(Fix) data_loader: Change Value Error to Warning for BatchSampler in sampler argument, and Fix Typos

Author: suzyahyah

src/accelerate/data_loader.py

@@ -631,10 +631,12 @@ def get_sampler(self):
         return get_sampler(self)
 
     def set_sampler(self, sampler):
-        if isinstance(sampler, BatchSampler):
-            self.sampler.batch_sampler = sampler
-        elif isinstance(sampler, Sampler):
+        if isinstance(self.sampler, BatchSampler):
             self.sampler.sampler = sampler
+        else:
+            self.batch_sampler.sampler = sampler
+            if hasattr(self.batch_sampler, "batch_sampler"):
+                self.batch_sampler.batch_sampler.sampler = sampler
 
 
 if is_torch_xla_available():
@@ -955,12 +957,12 @@ def get_sampler(self):
         return get_sampler(self)
 
     def set_sampler(self, sampler):
-        if isinstance(sampler, BatchSampler):
-            self.sampler.batch_sampler = sampler
-        elif isinstance(sampler, Sampler):
+        if isinstance(self.sampler, BatchSampler):
             self.sampler.sampler = sampler
         else:
-            raise ValueError(f"{sampler} must be of type torch.utills.data.Sampler or torch.utils.data.BatchSampler")
+            self.batch_sampler.sampler = sampler
+            if hasattr(self.batch_sampler, "batch_sampler"):
+                self.batch_sampler.batch_sampler.sampler = sampler
 
 
 def get_sampler(dataloader):
@@ -1150,8 +1152,10 @@ def prepare_data_loader(
     new_dataset = dataloader.dataset
     # Iterable dataset doesn't like batch_sampler, but data_loader creates a default one for it
     if isinstance(dataloader.sampler, BatchSampler):
-        raise ValueError(
-            "Should not pass a BatchSampler do dataloader sampler argument. As per pytorch>2.1.0 documentation, please pass this to sampler instead"
+        logger.warning(
+            "BatchSampler was passed to sampler argument."
+            "If you have a custom Sampler that yields a list of batch indices at a time, please pass it as the batch_sampler argument instead."
+            "For more information, see https://pytorch.org/docs/stable/data.html#torch.utils.data.DataLoader"
         )
 
     new_batch_sampler = dataloader.batch_sampler if not isinstance(new_dataset, IterableDataset) else None
@@ -1347,8 +1351,10 @@ def skip_first_batches(dataloader, num_batches=0):
 
     dataset = dataloader.dataset
     if isinstance(dataloader.sampler, BatchSampler):
-        raise ValueError(
-            "Should not pass a BatchSampler do dataloader sampler argument. As per the latest pytorch documentation, please pass this to sampler instead"
+        logger.warning(
+            "BatchSampler was passed to sampler argument."
+            "If you have a custom Sampler that yields a list of batch indices at a time, please pass it as the batch_sampler argument instead."
+            "For more information, see https://pytorch.org/docs/stable/data.html#torch.utils.data.DataLoader"
         )
 
     if isinstance(dataset, IterableDataset):