class_docstr: The replay candidate generator simply returns the model configurations seen
  during training.
  
  If candidates are provided, they are returned as is.
class_docstr_tok: ["The","replay","candidate","generator","simply","returns","the","model","configurations","seen","during","training",".","If","candidates","are","provided",",","they","are","returned","as","is","."]
code: def fit(self, configs: List[T]) -> None:
      self.cache = configs
  
imports: from typing import List, Optional
  from ._base import CandidateGenerator, T
label_desc: Use image node_id 2 for calling the ReplayCandidateGenerator obj's underlying member method code with example usage: obj.fit(configs) without return types