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 generate(self, candidates: Optional[List[T]] = None) -> List[T]:
      # Assert trained
      assert (
          self.cache
      ), "Replay candidate generator has not been fitted."
  
      # Return candidates or cache
      return candidates or self.cache
  
imports: from typing import List, Optional
  from ._base import CandidateGenerator, T
label_desc: Use image node_id 3 for calling the ReplayCandidateGenerator obj's underlying member method code with example usage: obj.generate(candidates) and returns: unknown