code: def recommend_k_svd(
      model, test, train, top_k=DEFAULT_K, remove_seen=True
  ):
      with Timer() as t:
          topk_scores = compute_ranking_predictions(
              model,
              train,
              usercol=DEFAULT_USER_COL,
              itemcol=DEFAULT_ITEM_COL,
              predcol=DEFAULT_PREDICTION_COL,
              remove_seen=remove_seen,
          )
      return topk_scores, t
  
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 9 for calling a global function with example usage: recommend_k_svd(model, test, train, top_k, remove_seen) and returns: topk_scores,  t