Comments (7)
tano297
commented on June 19, 2024
I'm going to need more information to help with this. It seems to be a problem with multi-gpu.
Can you share your setup? What is your version of pytorch. What is your computer configuration? What are you trying to achieve?
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tano297
commented on June 19, 2024
Closing this due to inactivity
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Spartacus782
commented on June 19, 2024
@tano297 I also got this error message it looks like. I am running two GeForce RTX 2080 Ti on an SLI bridge, running Ubuntu 16.04. My version of pytorch is 1.1.0. I've double checked all my versions with your requirements doc and they all match.
I'm just trying to run the data to get the training pipeline to work on my computer. I'll attach the output from running the program below.
Thanks for sharing your work, this is everything on PRBonn is super cool!
Input:
./train.py -d /home/stucky/catkin_ws/src/KITTI_dataset/dataset/ -ac /home/stucky/catkin_ws/src/darknet53-1024-model/arch_cfg.yaml -l /home/stucky/catkin_ws/logs/
Output:
----------
INTERFACE:
dataset /home/stucky/catkin_ws/src/KITTI_dataset/dataset/
arch_cfg /home/stucky/catkin_ws/src/darknet53-1024-model/arch_cfg.yaml
data_cfg config/labels/semantic-kitti.yaml
log /home/stucky/catkin_ws/logs/
pretrained None
----------
Commit hash (training version): b'4233111'
----------
Opening arch config file /home/stucky/catkin_ws/src/darknet53-1024-model/arch_cfg.yaml
Opening data config file config/labels/semantic-kitti.yaml
No pretrained directory found.
Copying files to /home/stucky/catkin_ws/logs/ for further reference.
Sequences folder exists! Using sequences from /home/stucky/catkin_ws/src/KITTI_dataset/dataset/sequences
parsing seq 00
parsing seq 01
parsing seq 02
parsing seq 03
parsing seq 04
parsing seq 05
parsing seq 06
parsing seq 07
parsing seq 09
parsing seq 10
Using 19130 scans from sequences [0, 1, 2, 3, 4, 5, 6, 7, 9, 10]
Sequences folder exists! Using sequences from /home/stucky/catkin_ws/src/KITTI_dataset/dataset/sequences
parsing seq 08
Using 4071 scans from sequences [8]
Loss weights from content: tensor([ 0.0000, 22.9317, 857.5627, 715.1100, 315.9618, 356.2452, 747.6170,
887.2239, 963.8915, 5.0051, 63.6247, 6.9002, 203.8796, 7.4802,
13.6315, 3.7339, 142.1462, 12.6355, 259.3699, 618.9667])
Using DarknetNet53 Backbone
Depth of backbone input = 5
Original OS: 32
New OS: 32
Strides: [2, 2, 2, 2, 2]
THCudaCheck FAIL file=/pytorch/aten/src/THC/THCGeneral.cpp line=383 error=11 : invalid argument
Decoder original OS: 32
Decoder new OS: 32
Decoder strides: [2, 2, 2, 2, 2]
Total number of parameters: 50377364
Total number of parameters requires_grad: 50377364
Param encoder 40585504
Param decoder 9786080
Param head 5780
No path to pretrained, using random init.
Training in device: cuda
Let's use 2 GPUs!
Ignoring class 0 in IoU evaluation
[IOU EVAL] IGNORE: tensor([0])
[IOU EVAL] INCLUDE: tensor([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18,
19])
Traceback (most recent call last):
File "./train.py", line 115, in <module>
trainer.train()
File "../../tasks/semantic/modules/trainer.py", line 236, in train
show_scans=self.ARCH["train"]["show_scans"])
File "../../tasks/semantic/modules/trainer.py", line 317, in train_epoch
output = model(in_vol, proj_mask)
File "/home/stucky/.local/lib/python3.5/site-packages/torch/nn/modules/module.py", line 493, in __call__
result = self.forward(*input, **kwargs)
File "/home/stucky/.local/lib/python3.5/site-packages/torch/nn/parallel/data_parallel.py", line 152, in forward
outputs = self.parallel_apply(replicas, inputs, kwargs)
File "/home/stucky/.local/lib/python3.5/site-packages/torch/nn/parallel/data_parallel.py", line 162, in parallel_apply
return parallel_apply(replicas, inputs, kwargs, self.device_ids[:len(replicas)])
File "/home/stucky/.local/lib/python3.5/site-packages/torch/nn/parallel/parallel_apply.py", line 83, in parallel_apply
raise output
File "/home/stucky/.local/lib/python3.5/site-packages/torch/nn/parallel/parallel_apply.py", line 59, in _worker
output = module(*input, **kwargs)
File "/home/stucky/.local/lib/python3.5/site-packages/torch/nn/modules/module.py", line 493, in __call__
result = self.forward(*input, **kwargs)
File "../../tasks/semantic/modules/segmentator.py", line 149, in forward
y, skips = self.backbone(x)
File "/home/stucky/.local/lib/python3.5/site-packages/torch/nn/modules/module.py", line 493, in __call__
result = self.forward(*input, **kwargs)
File "../..//backbones/darknet.py", line 167, in forward
x, skips, os = self.run_layer(x, self.conv1, skips, os)
File "../..//backbones/darknet.py", line 150, in run_layer
y = layer(x)
File "/home/stucky/.local/lib/python3.5/site-packages/torch/nn/modules/module.py", line 493, in __call__
result = self.forward(*input, **kwargs)
File "/home/stucky/.local/lib/python3.5/site-packages/torch/nn/modules/conv.py", line 338, in forward
self.padding, self.dilation, self.groups)
RuntimeError: cuda runtime error (11) : invalid argument at /pytorch/aten/src/THC/THCGeneral.cpp:383
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tano297
commented on June 19, 2024
I think this is related to this issue in turing gpus.
