[fix] Typo in ShardedDDP unit test (#282)

* fix typo, backend for CPU test

fairscale/nn/data_parallel/sharded_ddp.py

@@ -129,7 +129,7 @@ class ShardedDataParallel(nn.Module):
         return self.module(*inputs, **kwargs)
 
     def reduce(self) -> None:
-        """ .. deprecated:: 0.0.4
+        """.. deprecated:: 0.0.4
 
         This does not need to be called, the gradient reduction is done automatically during the BW pass
         """
@@ -157,8 +157,7 @@ class ShardedDataParallel(nn.Module):
         self.should_accumulate_grads = old_should_accumulate_grads
 
     def _clear_counters(self) -> None:
-        """ Reset all the grad reduce and call counters
-        """
+        """Reset all the grad reduce and call counters"""
         self._grad_to_be_reduced = [True for _ in self._grad_to_be_reduced]
         self._reduced_grads = {o: 0 for o in self.sharded_optimizers}
 
@@ -254,14 +253,14 @@ class ShardedDataParallel(nn.Module):
 
             _ = list(map(lambda x: x.wait(), work_handles))
 
-    def _passing_sync_batchnorm_handle(self, module):
+    def _passing_sync_batchnorm_handle(self, module: nn.Module) -> None:
         """
         Passes handle required for ``torch.nn.modules.SyncBatchNorm``.
         Adapted from ``torch.nn.distributed.DistributedDataParallel``.
         """
         for layer in module.modules():
             if isinstance(layer, torch.nn.modules.SyncBatchNorm):
-                assert self.device_type != 'cpu', "SyncBatchNorm layers only work with GPU modules"
+                assert self.device_type != "cpu", "SyncBatchNorm layers only work with GPU modules"
                 # device_id logic has not been handled, assume single-process single-device
                 # SyncBatchNorm only supports DDP with single-process single-device anyway'
-                layer._specify_ddp_gpu_num(1)
+                layer._specify_ddp_gpu_num(1)  # type: ignore

tests/nn/data_parallel/test_sharded_ddp.py

@@ -316,8 +316,7 @@ def test_ddp_attributes():
     # - device_type
 
     url = "file://" + tempfile.mkstemp()[1]
-    backend = dist.Backend.NCCL
-    dist.init_process_group(init_method=url, backend=backend, rank=0, world_size=1)
+    dist.init_process_group(init_method=url, backend="gloo", rank=0, world_size=1)
 
     model = Sequential(Linear(2, 3), Linear(3, 3))
     optimizer = OSS(params=model.parameters(), optim=torch.optim.SGD, lr=0.01, momentum=0.99)
@@ -352,10 +351,7 @@ def test_ddp_sync_batch_norm():
     temp_file_name = tempfile.mkstemp()[1]
     device = "cuda"
     mp.spawn(
-        run_test_ddp_sync_batch_norm,
-        args=(world_size, backend, device, temp_file_name),
-        nprocs=world_size,
-        join=True
+        run_test_ddp_sync_batch_norm, args=(world_size, backend, device, temp_file_name), nprocs=world_size, join=True
     )