class_docstr: Base optimizer class for the fastai library, updating `params` with `cbs`
class_docstr_tok: ["Base","optimizer","class","for","the","fastai","library",",","updating","`","params","`","with","`","cbs","`"]
code: def step(self, closure=None):
      if closure is not None:
          raise NotImplementedError(
              "fastai optimizers currently do not support closure"
          )
      for p, pg, state, hyper in self.all_params(with_grad=True):
          for cb in self.cbs:
              state = _update(state, cb(p, **{**state, **hyper}))
          self.state[p] = state
  
imports: from __future__ import annotations
  from .torch_basics import *
label_desc: Use image node_id 3 for calling the Optimizer obj's underlying member method code with example usage: obj.step(closure) without return types