other modif

src/accelerate/accelerator.py

@@ -648,6 +648,10 @@ class Accelerator:
     def dispatch_batches(self):
         return self.dataloader_config.dispatch_batches
 
+    @property
+    def cp(self):
+        return self.dataloader_config.cp
+
     @property
     def even_batches(self):
         return self.dataloader_config.even_batches
@@ -2410,6 +2414,7 @@ class Accelerator:
             non_blocking=self.non_blocking,
             use_stateful_dataloader=self.use_stateful_dataloader,
             torch_device_mesh=device_mesh,
+            cp=self.cp,
         )
         self._dataloaders.append(prepared_data_loader)
         return prepared_data_loader

src/accelerate/data_loader.py

@@ -1007,6 +1007,7 @@ def prepare_data_loader(
     non_blocking: bool = False,
     use_stateful_dataloader: bool = False,
     torch_device_mesh=None,
+    cp=False,
 ) -> DataLoader:
     """
     Wraps a PyTorch `DataLoader` to generate batches for one of the processes only.
@@ -1137,6 +1138,10 @@ def prepare_data_loader(
             process_index = process_index // submesh_tp_size
             num_processes = submesh_fsdp_size * submesh_dp_size
 
+    if cp:
+        process_index = 0
+        num_processes = 1
+    
     # Sanity check
     if split_batches:
         if dataloader.batch_size is not None:

src/accelerate/utils/dataclasses.py

@@ -815,6 +815,7 @@ class DataLoaderConfiguration:
             " underlying dataset is an `IterableDataset`, `False` otherwise."
         },
     )
+    cp: bool = field(default=False)
     even_batches: bool = field(
         default=True,
         metadata={