ref: unify slurm and TE under backendPlugin 5/n

pytorch_lightning/accelerators/ddp2_accelerator.py

@@ -11,22 +11,20 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License
-
 import os
 
 import torch
 import torch.distributed as torch_distrib
 
-from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from pytorch_lightning.core.lightning import LightningModule
 from pytorch_lightning.core.step_result import Result
 from pytorch_lightning.distributed.dist import LightningDistributed
 from pytorch_lightning import _logger as log
-from pytorch_lightning.accelerators.accelerator import Accelerator
+from pytorch_lightning.accelerators.accelerator import Accelerator, ReduceOp
 from pytorch_lightning.utilities import AMPType
-from pytorch_lightning.utilities.distributed import rank_zero_only
+from pytorch_lightning.utilities.distributed import rank_zero_only, sync_ddp_if_available
 from torch.nn.parallel import DistributedDataParallel
-from typing import List, Optional
+from typing import List, Optional, Union, Any
 
 try:
     from hydra.utils import to_absolute_path, get_original_cwd
@@ -203,3 +201,9 @@ def configure_sync_batchnorm(self, model: LightningModule) -> LightningModule:
         model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(model, process_group=None)
 
         return model
+
+    def sync_tensor(self,
+                    tensor: Union[torch.Tensor],
+                    group: Optional[Any] = None,
+                    reduce_op: Optional[Union[ReduceOp, str]] = None) -> torch.Tensor:
+        return sync_ddp_if_available(tensor, group, reduce_op)