code: def prepare_training_fastai(train, test):
      data = train.copy()
      data[DEFAULT_USER_COL] = data[DEFAULT_USER_COL].astype("str")
      data[DEFAULT_ITEM_COL] = data[DEFAULT_ITEM_COL].astype("str")
      data = CollabDataBunch.from_df(
          data,
          user_name=DEFAULT_USER_COL,
          item_name=DEFAULT_ITEM_COL,
          rating_name=DEFAULT_RATING_COL,
          valid_pct=0,
      )
      return data
  
imports: import os
  import numpy
  import pandas
  from tempfile import TemporaryDirectory
  import surprise
  import cornac
  from recommenders.utils.timer import Timer
  from recommenders.utils.constants import COL_DICT, DEFAULT_K, DEFAULT_USER_COL, DEFAULT_ITEM_COL, DEFAULT_RATING_COL, DEFAULT_PREDICTION_COL, DEFAULT_TIMESTAMP_COL, SEED
  from recommenders.models.sar import SAR
  from recommenders.models.surprise.surprise_utils import predict, compute_ranking_predictions
  from recommenders.models.cornac.cornac_utils import predict_ranking
  from recommenders.evaluation.python_evaluation import map, ndcg_at_k, precision_at_k, recall_at_k
  from recommenders.evaluation.python_evaluation import rmse, mae, rsquared, exp_var
label_desc: Use image node_id 10 for calling a global function with example usage: prepare_training_fastai(train, test) and returns: data