class_docstr: Basic class of models
  
  Attributes:
      hparams (HParams): A HParams object, holds the entire set of hyperparameters.
      train_iterator (object): An iterator to load the data in training steps.
      test_iterator (object): An iterator to load the data in testing steps.
      graph (object): An optional graph.
      seed (int): Random seed.
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code: def run_slow_eval(self, news_filename, behaviors_file):
      preds = []
      labels = []
      imp_indexes = []
  
      for batch_data_input in tqdm(
          self.test_iterator.load_data_from_file(
              news_filename, behaviors_file
          )
      ):
          step_pred, step_labels, step_imp_index = self.eval(
              batch_data_input
          )
          preds.extend(np.reshape(step_pred, -1))
          labels.extend(np.reshape(step_labels, -1))
          imp_indexes.extend(np.reshape(step_imp_index, -1))
  
      group_impr_indexes, group_labels, group_preds = self.group_labels(
          labels, preds, imp_indexes
      )
      return group_impr_indexes, group_labels, group_preds
  
imports: import abc
  import time
  import numpy
  from tqdm import tqdm
  import tensorflow
  from tensorflow.compat.v1 import keras
  from recommenders.models.deeprec.deeprec_utils import cal_metric
label_desc: Use image node_id 17 for calling the BaseModel obj's underlying member method code with example usage: obj.run_slow_eval(news_filename, behaviors_file) and returns: group_impr_indexes,  group_labels,  group_preds