Dockerfile

ARG CUDA
ARG DIST
ARG TARGET
FROM --platform=linux/amd64 nvidia/cuda:${CUDA}-${TARGET}-${DIST}

ARG DEBIAN_FRONTEND="noninteractive"
ENV TZ="America/Los_Angeles"

# Install base tools.
RUN apt-get update && apt-get install -y \
    build-essential \
    curl \
    git \
    jq \
    language-pack-en \
    make \
    sudo \
    unzip \
    vim \
    wget \
    parallel \
    iputils-ping \
    tmux

ARG BEAKER_VERSION
RUN curl --silent \
    --connect-timeout 5 \
    --max-time 10 \
    --retry 5 \
    --retry-delay 0 \
    --retry-max-time 40 \
    --output beaker.tar.gz \
    "https://beaker.org/api/v3/release/cli?os=linux&arch=amd64&version=${BEAKER_VERSION}" \
    && tar -zxf beaker.tar.gz -C /usr/local/bin/ ./beaker \
    && rm beaker.tar.gz

# This ensures the dynamic linker (or NVIDIA's container runtime, I'm not sure)
# puts the right NVIDIA things in the right place (that THOR requires).
ENV NVIDIA_DRIVER_CAPABILITIES=graphics,utility,compute

# Install conda. We give anyone in the users group the ability to run
# conda commands and install packages in the base (default) environment.
# Things installed into the default environment won't persist, but we prefer
# convenience in this case and try to make sure the user is aware of this
# with a message that's printed when the session starts.
RUN wget https://repo.anaconda.com/miniconda/Miniconda3-py310_23.1.0-1-Linux-x86_64.sh \
    && echo "32d73e1bc33fda089d7cd9ef4c1be542616bd8e437d1f77afeeaf7afdb019787 Miniconda3-py310_23.1.0-1-Linux-x86_64.sh" \
        | sha256sum --check \
    && bash Miniconda3-py310_23.1.0-1-Linux-x86_64.sh -b -p /opt/miniconda3 \
    && rm Miniconda3-py310_23.1.0-1-Linux-x86_64.sh

ENV PATH=/opt/miniconda3/bin:/opt/miniconda3/condabin:$PATH
ENV LD_LIBRARY_PATH=/usr/local/cuda/lib:/usr/local/cuda/lib64:$LD_LIBRARY_PATH

# Install a few additional utilities via pip
RUN /opt/miniconda3/bin/pip install --no-cache-dir \
    gpustat \
    jupyter \
    beaker-gantry \
    oocmap

# Ensure users can modify their container environment.
RUN echo '%users ALL=(ALL) NOPASSWD:ALL' >> /etc/sudoers

# Make the base image friendlier for interactive workloads. This makes things like the man command
# work.
RUN yes | unminimize

# Install MLNX OFED user-space drivers
# See https://docs.nvidia.com/networking/pages/releaseview.action?pageId=15049785#Howto:DeployRDMAacceleratedDockercontaineroverInfiniBandfabric.-Dockerfile
ENV MOFED_VER 5.8-1.1.2.1
ENV OS_VER ubuntu20.04
ENV PLATFORM x86_64
RUN wget --quiet https://content.mellanox.com/ofed/MLNX_OFED-${MOFED_VER}/MLNX_OFED_LINUX-${MOFED_VER}-${OS_VER}-${PLATFORM}.tgz && \
    tar -xvf MLNX_OFED_LINUX-${MOFED_VER}-${OS_VER}-${PLATFORM}.tgz && \
    MLNX_OFED_LINUX-${MOFED_VER}-${OS_VER}-${PLATFORM}/mlnxofedinstall --basic --user-space-only --without-fw-update -q && \
    rm -rf MLNX_OFED_LINUX-${MOFED_VER}-${OS_VER}-${PLATFORM} && \
    rm MLNX_OFED_LINUX-${MOFED_VER}-${OS_VER}-${PLATFORM}.tgz

# The -l flag makes bash act as a login shell and load /etc/profile, etc.
ENTRYPOINT ["bash", "-l"]

WORKDIR /stage/

# TODO When updating flash-attn or torch in the future, make sure to update the version in the requirements.txt file. 
ENV HF_HUB_ENABLE_HF_TRANSFER=1
COPY requirements.txt .
RUN pip install --upgrade pip "setuptools<70.0.0" wheel 
# TODO, unpin setuptools when this issue in flash attention is resolved
RUN pip install torch==2.4.0 torchvision==0.19.0 torchaudio==2.4.0 --index-url https://download.pytorch.org/whl/cu121
RUN pip install packaging
RUN pip install flash-attn==2.6.3 --no-build-isolation
RUN pip install -r requirements.txt

# NLTK download
RUN python -m nltk.downloader punkt
COPY open_instruct open_instruct
COPY oe-eval-internal oe-eval-internal

# install the package in editable mode
COPY pyproject.toml .
RUN pip install -e .
COPY .git/ ./.git/
COPY eval eval
COPY configs configs
COPY scripts scripts
COPY mason.py mason.py
RUN chmod +x scripts/*

# for interactive session
RUN chmod -R 777 /stage/