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[BuildOcl] Fatal error: cannot open file, Too many open files #2911

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xelibrion opened this issue Apr 21, 2024 · 8 comments
Closed

[BuildOcl] Fatal error: cannot open file, Too many open files #2911

xelibrion opened this issue Apr 21, 2024 · 8 comments

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@xelibrion
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xelibrion commented Apr 21, 2024

Hey folks, I'm curious if there's a regression of #962?

I'm running ROCm 6.0.2 and this is the error that I get. I've seen this behaviour on ROCm 5.7 as well I think, except my Python process would just crash without any reasonable output/logs.
With the never version of PyTorch at least there's a log clearly stating a reason.

I tried setting a higher ulimit ulimit -Sn 2048 as suggested in #962, but number of open files just kept rising (as reported by watch 'ls /proc/8757/fd | wc -l'. It took 4x time to hit this new limit, but the program would crash eventually anyway.

Debug info:

GPU:   gfx1100 AMD Radeon RX 7900 XTX
Kernel version: 6.6.28-gentoo-x86_64
ROCm version: 6.0.2
PyTorch version: 
- torch==2.4.0.dev20240421+rocm6.0
- pytorch-triton-rocm==3.0.0+0a22a91d04
MIOpen(HIP): Error [Do] 'amd_comgr_do_action(kind, handle, in.GetHandle(), out.GetHandle())' AMD_COMGR_ACTION_COMPILE_SOURCE_WITH_DEVICE_LIBS_TO_BC: ERROR 

MIOpen(HIP): Error [BuildOcl] comgr status = ERROR (1)
MIOpen(HIP): Warning [BuildOcl] fatal error: cannot open file '/tmp/comgr-1516b6/rocm/amdgcn/bitcode/opencl.bc': Too many open files
1 error generated.

MIOpen Error: /long_pathname_so_that_rpms_can_package_the_debug_info/src/extlibs/MLOpen/src/hipoc/hipoc_program.cpp:304: Code object build failed. Source: MIOpenBatchNormFwdTrainSpatial.cl
Traceback (most recent call last):
  File "/home/xelibrion/projects/FastSpeech2/train.py", line 288, in <module>
    main(args, configs)
  File "/home/xelibrion/projects/FastSpeech2/train.py", line 149, in main
    output = model(*(batch[2:]))
  File "/home/xelibrion/anaconda3/envs/FastSpeech2/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/home/xelibrion/anaconda3/envs/FastSpeech2/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/xelibrion/anaconda3/envs/FastSpeech2/lib/python3.9/site-packages/torch/nn/parallel/data_parallel.py", line 183, in forward
    return self.module(*inputs[0], **module_kwargs[0])
  File "/home/xelibrion/anaconda3/envs/FastSpeech2/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/home/xelibrion/anaconda3/envs/FastSpeech2/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/xelibrion/projects/FastSpeech2/model/fastspeech2.py", line 97, in forward
    postnet_output = self.postnet(output) + output
  File "/home/xelibrion/anaconda3/envs/FastSpeech2/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/home/xelibrion/anaconda3/envs/FastSpeech2/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/xelibrion/projects/FastSpeech2/transformer/Layers.py", line 134, in forward
    x = F.dropout(self.convolutions[-1](x), 0.5, self.training)
  File "/home/xelibrion/anaconda3/envs/FastSpeech2/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/home/xelibrion/anaconda3/envs/FastSpeech2/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/xelibrion/anaconda3/envs/FastSpeech2/lib/python3.9/site-packages/torch/nn/modules/container.py", line 217, in forward
    input = module(input)
  File "/home/xelibrion/anaconda3/envs/FastSpeech2/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/home/xelibrion/anaconda3/envs/FastSpeech2/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/xelibrion/anaconda3/envs/FastSpeech2/lib/python3.9/site-packages/torch/nn/modules/batchnorm.py", line 175, in forward
    return F.batch_norm(
  File "/home/xelibrion/anaconda3/envs/FastSpeech2/lib/python3.9/site-packages/torch/nn/functional.py", line 2511, in batch_norm
    return torch.batch_norm(
RuntimeError: miopenStatusUnknownError
@atamazov
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@xelibrion

I'm curious if there's a regression of #962?

