code: def evaluation(self, batch_size, excl_datasets=[]):
      output_types = {
          "user_id": tf.int32,
          "pos_mask": tf.bool,
          "excl_mask": tf.bool,
      }
      output_shapes = {
          "user_id": [],
          "pos_mask": [self.datastore.total_items()],
          "excl_mask": [self.datastore.total_items()],
      }
  
      return self._build_dataset(
          generator=_evaluation_generator,
          generator_params=(self.datastore, excl_datasets),
          output_types=output_types,
          output_shapes=output_shapes,
          batch_size=batch_size,
          num_parallel_calls=1,
      )
  
file_path: openrec/openrec/tf2/data/dataset.py
imports: from openrec.tf2.data import _ParallelDataset
  from openrec.tf2.data import _DataStore
  import tensorflow
  import numpy
  import random
label_desc: Use image node_id 6 for calling the Dataset obj's underlying member method code with example usage: obj.evaluation(batch_size, excl_datasets) and returns: self