Migrate to use dataset.cardinality.

The functionality is identical. We plan to deprecate tf.data.experimental.cardinality in the near future, so this will avoid a deprecation warning.

PiperOrigin-RevId: 315305120

Author: aaudiber

research/kg_hyp_emb/models/base.py

@@ -202,7 +202,7 @@ def eval(self, examples, filters, batch_size=1000):
     mean_rank = {}
     mean_reciprocal_rank = {}
     hits_at = {}
-    total_examples = tf.data.experimental.cardinality(examples).numpy()
+    total_examples = examples.cardinality().numpy()
     batch_size = min(batch_size, total_examples)
     for missing in ['rhs', 'lhs']:
       ranks = np.ones(total_examples)