We do not see evidence of this from other sources.

What version of MIOpen are you using? Has it ever worked and with what version?

If you build MIOpen yourself, then please attach output of CMake.

Kernel version: 6.6.28-gentoo-x86_64

I am afraid you are using Linux distribution which is not officially supported. In this case our support options are limited. Of course we'll try to help, but please aware.

@xelibrion
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@atamazov thanks for the pointer. Closing the issue now that I realised that some dependencies (comgr most notably) on my OS are horribly out of date.

@xelibrion xelibrion reopened this Apr 28, 2024
@xelibrion
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xelibrion commented Apr 28, 2024

@atamazov I was able to reproduce exactly the same problem using one of the ROCm docker images.

Docker image:

rocm/dev-ubuntu-22.04:6.1

Pytorch is installed in the container via (latest stable version)

pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.0

Docker command (please note --ulimit nofile=1024:1024):

docker run -it --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --device=/dev/kfd --device=/dev/dri --group-add video --ipc=host --shm-size 8G -v $PWD:/fastspeech -v $HOME/.cache/pip-docker:/root/.cache/pip --ulimit nofile=1024:1024 rocm/dev-ubuntu-22.04:6.1

By default Docker has a fairly high limit on number of open files (I think it was something like 256k by default). I'm curious to know if this is indeed a problem, or if I should just up the limit on my host and live with it?

root@6a67cdf4199e:/fastspeech# python3 train.py -p config/LJSpeech/preprocess.yaml -m config/LJSpeech/model.yaml -t config/LJSpeech/train.yaml --restore_step 70000
Prepare training ...
Loading model...
ScheduledOptim: batch_scale = 1, lr_scale = 1.0, init_lr = 0.0625
nn.DataParallel...
Init loss...
Number of FastSpeech2 Parameters: 35159361
/usr/local/lib/python3.10/dist-packages/torch/nn/utils/weight_norm.py:28: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.
  warnings.warn("torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.")
Removing weight norm...
Step 70200/900000, Total Loss: 1.0916, Mel Loss: 0.4467, Mel PostNet Loss: 0.4461, Pitch Loss: 0.0916, Energy Loss: 0.0616, Duration Loss: 0.0458
Step 70400/900000, Total Loss: 1.1366, Mel Loss: 0.4462, Mel PostNet Loss: 0.4454, Pitch Loss: 0.1320, Energy Loss: 0.0687, Duration Loss: 0.0443
Training:   8%|█████████████▊                                                                                                                                                                  | 70435/900000 [09:04<230:56:52,  1.00s/it]MIOpen(HIP): Error [Do] 'amd_comgr_do_action(kind, handle, in.GetHandle(), out.GetHandle())' AMD_COMGR_ACTION_COMPILE_SOURCE_WITH_DEVICE_LIBS_TO_BC: ERROR (1)                                          | 108/197 [09:03<07:05,  4.78s/it]
MIOpen(HIP): Error [BuildOcl] comgr status = ERROR (1)
MIOpen(HIP): Warning [BuildOcl] fatal error: cannot open file '/tmp/comgr-c3205a/rocm/amdgcn/bitcode/opencl.bc': Too many open files
1 error generated.

MIOpen Error: /long_pathname_so_that_rpms_can_package_the_debug_info/src/extlibs/MLOpen/src/hipoc/hipoc_program.cpp:304: Code object build failed. Source: MIOpenBatchNormFwdTrainSpatial.cl
Traceback (most recent call last):
  File "/fastspeech/train.py", line 288, in <module>
    main(args, configs)
  File "/fastspeech/train.py", line 149, in main
    output = model(*(batch[2:]))
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/parallel/data_parallel.py", line 183, in forward
    return self.module(*inputs[0], **module_kwargs[0])
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/fastspeech/model/fastspeech2.py", line 97, in forward
    postnet_output = self.postnet(output) + output
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/fastspeech/transformer/Layers.py", line 133, in forward
    x = F.dropout(torch.tanh(self.convolutions[i](x)), 0.5, self.training)
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/container.py", line 217, in forward
    input = module(input)
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1541, in _call_impl
    return forward_call(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/batchnorm.py", line 175, in forward
    return F.batch_norm(
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/functional.py", line 2509, in batch_norm
    return torch.batch_norm(
RuntimeError: miopenStatusUnknownError

