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Answered
Hi All, I Was Trying To Use Clearml-Task To Run A Custom Docker(With Poetry To Install All The Python Dependencies And Activated The Environment) Using Clearml Gpu, But It Seems Like Clearml Always Create A Virtual Environment And Run The Python Script Fr

Hi all, I was trying to use clearml-task to run a custom docker(with poetry to install all the python dependencies and activated the environment) using clearml GPU, but it seems like clearml always create a virtual environment and run the python script from /root/.clearml/venvs-builds/3.10/bin/python . Is there a way that I can have the clearml-task to automatically activated a virtual environment use the activated custom virtual environment in my docker and run the scripts from there instead of always creating a new venv inheriting from the clearml system_site_packages? I noticed that clearml.conf has a configuration agent.docker_use_activated_venv , but I am not sure how to enable it from clearml-task

  
  
Posted 2 years ago
Votes Newest

Answers 38


Thanks for the detials @<1597762318140182528:profile|EnchantingPenguin77>

clearml.Auto-Scaler - INFO - New instance b97e702d-e2b3-4f28-adab-be59648601ea listening to test-gpu queue

This looks like a new agent was spined on your EC2 account, can you see it in the "Workers" page ?

  
  
Posted 2 years ago

well I do not think you set your pytorch lightining to use cuda:

GPU available: True (cuda), used: False
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
/code/.venv/lib/python3.9/site-packages/lightning/pytorch/trainer/setup.py:176: PossibleUserWarning: GPU available but not used. Set `accelerator` and `devices` using `Trainer(accelerator='gpu', devices=1)`.
  
  
Posted 2 years ago

I see, seems like the -args for scripts didn't passed to the docker:

--script fluoro_motion_detection/src/run/main.py \
--args experiment=example.yaml \
  
  
Posted 2 years ago

I see, like that?
image

  
  
Posted 2 years ago

@<1523701205467926528:profile|AgitatedDove14> I'm trying to run Clearml GPU compute(RTX 3080) with pytorch-lightning but keep getting CUDA error. Is there any specific CUDA/Ubuntu/torch/python version required? I tried several different version but can't make it work

FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu22.04 as telos_algorithms
  File "/code/.venv/lib/python3.10/site-packages/lightning/pytorch/trainer/trainer.py", line 1013, in _run_stage
    with isolate_rng():
  File "/.pyenv/versions/3.10.9/lib/python3.10/contextlib.py", line 135, in __enter__
    return next(self.gen)
  File "/code/.venv/lib/python3.10/site-packages/lightning/pytorch/utilities/seed.py", line 42, in isolate_rng
    states = _collect_rng_states(include_cuda)
  File "/code/.venv/lib/python3.10/site-packages/lightning/fabric/utilities/seed.py", line 115, in _collect_rng_states
    states["torch.cuda"] = torch.cuda.get_rng_state_all()
  File "/code/.venv/lib/python3.10/site-packages/torch/cuda/random.py", line 39, in get_rng_state_all
    results.append(get_rng_state(i))
  File "/code/.venv/lib/python3.10/site-packages/torch/cuda/random.py", line 22, in get_rng_state
    _lazy_init()
  File "/code/.venv/lib/python3.10/site-packages/torch/cuda/__init__.py", line 247, in _lazy_init
    torch._C._cuda_init()
RuntimeError: Unexpected error from cudaGetDeviceCount(). Did you run some cuda functions before calling NumCudaDevices() that might have already set an error? Error 804: forward compatibility was attempted on non supported HW
Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.
  
  
Posted 2 years ago

None
See: Add an experiment hyperparameter:
and add gpu : True

  
  
Posted 2 years ago

I was trying to run python main.py experiemnt=example.yaml

  
  
Posted 2 years ago

I've added gpu:True to my hydra config file but the GPU is still not used

  
  
Posted 2 years ago