounds
  from .gradient_descent_base import AdamOptimizer
label_desc: Use image node_id 1 for calling a global function with example usage: best_other_classes(logits, exclude) and returns: other_logits