List of open files:

Open files
root@d29b198beff4:/# find /proc/224/fd | xargs -I {} readlink {}
/dev/pts/0
/dev/pts/0
/dev/pts/0
/dev/kfd
anon_inode:[eventfd]
/usr/local/lib/python3.10/dist-packages/torch/lib/librccl.so
/usr/local/lib/python3.10/dist-packages/torch/lib/libmagma.so
/dev/dri/renderD128
/usr/local/lib/python3.10/dist-packages/torch/lib/librocsolver.so
/usr/local/lib/python3.10/dist-packages/torch/lib/librocblas.so
/usr/local/lib/python3.10/dist-packages/torch/lib/librocsparse.so
/usr/local/lib/python3.10/dist-packages/torch/lib/librocfft.so
/usr/local/lib/python3.10/dist-packages/torch/lib/librocrand.so
/usr/local/lib/python3.10/dist-packages/torch/lib/libhipblaslt.so
/usr/local/lib/python3.10/dist-packages/torch/lib/libMIOpen.so
/usr/local/lib/python3.10/dist-packages/torch/lib/libtorch_hip.so
/tmp/miopen-lockfiles/ae8826c819ac18d7f58ce1cfbd6bad4f_gfx1100_48.HIP.3_00_0_f34a90f76-dirty.ufdb.txt.lock
/root/.config/miopen/gfx1100_48_1.1.0.udb
/root/.config/miopen/gfx1100_48_1.1.0.udb-wal
/root/.config/miopen/gfx1100_48_1.1.0.udb-shm
/root/.cache/miopen/3.0.0.f34a90f76-dirty/gfx1100_48.ukdb
/root/.cache/miopen/3.0.0.f34a90f76-dirty/gfx1100_48.ukdb-wal
/root/.cache/miopen/3.0.0.f34a90f76-dirty/gfx1100_48.ukdb-shm
/tmp/miopen-interim-hsaco-4276-c9ab-a276-246d/file (deleted)
/tmp/miopen-interim-hsaco-7eec-fae5-ef3d-8707/file (deleted)
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/tmp/miopen-lockfiles/d41d8cd98f00b204e9800998ecf8427e_:memory:gfx1100.lock
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@atamazov
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@xelibrion Thanks for the logs. I recommend compacting comments that contain long console logs, see https://github.com/ROCm/MIOpen/wiki/How-to-insert-console-logs-into-github-pages.

@atamazov
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@xelibrion The reason of the issue is related to HIP runtime problem that enforced us to use interim code object files (as a workaround). The workaround was removed in #2225, the fix was first released in MIOpen 3.1.0 (https://github.com/ROCm/MIOpen/releases/tag/rocm-6.1.0).

I suspect that PyTorch from https://download.pytorch.org/whl/rocm6.0 does not contain the necessary fixes, and you need to use the rocm6.1 based one. Possibly you can get it from https://download.pytorch.org/whl/nightly/rocm6.1.

@xelibrion
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@atamazov unfortunately the url https://download.pytorch.org/whl/nightly/rocm6.1 does not seem to have a version of pytorch built against 6.1 yet.
How closely do you guys work with the Pytorch team? Are you able to request a Pytorch build with ROCm 6.1?

@atamazov
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@xelibrion I've looked at https://rocm.docs.amd.com/projects/radeon/en/latest/docs/install/install-pytorch.html, and that led me to
http://repo.radeon.com/rocm/manylinux/rocm-rel-6.1/ where files like torch-2.1.2+rocm6.1-cp310-cp310-linux_x86_64.whl can be found. Hope this helps.

@xelibrion
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@atamazov thanks, it does indeed - I did not encounter any issues with that build. Closing the issue.

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