simplify condiiton for readability

fairscale/nn/data_parallel/fully_sharded_data_parallel.py

@@ -587,19 +587,20 @@ class FullyShardedDataParallel(nn.Module):
                 assert p.dtype == torch.float32
 
             # If world_size is 1, then we all-reduce grads instead of sharding.
-            p._is_sharded = self.world_size > 1
             p._orig_size = p.data.size()
 
-            if not p._is_sharded:
+            if self.world_size == 1:
+                p._is_sharded = False
                 self.numel_padded_per_param.append(0)
                 continue
-            p._is_sharded = True
 
             # Replace p.data with the relevant shard.
             orig_data = p.data
             p.data, num_padded = self._get_shard(p.data)
             self.numel_padded_per_param.append(num_padded)
             free_storage_(orig_data)
+
+            p._is_sharded = True
         assert len(self.numel_padded_per_param) == len(self.params)
 
     def _get_shard(self, tensor: torch.Tensor) -> Tuple[torch.Tensor, int]: