Don't compute metrics in LM examples on TPU (#16029)

examples/pytorch/language-modeling/run_clm.py

@@ -43,6 +43,7 @@ from transformers import (
     Trainer,
     TrainingArguments,
     default_data_collator,
+    is_torch_tpu_available,
     set_seed,
 )
 from transformers.testing_utils import CaptureLogger
@@ -479,8 +480,10 @@ def main():
         tokenizer=tokenizer,
         # Data collator will default to DataCollatorWithPadding, so we change it.
         data_collator=default_data_collator,
-        compute_metrics=compute_metrics if training_args.do_eval else None,
-        preprocess_logits_for_metrics=preprocess_logits_for_metrics if training_args.do_eval else None,
+        compute_metrics=compute_metrics if training_args.do_eval and not is_torch_tpu_available() else None,
+        preprocess_logits_for_metrics=preprocess_logits_for_metrics
+        if training_args.do_eval and not is_torch_tpu_available()
+        else None,
     )
 
     # Training

examples/pytorch/language-modeling/run_mlm.py

@@ -43,6 +43,7 @@ from transformers import (
     HfArgumentParser,
     Trainer,
     TrainingArguments,
+    is_torch_tpu_available,
     set_seed,
 )
 from transformers.trainer_utils import get_last_checkpoint
@@ -513,8 +514,10 @@ def main():
         eval_dataset=eval_dataset if training_args.do_eval else None,
         tokenizer=tokenizer,
         data_collator=data_collator,
-        compute_metrics=compute_metrics if training_args.do_eval else None,
-        preprocess_logits_for_metrics=preprocess_logits_for_metrics if training_args.do_eval else None,
+        compute_metrics=compute_metrics if training_args.do_eval and not is_torch_tpu_available() else None,
+        preprocess_logits_for_metrics=preprocess_logits_for_metrics
+        if training_args.do_eval and not is_torch_tpu_available()
+        else None,
     )
 
     # Training