class_docstr: Can be used to program the learning rate schedule of an `optim.base.Optimizer`.
docstr: Returns the learning rate at a given iteration.
  
  Parameters
  ----------
  t
      The iteration number.
docstr_tok: ["Returns","the","learning","rate","at","a","given","iteration",".","Parameters","--","--","--","--","--","t","The","iteration","number","."]
code: def get(self, t: int) -> float:
      """Returns the learning rate at a given iteration.
  
      Parameters
      ----------
      t
          The iteration number.
  
      """
  
imports: from __future__ import annotations
  import abc
  import typing
  import numpy
  from river import base, optim, utils
label_desc: Use image node_id 1 for calling the Scheduler obj's underlying member method code with example usage: obj.get(t) without return types