Do not shuffle test/validation splits

The argument defaults to `True`, but shuffling these is redundant.

pytorch-ddp-example/main.py

@@ -133,8 +133,14 @@ def prepare_datasets(args, device):
         shuffle=True,
         seed=args.seed,
     )
-    valid_sampler = torch.utils.data.distributed.DistributedSampler(valid_dset)
-    test_sampler = torch.utils.data.distributed.DistributedSampler(test_dset)
+    valid_sampler = torch.utils.data.distributed.DistributedSampler(
+        valid_dset,
+        shuffle=False,
+    )
+    test_sampler = torch.utils.data.distributed.DistributedSampler(
+        test_dset,
+        shuffle=False,
+    )
 
     train_dset = torch.utils.data.DataLoader(
         train_dset,

pytorch-fsdp-example/main.py

@@ -181,8 +181,14 @@ def prepare_datasets(args, device):
         shuffle=True,
         seed=args.seed,
     )
-    valid_sampler = torch.utils.data.distributed.DistributedSampler(valid_dset)
-    test_sampler = torch.utils.data.distributed.DistributedSampler(test_dset)
+    valid_sampler = torch.utils.data.distributed.DistributedSampler(
+        valid_dset,
+        shuffle=False,
+    )
+    test_sampler = torch.utils.data.distributed.DistributedSampler(
+        test_dset,
+        shuffle=False,
+    )
 
     train_dset = torch.utils.data.DataLoader(
         train_dset,