Added distributed training check (#287)

maskrcnn_benchmark/utils/comm.py

@@ -13,18 +13,24 @@ import torch
 
 
 def get_world_size():
+    if not torch.distributed.is_available():
+        return 1
     if not torch.distributed.is_initialized():
         return 1
     return torch.distributed.get_world_size()
 
 
 def get_rank():
+    if not torch.distributed.is_available():
+        return 0
     if not torch.distributed.is_initialized():
         return 0
     return torch.distributed.get_rank()
 
 
 def is_main_process():
+    if not torch.distributed.is_available():
+        return True
     if not torch.distributed.is_initialized():
         return True
     return torch.distributed.get_rank() == 0
@@ -35,6 +41,8 @@ def synchronize():
     Helper function to synchronize between multiple processes when
     using distributed training
     """
+    if not torch.distributed.is_available():
+        return
     if not torch.distributed.is_initialized():
         return
     world_size = torch.distributed.get_world_size()
@@ -103,6 +111,8 @@ def scatter_gather(data):
     # each process will then serialize the data to the folder defined by
     # the main process, and then the main process reads all of the serialized
     # files and returns them in a list
+    if not torch.distributed.is_available():
+        return [data]
     if not torch.distributed.is_initialized():
         return [data]
     synchronize()