Maskrcnn-benchmark: RuntimeError: copy_if failed to synchronize: device-side assert triggered

[yxchng]

🐛 Bug

...
/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:53: lambda ->auto::operator()(int)->auto: bl
ock: [0,0,0], thread: [41,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bou nds" failed.
...

Traceback (most recent call last):
File "tools/train_net.py", line 174, in
main()
File "tools/train_net.py", line 167, in main
model = train(cfg, args.local_rank, args.distributed)
File "tools/train_net.py", line 73, in train
arguments,
File "/run/mount/sdd1/maskrcnn_wrapper/env/lib/python3.5/site-packages/maskrcnn_benchmark-0.1-py3.5
-linux-x86_64.egg/maskrcnn_benchmark/engine/trainer.py", line 66, in do_train
loss_dict = model(images, targets)
File "/run/mount/sdd1/maskrcnn_wrapper/env/lib/python3.5/site-packages/torch/nn/modules/module.py",
line 494, in __call__
result = self.forward(input, *kwargs)
File "/run/mount/sdd1/maskrcnn_wrapper/env/lib/python3.5/site-packages/maskrcnn_benchmark-0.1-py3.5
-linux-x86_64.egg/maskrcnn_benchmark/modeling/detector/generalized_rcnn.py", line 50, in forward
proposals, proposal_losses = self.rpn(images, features, targets)
File "/run/mount/sdd1/maskrcnn_wrapper/env/lib/python3.5/site-packages/torch/nn/modules/module.py",
line 494, in __call__
result = self.forward(input, *kwargs)
File "/run/mount/sdd1/maskrcnn_wrapper/env/lib/python3.5/site-packages/maskrcnn_benchmark-0.1-py3.5
-linux-x86_64.egg/maskrcnn_benchmark/modeling/rpn/rpn.py", line 159, in forward
return self._forward_train(anchors, objectness, rpn_box_regression, targets)
File "/run/mount/sdd1/maskrcnn_wrapper/env/lib/python3.5/site-packages/maskrcnn_benchmark-0.1-py3.5
-linux-x86_64.egg/maskrcnn_benchmark/modeling/rpn/rpn.py", line 175, in _forward_train
anchors, objectness, rpn_box_regression, targets
File "/run/mount/sdd1/maskrcnn_wrapper/env/lib/python3.5/site-packages/torch/nn/modules/module.py",
line 494, in __call__
result = self.forward(input, *kwargs)
File "/run/mount/sdd1/maskrcnn_wrapper/env/lib/python3.5/site-packages/maskrcnn_benchmark-0.1-py3.5
-linux-x86_64.egg/maskrcnn_benchmark/modeling/rpn/inference.py", line 138, in forward
sampled_boxes.append(self.forward_for_single_feature_map(a, o, b))
File "/run/mount/sdd1/maskrcnn_wrapper/env/lib/python3.5/site-packages/maskrcnn_benchmark-0.1-py3.5
-linux-x86_64.egg/maskrcnn_benchmark/modeling/rpn/inference.py", line 113, in forward_for_single_feat
ure_map
boxlist = remove_small_boxes(boxlist, self.min_size)
File "/run/mount/sdd1/maskrcnn_wrapper/env/lib/python3.5/site-packages/maskrcnn_benchmark-0.1-py3.5
-linux-x86_64.egg/maskrcnn_benchmark/structures/boxlist_ops.py", line 47, in remove_small_boxes
(ws >= min_size) & (hs >= min_size)
RuntimeError: copy_if failed to synchronize: device-side assert triggered

This may be similar to https://github.com/facebookresearch/maskrcnn-benchmark/issues/229 but the message is slightly different. 229 is an illegal memory access was encountered but what I met is device-side assert triggered.

I have changed the NUM_CLASSES as well.

To Reproduce

Steps to reproduce the behavior:

Run training code

Expected behavior

No error

Environment

PyTorch version: 1.0.0.dev20190409
Is debug build: No
CUDA used to build PyTorch: 10.0.130

OS: Ubuntu 16.04.4 LTS
GCC version: (Ubuntu 5.5.0-12ubuntu1~16.04) 5.5.0 20171010
CMake version: version 3.5.1

Python version: 3.5
Is CUDA available: Yes
CUDA runtime version: 10.0.130
GPU models and configuration:
GPU 0: GeForce RTX 2080 Ti
GPU 1: TITAN X (Pascal)

Nvidia driver version: 418.39
cuDNN version: Could not collect

Versions of relevant libraries:
[pip] Could not collect
[conda] Could not collect
Pillow (6.0.0)

[yxchng]

According to this https://github.com/facebookresearch/maskrcnn-benchmark/issues/275, it seems like having a learning rate that is too large may have caused the problem? But the error message does not seem to be related at all. I am still in the process of verifying this fact.

[yxchng]

Having learning rate that is too large is indeed the problem. Lowering the learning rate solves the problem.

[19995YYQ]

Having learning rate that is too large is indeed the problem. Lowering the learning rate solves the problem.

I meet the same issues. Can you tell me how to reduce your learning rate? Is it just experience to lower the value a little bit from the beginning?thanks

[PyNancy]

batch size too large also cause this issue

[Enn29]

hello, I have met the seem issue, then i reduce the learning rate, but i can't reslove it. so could you help me to reslove the issue, thanks!

the error in below:
File "C:\Anaconda3\envs\maskrcnn_benchmark\lib\site-packages\maskrcnn-benchmark\maskrcnn_benchmark\engine\trainer.py", line 88, in do_train loss_dict = model(images, targets) File "C:\Anaconda3\envs\maskrcnn_benchmark\lib\site-packages\torch\nn\modules\module.py", line 491, in __call__ result = self.forward(input, *kwargs) File "C:\Anaconda3\envs\maskrcnn_benchmark\lib\site-packages\apex-0.1-py3.7-win-amd64.egg\apex\amp_initialize.py", line 194, in new_fwd *applier(kwargs, input_caster)) File "C:\Anaconda3\envs\maskrcnn_benchmark\lib\site-packages\maskrcnn-benchmark\maskrcnn_benchmark\modeling\detector\generalized_rcnn.py", line 60, in forward x, result, detector_losses = self.roi_heads(features, proposals, targets) File "C:\Anaconda3\envs\maskrcnn_benchmark\lib\site-packages\torch\nn\modules\module.py", line 491, in __call__ result = self.forward(input, *kwargs) File "C:\Anaconda3\envs\maskrcnn_benchmark\lib\site-packages\maskrcnn-benchmark\maskrcnn_benchmark\modeling\roi_heads\roi_heads.py", line 26, in forward x, detections, loss_box = self.box(features, proposals, targets) File "C:\Anaconda3\envs\maskrcnn_benchmark\lib\site-packages\torch\nn\modules\module.py", line 491, in __call__ result = self.forward(input, **kwargs) File "C:\Anaconda3\envs\maskrcnn_benchmark\lib\site-packages\maskrcnn-benchmark\maskrcnn_benchmark\modeling\roi_heads\box_head\box_head.py", line 56, in forward [class_logits], [box_regression] File "C:\Anaconda3\envs\maskrcnn_benchmark\lib\site-packages\maskrcnn-benchmark\maskrcnn_benchmark\modeling\roi_heads\box_head\loss.py", line 151, in __call__ sampled_pos_inds_subset = torch.nonzero(labels > 0).squeeze(1) RuntimeError: copy_if failed to synchronize: device-side assert triggered