class_docstr: Switcher to do `n_crit` iterations of the critic then `n_gen` iterations of the generator.
class_docstr_tok: ["Switcher","to","do","`","n_crit","`","iterations","of","the","critic","then","`","n_gen","`","iterations","of","the","generator","."]
code: def __init__(
      self,
      n_crit: int = 1,  # How many steps of critic training before switching to generator
      n_gen: int = 1,  # How many steps of generator training before switching to critic
  ):
      store_attr("n_crit,n_gen")
  
imports: from __future__ import annotations
  from ..basics import *
  from .all import *
label_desc: Use image node_id 1 to create a new FixedGANSwitcher object from inherited base classes: Callback with example: obj = FixedGANSwitcher(n_crit, n_gen)