OCI runtime exec error: flag provided but not defined: -console-socket #37

ianmiell · 2018-05-05T11:05:05Z

gvisor1:2ehal1nT:G7HJX100# docker exec -ti 123 bash
OCI runtime exec failed: /var/lib/docker/runtimes/runsc did not terminate sucessfully: flag provided but not defined: -console-socket
                                                                                                                                     exec [command options] <container-id> <command> [comman
d options] || --process process.json <container-id>
                       
                       
                                                   Where "<container-id>" is the name for the instance of the container and
                                                                                                                           "<command>" is the command to be executed in the container.
                                                                                                                                                                                      "<comm
and>" can't be empty unless a "-process" flag provided.

gvisor1:2ehal1nT:G7HJX100# docker version
Client:
 Version:      18.03.1-ce
 API version:  1.37
 Go version:   go1.9.5
 Git commit:   9ee9f40
 Built:        Thu Apr 26 07:17:20 2018
 OS/Arch:      linux/amd64
 Experimental: false
 Orchestrator: swarm

Server:
 Engine:
  Version:      18.03.1-ce
  API version:  1.37 (minimum version 1.12)
  Go version:   go1.9.5
  Git commit:   9ee9f40
  Built:        Thu Apr 26 07:15:30 2018
  OS/Arch:      linux/amd64
  Experimental: false

gvisor1:2ehal1nT:G7HJX100# uname -a
Linux gvisor1 4.4.0-122-generic #146-Ubuntu SMP Mon Apr 23 15:34:04 UTC 2018 x86_64 x86_64 x86_64 GNU/Linux

Code to repro:

https://github.com/ianmiell/shutit-gvisor/blob/master/build.py

The text was updated successfully, but these errors were encountered:

Ace-Tang · 2018-05-08T12:44:32Z

I got the same error message

$ docker version
Client:
 Version:      18.03.1-ce
 API version:  1.37
 Go version:   go1.9.5
 Git commit:   9ee9f40
 Built:        Thu Apr 26 07:17:20 2018
 OS/Arch:      linux/amd64
 Experimental: false
 Orchestrator: swarm

Server:
 Engine:
  Version:      18.03.1-ce
  API version:  1.37 (minimum version 1.12)
  Go version:   go1.9.5
  Git commit:   9ee9f40
  Built:        Thu Apr 26 07:15:30 2018
  OS/Arch:      linux/amd64
  Experimental: false

fvoznika · 2018-05-08T16:23:54Z

runsc doesn't support terminal with docker exec yet. It will work if you change your command to docker run.

Ace-Tang · 2018-05-10T01:41:00Z

thanks for your reply, @fvoznika

YvesChan · 2018-07-23T10:24:03Z

Same here. So runsc cannot support docker exec with an existing container to run some commands? Neither any bugfix plan?

fvoznika · 2018-07-23T14:37:10Z

It does support docker exec, but it doesn't support it when -ti option is used.

