class_docstr: An operation which loads the games played while training an
  OpenAlphaTensor model.
class_docstr_tok: ["An","operation","which","loads","the","games","played","while","training","an","OpenAlphaTensor","model","."]
docstr: Load the games played while training an OpenAlphaTensor model.
  
  Args:
      games_store_dir: The directory where the games are stored.
      trainer: The trainer to load the games into.
docstr_tok: ["Load","the","games","played","while","training","an","OpenAlphaTensor","model",".","Args",":","games_store_dir",":","The","directory","where","the","games","are","stored",".","trainer",":","The","trainer","to","load","the","games","into","."]
code: def execute(self, games_store_dir: Path, trainer: Trainer):
      """Load the games played while training an OpenAlphaTensor model.
  
      Args:
          games_store_dir: The directory where the games are stored.
          trainer: The trainer to load the games into.
      """
      games_store_dir = games_store_dir or BASE_CHECKPOINT_DATA_DIR
      # if games_store_dir contains games, load them
      if (
          games_store_dir.exists()
          and (games_store_dir / "game_data.json").exists()
      ):
          trainer.dataset.load_games(games_store_dir)
      self._loaded = True
  
imports: from pathlib import Path
  from typing import Any
  import torch
  from nebullvm.operations.base import Operation
  from open_alpha_tensor.config import BASE_CHECKPOINT_DATA_DIR, BASE_CHECKPOINT_DIR
  from open_alpha_tensor.core.modules.alpha_tensor import AlphaTensorModel
  from open_alpha_tensor.core.training import Trainer
label_desc: Use image node_id 2 for calling the LoadCheckpointDataOp obj's underlying member method code with example usage: obj.execute(games_store_dir, trainer) without return types