[docs] Fix datasets in guides (#28715)

* change datasets

* fix

examples/pytorch/image-classification/run_image_classification_no_trainer.py

@@ -439,7 +439,9 @@ def main():
         name=args.lr_scheduler_type,
         optimizer=optimizer,
         num_warmup_steps=args.num_warmup_steps * accelerator.num_processes,
-        num_training_steps=args.max_train_steps if overrode_max_train_steps else args.max_train_steps * accelerator.num_processes,
+        num_training_steps=args.max_train_steps
+        if overrode_max_train_steps
+        else args.max_train_steps * accelerator.num_processes,
     )
 
     # Prepare everything with our `accelerator`.

examples/pytorch/image-pretraining/run_mim_no_trainer.py

@@ -627,7 +627,9 @@ def main():
         name=args.lr_scheduler_type,
         optimizer=optimizer,
         num_warmup_steps=args.num_warmup_steps * accelerator.num_processes,
-        num_training_steps=args.max_train_steps if overrode_max_train_steps else args.max_train_steps * accelerator.num_processes,
+        num_training_steps=args.max_train_steps
+        if overrode_max_train_steps
+        else args.max_train_steps * accelerator.num_processes,
     )
 
     # Prepare everything with our `accelerator`.

examples/pytorch/language-modeling/run_clm_no_trainer.py

@@ -527,7 +527,9 @@ def main():
         name=args.lr_scheduler_type,
         optimizer=optimizer,
         num_warmup_steps=args.num_warmup_steps * accelerator.num_processes,
-        num_training_steps=args.max_train_steps if overrode_max_train_steps else args.max_train_steps * accelerator.num_processes,
+        num_training_steps=args.max_train_steps
+        if overrode_max_train_steps
+        else args.max_train_steps * accelerator.num_processes,
     )
 
     # Prepare everything with our `accelerator`.

examples/pytorch/language-modeling/run_mlm_no_trainer.py

@@ -564,7 +564,9 @@ def main():
         name=args.lr_scheduler_type,
         optimizer=optimizer,
         num_warmup_steps=args.num_warmup_steps * accelerator.num_processes,
-        num_training_steps=args.max_train_steps if overrode_max_train_steps else args.max_train_steps * accelerator.num_processes,
+        num_training_steps=args.max_train_steps
+        if overrode_max_train_steps
+        else args.max_train_steps * accelerator.num_processes,
     )
 
     # Prepare everything with our `accelerator`.

examples/pytorch/multiple-choice/run_swag_no_trainer.py

@@ -511,7 +511,9 @@ def main():
         name=args.lr_scheduler_type,
         optimizer=optimizer,
         num_warmup_steps=args.num_warmup_steps * accelerator.num_processes,
-        num_training_steps=args.max_train_steps if overrode_max_train_steps else args.max_train_steps * accelerator.num_processes,
+        num_training_steps=args.max_train_steps
+        if overrode_max_train_steps
+        else args.max_train_steps * accelerator.num_processes,
     )
 
     # Prepare everything with our `accelerator`.

examples/pytorch/question-answering/run_qa_beam_search_no_trainer.py

@@ -751,7 +751,9 @@ def main():
         name=args.lr_scheduler_type,
         optimizer=optimizer,
         num_warmup_steps=args.num_warmup_steps * accelerator.num_processes,
-        num_training_steps=args.max_train_steps if overrode_max_train_steps else args.max_train_steps * accelerator.num_processes,
+        num_training_steps=args.max_train_steps
+        if overrode_max_train_steps
+        else args.max_train_steps * accelerator.num_processes,
     )
 
     # Prepare everything with our `accelerator`.

examples/pytorch/question-answering/run_qa_no_trainer.py

@@ -781,7 +781,9 @@ def main():
         name=args.lr_scheduler_type,
         optimizer=optimizer,
         num_warmup_steps=args.num_warmup_steps * accelerator.num_processes,
-        num_training_steps=args.max_train_steps if overrode_max_train_steps else args.max_train_steps * accelerator.num_processes,
+        num_training_steps=args.max_train_steps
+        if overrode_max_train_steps
+        else args.max_train_steps * accelerator.num_processes,
     )
 
     # Prepare everything with our `accelerator`.

examples/pytorch/semantic-segmentation/run_semantic_segmentation_no_trainer.py

@@ -514,7 +514,9 @@ def main():
         name=args.lr_scheduler_type,
         optimizer=optimizer,
         num_warmup_steps=args.num_warmup_steps * accelerator.num_processes,
-        num_training_steps=args.max_train_steps if overrode_max_train_steps else args.max_train_steps * accelerator.num_processes,
+        num_training_steps=args.max_train_steps
+        if overrode_max_train_steps
+        else args.max_train_steps * accelerator.num_processes,
     )
 
     # Prepare everything with our `accelerator`.

examples/pytorch/summarization/run_summarization_no_trainer.py

@@ -581,7 +581,9 @@ def main():
         name=args.lr_scheduler_type,
         optimizer=optimizer,
         num_warmup_steps=args.num_warmup_steps * accelerator.num_processes,
-        num_training_steps=args.max_train_steps if overrode_max_train_steps else args.max_train_steps * accelerator.num_processes,
+        num_training_steps=args.max_train_steps
+        if overrode_max_train_steps
+        else args.max_train_steps * accelerator.num_processes,
     )
 
     # Prepare everything with our `accelerator`.