fvoznika · 2018-08-29T22:40:00Z

Fixed by 106de21

Distributed training isn't working with PyTorch on certain A100 nodes. Adds the missing ioctl `UVM_UNMAP_EXTERNAL` allowing for certain NCCL operations to succeed when using [`torch.distributed`](https://pytorch.org/docs/stable/distributed.html), fixing distributed training. ## Reproduction This affects numerous A100 40GB and 80GB instances in our fleet. This reproduction requires 4 A100 GPUs, either 40GB or 80GB. - **NVIDIA Driver Version**: 550.54.15 - **CUDA Version**: 12.4 - **NVIDIA device**: NVIDIA A100 80GB PCIe ### Steps 1. **Install gvisor** ```bash URL="https://storage.googleapis.com/gvisor/releases/master/latest/${ARCH}" wget -nc "${URL}/runsc" "${URL}/runsc.sha512" chmod +x runsc sudo cp runsc /usr/local/bin/runsc sudo /usr/local/bin/runsc install sudo systemctl reload docker ``` 2. **Add GPU enabling gvisor options** ```json { "runtimes": { "nvidia": { "path": "nvidia-container-runtime", "runtimeArgs": [] }, "runsc": { "path": "/usr/local/bin/runsc", "runtimeArgs": ["--nvproxy", "--nvproxy-docker", "-debug-log=/tmp/runsc/", "-debug", "-strace"] } } } ``` Reload configs with `sudo systemctl reload docker`. 3. **Run reproduction NCCL test** This test creates one main process and N peer processes. Each peer process sends a torch `Tensor` to the main process using NCCL. ```Dockerfile # Dockerfile FROM python:3.9.15-slim-bullseye RUN pip install torch numpy COPY <<EOF repro.py import argparse import datetime import os import torch import torch.distributed as dist import torch.multiprocessing as mp def setup(rank, world_size): os.environ["MASTER_ADDR"] = "localhost" os.environ["MASTER_PORT"] = "12355" dist.init_process_group("nccl", rank=rank, world_size=world_size, timeout=datetime.timedelta(seconds=600)) torch.cuda.set_device(rank) def cleanup(): dist.destroy_process_group() def send_tensor(rank, world_size): try: setup(rank, world_size) # rank receiving all tensors target_rank = world_size - 1 dist.barrier() tensor = torch.ones(5).cuda(rank) if rank < target_rank: print(f"[RANK {rank}] sending tensor: {tensor}") dist.send(tensor=tensor, dst=target_rank) elif rank == target_rank: for other_rank in range(target_rank): tensor = torch.zeros(5).cuda(target_rank) dist.recv(tensor=tensor, src=other_rank) print(f"[RANK {target_rank}] received tensor from rank={other_rank}: {tensor}") print("PASS: NCCL working.") except Exception as e: print(f"[RANK {rank}] error in send_tensor: {e}") raise finally: cleanup() def main(world_size: int = 2): mp.spawn(send_tensor, args=(world_size,), nprocs=world_size, join=True) if __name__ == "__main__": parser = argparse.ArgumentParser(description="Run torch-based NCCL tests") parser.add_argument("world_size", type=int, help="number of GPUs to run test on") args = parser.parse_args() if args.world_size < 2: raise RuntimeError(f"world_size needs to be larger than 1 {args.world_size}") main(args.world_size) EOF ENTRYPOINT ["python", "repro.py", "4"] ``` Build image with: ``` docker build -f Dockerfile . ``` Then run it with: ``` sudo docker run -it --shm-size=2.00gb --runtime=runsc --gpus='"device=GPU-742ea7fc-dd4f-612c-e860-499bf200a815,GPU-94a801d8-7713-acf6-337d-338b7cfdf19e,GPU-0d19cef2-10ce-e445-a0be-3d330e36c1fd,GPU-ac5046fb-020c-93e8-2784-f44aedbc5bbd"' 040a44863fb1 ``` #### Failure (truncated) ``` ... Exception raised from recvBytes at ../torch/csrc/distributed/c10d/Utils.hpp:672 (most recent call first): frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7edda14cf897 in /usr/local/lib/python3.11/site-packages/torch/lib/libc10.so) frame #1: <unknown function> + 0x5b3a23e (0x7edd8d73a23e in /usr/local/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so) frame #2: c10d::TCPStore::doWait(c10::ArrayRef<std::string>, std::chrono::duration<long, std::ratio<1l, 1000l> >) + 0x2c7 (0x7edd8d734c87 in /usr/local/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so) frame #3: c10d::TCPStore::doGet(std::string const&) + 0x32 (0x7edd8d734f82 in /usr/local/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so) frame #4: c10d::TCPStore::get(std::string const&) + 0xa1 (0x7edd8d735fd1 in /usr/local/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so) frame #5: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7edd8d6ea371 in /usr/local/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so) frame #6: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7edd8d6ea371 in /usr/local/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so) frame #7: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7edd8d6ea371 in /usr/local/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so) frame #8: c10d::ProcessGroupNCCL::broadcastUniqueNCCLID(ncclUniqueId*, bool, std::string const&, int) + 0xa9 (0x7edd54da9189 in /usr/local/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so) frame #9: c10d::ProcessGroupNCCL::getNCCLComm(std::string const&, c10::Device&, c10d::OpType, int, bool) + 0xc50 (0x7edd54db0610 in /usr/local/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so) frame #10: c10d::ProcessGroupNCCL::recv(std::vector<at::Tensor, std::allocator<at::Tensor> >&, int, int) + 0x5f8 (0x7edd54dcf978 in /usr/local/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so) frame #11: <unknown function> + 0x5adc309 (0x7edd8d6dc309 in /usr/local/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so) frame #12: <unknown function> + 0x5ae6f10 (0x7edd8d6e6f10 in /usr/local/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so) frame #13: <unknown function> + 0x5ae6fa5 (0x7edd8d6e6fa5 in /usr/local/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so) frame #14: <unknown function> + 0x5124446 (0x7edd8cd24446 in /usr/local/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so) frame #15: <unknown function> + 0x1acf4b8 (0x7edd896cf4b8 in /usr/local/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so) frame #16: <unknown function> + 0x5aee004 (0x7edd8d6ee004 in /usr/local/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so) frame #17: <unknown function> + 0x5af36b5 (0x7edd8d6f36b5 in /usr/local/lib/python3.11/site-packages/torch/lib/libtorch_cpu.so) frame #18: <unknown function> + 0xd2fe8e (0x7edda032fe8e in /usr/local/lib/python3.11/site-packages/torch/lib/libtorch_python.so) frame #19: <unknown function> + 0x47f074 (0x7edd9fa7f074 in /usr/local/lib/python3.11/site-packages/torch/lib/libtorch_python.so) <omitting python frames> frame #35: <unknown function> + 0x29d90 (0x7edda2029d90 in /usr/lib/x86_64-linux-gnu/libc.so.6) frame #36: __libc_start_main + 0x80 (0x7edda2029e40 in /usr/lib/x86_64-linux-gnu/libc.so.6) frame #37: <unknown function> + 0x108e (0x55f950b0c08e in /usr/local/bin/python) . This may indicate a possible application crash on rank 0 or a network set up issue. ... ``` ### Fix gvisor debug logs show: ``` W0702 20:36:17.577055 445833 uvm.go:148] [ 22: 84] nvproxy: unknown uvm ioctl 66 = 0x42 ``` I've implemented that ioctl in this PR. This is the output after the fix. ``` [RANK 2] sending tensor: tensor([1., 1., 1., 1., 1.], device='cuda:2') [RANK 0] sending tensor: tensor([1., 1., 1., 1., 1.], device='cuda:0') [RANK 1] sending tensor: tensor([1., 1., 1., 1., 1.], device='cuda:1') [RANK 3] received tensor from rank=0: tensor([1., 1., 1., 1., 1.], device='cuda:3') [RANK 3] received tensor from rank=1: tensor([1., 1., 1., 1., 1.], device='cuda:3') [RANK 3] received tensor from rank=2: tensor([1., 1., 1., 1., 1.], device='cuda:3') PASS: NCCL working. ``` FUTURE_COPYBARA_INTEGRATE_REVIEW=#10610 from luiscape:master ee88734 PiperOrigin-RevId: 649146570

