Update no trainer examples for QA and Semantic Segmentation (#18474)

* swag_no_trainer updated for with gather_metrics

* Removed unused variable samples_seen

* updated examples with gather_for_metrics

examples/pytorch/semantic-segmentation/run_semantic_segmentation_no_trainer.py

@@ -605,7 +605,6 @@ def main():
 
         logger.info("***** Running evaluation *****")
         model.eval()
-        samples_seen = 0
         for step, batch in enumerate(tqdm(eval_dataloader, disable=not accelerator.is_local_main_process)):
             with torch.no_grad():
                 outputs = model(**batch)
@@ -615,15 +614,7 @@ def main():
             )
             predictions = upsampled_logits.argmax(dim=1)
 
-            predictions, references = accelerator.gather((predictions, batch["labels"]))
-
-            # If we are in a multiprocess environment, the last batch has duplicates
-            if accelerator.num_processes > 1:
-                if step == len(eval_dataloader) - 1:
-                    predictions = predictions[: len(eval_dataloader.dataset) - samples_seen]
-                    references = references[: len(eval_dataloader.dataset) - samples_seen]
-                else:
-                    samples_seen += references.shape[0]
+            predictions, references = accelerator.gather_for_metrics((predictions, batch["labels"]))
 
             metric.add_batch(
                 predictions=predictions,