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# 1. git clone & cd to your submission repository | ||
# 2. mount `.` to container `/workdir`: | ||
docker run --rm -it --gpus all -p 6006:6006 \ | ||
-v /path/to/data:/mnt/share/petric:ro \ | ||
-v .:/workdir -w /workdir synerbi/sirf:edge-gpu /bin/bash | ||
# 3. optionally, conda/pip/apt install environment.yml/requirements.txt/apt.txt | ||
# 4. install metrics & run your submission | ||
# 3. install metrics & GPU libraries | ||
conda install monai tensorboard tensorboardx jupytext cudatoolkit=11.8 | ||
pip uninstall torch # monai installs pytorch (CPU), so remove it | ||
pip install tensorflow[and-cuda]==2.14 # last to support cu118 | ||
pip install torch --index-url https://download.pytorch.org/whl/cu118 | ||
pip install git+https://github.com/TomographicImaging/Hackathon-000-Stochastic-QualityMetrics | ||
# 4. optionally, conda/pip/apt install environment.yml/requirements.txt/apt.txt | ||
# 5. run your submission | ||
python petric.py & | ||
# 5. optionally, serve logs at <http://localhost:6006> | ||
# 6. optionally, serve logs at <http://localhost:6006> | ||
tensorboard --bind_all --port 6006 --logdir ./output |