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","."]
docstr: Initializes a new replay candidate generator.
docstr_tok: ["Initializes","a","new","replay","candidate","generator","."]
code: def __init__(self) -> None:
      """
      Initializes a new replay candidate generator.
      """
      self.cache: List[T] = []
  
imports: from typing import List, Optional
  from ._base import CandidateGenerator, T
label_desc: Use image node_id 1 to create a new ReplayCandidateGenerator object from inherited base classes: CandidateGenerator with example: obj = ReplayCandidateGenerator()