code: def uniform_l1_n_balls(
      dummy: ep.Tensor, batch_size: int, n: int
  ) -> ep.Tensor:
      # https://mathoverflow.net/a/9188
      u = ep.uniform(dummy, (batch_size, n))
      v = u.sort(axis=-1)
      vp = ep.concatenate(
          [ep.zeros(v, (batch_size, 1)), v[:, : n - 1]], axis=-1
      )
      assert v.shape == vp.shape
      x = v - vp
      sign = ep.uniform(
          dummy, (batch_size, n), low=-1.0, high=1.0
      ).sign()
      return sign * x
  
imports: from typing import Union, Any, Optional, Callable, Tuple
  from abc import ABC, abstractmethod
  import eagerpy
  from ..devutils import flatten
  from ..devutils import atleast_kd
  from ..types import Bounds
  from ..models.base import Model
  from ..criteria import Misclassification, TargetedMisclassification
  from ..distances import l1, l2, linf
  from .base import FixedEpsilonAttack
  from .base import T
  from .base import get_criterion
  from .base import raise_if_kwargs
  from .base import verify_input_bounds
label_desc: Use image node_id 3 for calling a global function with example usage: uniform_l1_n_balls(dummy, batch_size, n) and returns: unknown