Fix cardinality (#9505)

src/transformers/trainer_tf.py

@@ -135,7 +135,7 @@ class TFTrainer:
             raise ValueError("Trainer: training requires a train_dataset.")
 
         self.total_train_batch_size = self.args.train_batch_size * self.args.gradient_accumulation_steps
-        self.num_train_examples = self.train_dataset.cardinality(self.train_dataset).numpy()
+        self.num_train_examples = self.train_dataset.cardinality().numpy()
 
         if self.num_train_examples < 0:
             raise ValueError("The training dataset must have an asserted cardinality")
@@ -167,7 +167,7 @@ class TFTrainer:
             raise ValueError("Trainer: evaluation requires an eval_dataset.")
 
         eval_dataset = eval_dataset if eval_dataset is not None else self.eval_dataset
-        num_examples = eval_dataset.cardinality(eval_dataset).numpy()
+        num_examples = eval_dataset.cardinality().numpy()
 
         if num_examples < 0:
             raise ValueError("The training dataset must have an asserted cardinality")
@@ -197,7 +197,7 @@ class TFTrainer:
         Subclass and override this method if you want to inject some custom behavior.
         """
 
-        num_examples = test_dataset.cardinality(test_dataset).numpy()
+        num_examples = test_dataset.cardinality().numpy()
 
         if num_examples < 0:
             raise ValueError("The training dataset must have an asserted cardinality")