fvoznika closed this as completed Aug 29, 2018

amscanne pushed a commit to amscanne/gvisor that referenced this issue May 6, 2020

Replace pre-go1.11 vendoring with a go1.12 module. (google#37)

9ce9cea

derpsteb mentioned this issue Jan 25, 2024

cuCtxCreate triggers NV_ERR_INVALID_ADDRESS with H100 CC-mode on #9921

Closed

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OCI runtime exec error: flag provided but not defined: -console-socket #37

OCI runtime exec error: flag provided but not defined: -console-socket #37

ianmiell commented May 5, 2018

Ace-Tang commented May 8, 2018

fvoznika commented May 8, 2018 •

edited

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Ace-Tang commented May 10, 2018

YvesChan commented Jul 23, 2018

fvoznika commented Jul 23, 2018

fvoznika commented Aug 29, 2018

OCI runtime exec error: flag provided but not defined: -console-socket #37

OCI runtime exec error: flag provided but not defined: -console-socket #37

Comments

ianmiell commented May 5, 2018

Ace-Tang commented May 8, 2018

fvoznika commented May 8, 2018 • edited Loading

Ace-Tang commented May 10, 2018

YvesChan commented Jul 23, 2018

fvoznika commented Jul 23, 2018

fvoznika commented Aug 29, 2018

fvoznika commented May 8, 2018 •

edited

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