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Indraneil PaulIndraneil Paul
Indraneil Paul
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Indraneil Paul
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Add in CUDA 12 dockerfiles
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Evaluate.Dockerfile renamed to Docker/Evaluate.Dockerfile

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# Better use newer Python as generated code can use new features
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FROM python:3.10-slim
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FROM python:3.11-slim
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# install git, g++ and python3-tk
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RUN apt-get update && apt-get install -y git g++ python3-tk zip unzip procps r-base
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# Add a new user "wildcodeuser"
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RUN adduser --disabled-password --gecos "" wildcodeuser
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COPY . /wildcode
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# Acquire benchmark code to local
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RUN git clone https://github.com/bigcode-project/code-eval.git /wildcode
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RUN cd /wildcode && pip install . && pip install -U -I -r https://raw.githubusercontent.com/bigcode-project/wildcodebench-annotation/main/requirements.txt
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Generate.Dockerfile renamed to Docker/Generate_Cuda11.Dockerfile

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RUN adduser --disabled-password --gecos "" wildcodeuser
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# Acquire benchmark code to local
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RUN git clone https://github.com/NVIDIA/apex /wildcode
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RUN git clone https://github.com/bigcode-project/code-eval.git /wildcode
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RUN chown -R wildcodeuser:wildcodeuser /wildcode
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USER wildcodeuser

‎Docker/Generate_Cuda12.Dockerfile‎

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FROM nvidia/cuda:12.1.1-cudnn8-devel-ubuntu22.04
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SHELL ["/bin/bash", "-c"]
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# Setup Environment Variables
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ENV CUDA_HOME=/usr/local/cuda \
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PYTHONUNBUFFERED=1 \
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TORCH_CUDA_ARCH_LIST="7.0 7.5 8.0 8.6 8.9 9.0+PTX"
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# Setup System Utilities
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RUN apt-get update --yes --quiet \
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&& apt-get upgrade --yes --quiet \
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&& DEBIAN_FRONTEND=noninteractive apt-get install --yes --quiet --no-install-recommends \
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apt-utils \
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autoconf \
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automake \
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bc \
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build-essential \
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ca-certificates \
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check \
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cmake \
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curl \
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dmidecode \
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emacs \
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g++\
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gcc \
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git \
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iproute2 \
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jq \
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kmod \
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libaio-dev \
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libcurl4-openssl-dev \
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libgl1-mesa-glx \
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libglib2.0-0 \
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libgomp1 \
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libibverbs-dev \
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libnuma-dev \
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libnuma1 \
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libomp-dev \
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libsm6 \
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libssl-dev \
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libsubunit-dev \
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libsubunit0 \
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libtool \
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libxext6 \
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libxrender-dev \
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make \
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moreutils \
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net-tools \
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ninja-build \
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openssh-client \
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openssh-server \
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openssl \
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pkg-config \
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python3-dev \
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software-properties-common \
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sudo \
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unzip \
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util-linux \
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vim \
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wget \
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zlib1g-dev \
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&& apt-get autoremove \
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&& apt-get clean \
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&& rm -rf /var/lib/apt/lists/
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# Setup base Python to bootstrap Mamba
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RUN add-apt-repository --yes ppa:deadsnakes/ppa \
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&& apt-get update --yes --quiet
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RUN DEBIAN_FRONTEND=noninteractive apt-get install --yes --quiet --no-install-recommends \
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python3.11 \
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python3.11-dev \
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python3.11-distutils \
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python3.11-lib2to3 \
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python3.11-gdbm \
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python3.11-tk \
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pip
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RUN update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.11 999 \
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&& update-alternatives --config python3 \
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&& ln -s /usr/bin/python3 /usr/bin/python
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RUN pip install --upgrade pip
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# Setup optimized Mamba environment with required PyTorch dependencies
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RUN wget -O /tmp/Miniforge.sh https://github.com/conda-forge/miniforge/releases/download/24.3.0-0/Mambaforge-24.3.0-0-Linux-x86_64.sh \
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&& bash /tmp/Miniforge.sh -b -p /Miniforge \
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&& source /Miniforge/etc/profile.d/conda.sh \
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&& source /Miniforge/etc/profile.d/mamba.sh \
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&& mamba update -y -q -n base -c defaults mamba \
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&& mamba create -y -q -n Code-Eval python=3.11 setuptools=69.5.1 \
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&& mamba activate Code-Eval \
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&& mamba install -y -q -c conda-forge \
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charset-normalizer \
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gputil \
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ipython \
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numpy \
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pandas \
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scikit-learn \
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wandb \
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&& mamba install -y -q -c intel \
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"mkl==2023" \
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"mkl-static==2023" \
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"mkl-include==2023" \
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&& mamba install -y -q -c pytorch magma-cuda121 \
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&& mamba clean -a -f -y
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# Install VLLM precompiled with appropriate CUDA and ensure PyTorch is installed form the same version channel
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RUN source /Miniforge/etc/profile.d/conda.sh \
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&& source /Miniforge/etc/profile.d/mamba.sh \
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&& mamba activate Code-Eval \
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&& pip install https://github.com/vllm-project/vllm/releases/download/v0.4.0/vllm-0.4.0-cp311-cp311-manylinux1_x86_64.whl \
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--extra-index-url https://download.pytorch.org/whl/cu121
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# Install Flash Attention
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RUN source /Miniforge/etc/profile.d/conda.sh \
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&& source /Miniforge/etc/profile.d/mamba.sh \
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&& mamba activate Code-Eval \
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&& export MAX_JOBS=$(($(nproc) - 2)) \
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&& pip install --no-cache-dir ninja packaging psutil \
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&& pip install flash-attn==2.5.8 --no-build-isolation
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# Add a new user "wildcodeuser"
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RUN adduser --disabled-password --gecos "" wildcodeuser
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# Acquire benchmark code to local
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RUN git clone https://github.com/bigcode-project/code-eval.git /wildcode
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RUN chown -R wildcodeuser:wildcodeuser /wildcode
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USER wildcodeuser
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# Install Code-Eval and pre-load the dataset
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RUN source /Miniforge/etc/profile.d/conda.sh \
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&& source /Miniforge/etc/profile.d/mamba.sh \
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&& mamba activate Code-Eval \
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&& pip install wild-code --upgrade \
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&& python -c "from wildcode.data import get_wildcodebench; get_wildcodebench()"
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WORKDIR /wildcode
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# Declare an argument for the huggingface token
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ARG HF_TOKEN
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RUN if [[ -n "$HF_TOKEN" ]] ; then /Miniforge/envs/Code-Eval/bin/huggingface-cli login --token $HF_TOKEN ; \
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else echo "No HuggingFace token specified. Access to gated or private models will be unavailable." ; fi
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ENTRYPOINT ["/Miniforge/envs/Code-Eval/bin/python", "-m", "wildcode.generate"]

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