class_docstr: The base class for a stochastic solver.
  In only deals with verbosing information, and setting parameters.
  
  Parameters
  ----------
  epoch_size : `int`, default=0
      Epoch size. If given before calling set_model, then we'll
      use the specified value. If not, we ``epoch_size`` is specified
      by the model itself, when calling set_model
  
  rand_type : `str`
      Type of random sampling
  
      * if ``"unif"`` samples are uniformly drawn among all possibilities
      * if ``"perm"`` a random permutation of all possibilities is
        generated and samples are sequentially taken from it. Once all of
        them have been taken, a new random permutation is generated
  
  seed : `int`
      The seed of the random sampling. If it is negative then a random seed
      (different at each run) will be chosen.
  
  Notes
  -----
  This class should not be used by end-users
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code: def _set_rand_max(self, model):
      model_rand_max = model._rand_max
      self._set("_rand_max", model_rand_max)
  
file_path: tick/tick/solver/base/sto.py
imports: from abc import ABC
  from tick.base import Base
  from tick.base_model import Model
  from tick.prox.base import Prox
  from ..build.solver import RandType_perm
  from ..build.solver import RandType_unif
label_desc: Use image node_id 6 for calling the SolverSto obj's underlying member method code with example usage: obj._set_rand_max(model) without return types