using mmcv==0.2.16

docs/INSTALL.md

@@ -8,7 +8,7 @@
 - CUDA 9.0 or higher
 - NCCL 2
 - GCC 4.9 or higher
-- [mmcv](https://github.com/open-mmlab/mmcv)
+- [mmcv 0.2.16](https://github.com/open-mmlab/mmcv/tree/v0.2.16)
 
 We have tested the following versions of OS and softwares:
 

mmdet/apis/train.py

@@ -205,15 +205,7 @@ def _dist_train(model,
         for ds in dataset
     ]
     # put model on gpus
-    # model = MMDistributedDataParallel(model.cuda())
-    find_unused_parameters = True
-    # Sets the `find_unused_parameters` parameter in
-    # torch.nn.parallel.DistributedDataParallel
-    model = MMDistributedDataParallel(
-        model.cuda(),
-        device_ids=[torch.cuda.current_device()],
-        broadcast_buffers=False,
-        find_unused_parameters=find_unused_parameters)
+    model = MMDistributedDataParallel(model.cuda())
 
     # build runner
     optimizer = build_optimizer(model, cfg.optimizer)

requirements/runtime.txt

 matplotlib
-mmcv>=0.3.1
+mmcv==0.2.16
 numpy
 scipy
 # need older pillow until torchvision is fixed

tools/test.py

@@ -240,11 +240,7 @@ def main():
         model = MMDataParallel(model, device_ids=[0])
         outputs = single_gpu_test(model, data_loader, args.show)
     else:
-        # model = MMDistributedDataParallel(model.cuda())
-        model = MMDistributedDataParallel(
-            model.cuda(),
-            device_ids=[torch.cuda.current_device()],
-            broadcast_buffers=False)
+        model = MMDistributedDataParallel(model.cuda())
         outputs = multi_gpu_test(model, data_loader, args.tmpdir,
                                  args.gpu_collect)
 

tools/test_robustness.py

@@ -375,11 +375,7 @@ def main():
                 model = MMDataParallel(model, device_ids=[0])
                 outputs = single_gpu_test(model, data_loader, args.show)
             else:
-                # model = MMDistributedDataParallel(model.cuda())
-                model = MMDistributedDataParallel(
-                    model.cuda(),
-                    device_ids=[torch.cuda.current_device()],
-                    broadcast_buffers=False)
+                model = MMDistributedDataParallel(model.cuda())
                 outputs = multi_gpu_test(model, data_loader, args.tmpdir)
 
             rank, _ = get_dist_info()