Can you check if installing pytorch from source solves this? It takes a couple of hours to build, but it may save you a lot of pain. Make sure to checkout the 1.1.0 branch before you build.
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Spartacus782
commented on June 19, 2024
Sorry, had a bit of a saga. I think it is training now, but there's no tensorboard output. I'm going to let it run for a while. I had this going shortly after you suggested installing pytorch from source (using your advice), but wasn't getting the tensorboard output (it just says there's no dashboards for the current data set).
Fiddling around with it I had one run where the log parameter in the ./train.py command was directed at the ~ directory. It deleted the .bashrc file and messed with several other things. Not sure what all happened, but getting all the drivers and libraries in the right place again took a little time. I still don't see any tensorboard output, but I'll let this run for a day. Using nvidia-smi there's a python3 process taking most of the memory usage on both cards, so I'm pretty sure it's going. Any guesstimate on how long the training will take on 2x2080 RTX Ti's (1 hour, 1 day, 1 week...)? Any idea why there's no Tensorboard output (the tb directory doesn't have any files in it)?
There's also a warning in the output:
Let's use 2 GPUs!
/home/stucky/BonnEnv/lib/python3.5/site-packages/torch/optim/lr_scheduler.py:123: UserWarning: Detected call of `lr_scheduler.step()` before `optimizer.step()`. In PyTorch 1.1.0 and later, you should call them in the opposite order: `optimizer.step()` before `lr_scheduler.step()`. Failure to do this will result in PyTorch skipping the first value of the learning rate schedule. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate
"https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate", UserWarning)
Ignoring class 0 in IoU evaluation
[IOU EVAL] IGNORE: tensor([0])
[IOU EVAL] INCLUDE: tensor([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18,
19])
$ ~/catkin_ws/logs$ tensorboard --logdir=. --port 5555
TensorBoard 1.13.1 at http://stucky-SC:5555 (Press CTRL+C to quit)
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KleinYuan
commented on June 19, 2024
Met the same issue, but
pip install --upgrade https://download.pytorch.org/whl/cu100/torch-1.1.0-cp36-cp36m-linux_x86_64.whl
pip install --upgrade https://download.pytorch.org/whl/cu100/torchvision-0.3.0-cp36-cp36m-linux_x86_64.whl
will do the trick.
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kosmastsk
commented on June 19, 2024
Had the same issue on Ubuntu 18.04 with Nvidia GTX 1660 Ti and cuda 10.0 installed. Removing the version from torch and torchvision packages in the requirements.txt, solved the problem for me
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Related Issues (20)
- Expected object of scalar type Long but got scalar type Int for argument #2 'target'
- Question about speed after tensorrt of rangenet++ HOT 2
- Possibility of rosifying the process HOT 1
- No error or no visualizations when executing the viusalization.py file
- Questions about the learning setting HOT 1
- Where are the pretrained models HOT 4
- Inference, and training not working on Semantic KITTI dataset. HOT 2
- index the unused points HOT 1
- KNN HOT 1
- Module not found error when running the infer function to get the prediction.
- RangeNet++
- Calculation Accuracy HOT 1
- Where is the rangenet? HOT 1
- about labels/semantic-kitti yaml
- About train my dataset result HOT 2
- IndexError: index -2147483648 is out of bounds for axis 0 with size 64 HOT 6
- About learning_map in semantic-kitti.yaml file HOT 3
- Where do the values in arch_cfg.yaml file come from, especially fov_up, fov_down, img_means, img_stds? HOT 4
- IndexError HOT 2
- Stop-gradients in skip-connections HOT 2
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