code: def _compute_tolerance(workers):
      """Computes how many workers can be ignored for one gradient update.
  
      These numbers were chosen based on just a few expriments.  They are rather
      arbitrary, feel free to change them.
  
      Args:
        workers: Number of workers used during computations.
  
      Returns:
        int: how many workers can be preemptied during one step.
      """
      if workers <= 4:
          return 0
      elif workers <= 10:
          return 1
      elif workers <= 30:
          return int(0.1 * workers)
      else:
          return int(0.5 * workers)
  
imports: import collections
  import functools
  import inspect
  from absl import logging
  from model_search import block_builder
  from model_search import ensembler
  from model_search.architecture import architecture_utils
  from model_search.architecture import tower
  from model_search.ensembler import EnsembleLogits
  from model_search.generators import base_tower_generator
  from model_search.generators import trial_utils
  from model_search.meta import distillation
  import numpy
  import tensorflow.compat.v2
label_desc: Use image node_id 4 for calling a global function with example usage: _compute_tolerance(workers) and returns: int, int, int, int