wehub-resource-sync
48 lines
1.5 KiB
Docker
48 lines
1.5 KiB
Docker
# Use the official PyTorch image as the base image
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FROM pytorch/pytorch:latest
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# FROM pytorch/pytorch:2.4.1-cuda12.1-cudnn9-runtime
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# torch.__version__ == '2.4.1+cu121' in "gcr.io/kaggle-gpu-images/python"
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# Install additional tools
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RUN apt-get update && apt-get install -y \
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curl \
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vim \
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git \
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build-essential \
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git-lfs \
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unzip && \
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rm -rf /var/lib/apt/lists/*
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# Default command to keep the container running
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ENTRYPOINT ["/workspace/run/entrypoint.sh"]
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RUN conda init bash
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# MLE-Bench
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RUN conda create -n mlebench python==3.11 pip -y
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RUN cd /workspace && git clone https://github.com/openai/mle-bench.git
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RUN cd /workspace/mle-bench && git lfs fetch --all
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RUN cd /workspace/mle-bench && git lfs pull
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RUN cd /workspace/mle-bench && conda run -n mlebench pip install -e .
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# Kaggle Environment
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COPY ./kaggle_environment.yaml /workspace
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RUN cd /workspace && conda env create -f /workspace/kaggle_environment.yaml
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# RD-Agent
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RUN cd /workspace && git clone https://github.com/microsoft/RD-Agent
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RUN cd RD-Agent && git fetch && make dev
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# litellm
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RUN cd /workspace && mkdir -p litellm-srv
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RUN cd /workspace/litellm-srv && curl https://raw.githubusercontent.com/you-n-g/deploy/refs/heads/master/configs/python/litellm.trapi.yaml -o litellm.trapi.yaml
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RUN pip install 'litellm[proxy]'
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RUN pip install git+https://github.com/you-n-g/litellm@add_mi_cred_pr
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run cd /workspace && mkdir -p run
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COPY ./entrypoint.sh /workspace/run
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WORKDIR /workspace/RD-Agent/
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