125 lines
4.5 KiB
Docker
125 lines
4.5 KiB
Docker
# ---------- llama.cpp Build Stage
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FROM nvidia/cuda:13.2.1-cudnn-devel-ubuntu24.04 AS builder
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ENV DEBIAN_FRONTEND=noninteractive
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# Install build tools, CMake, Git, and documentation tools
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RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
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--mount=type=cache,target=/var/lib/apt,sharing=locked \
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apt-get update && apt-get install -y --no-install-recommends \
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build-essential \
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cmake \
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git \
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ninja-build \
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ca-certificates \
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libgomp1 \
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pandoc \
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&& rm -rf /var/lib/apt/lists/*
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WORKDIR /workspace
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# Clone llama.cpp repository
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ARG LLAMA_CPP_TAG=master
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RUN git clone --depth 1 --branch ${LLAMA_CPP_TAG} https://github.com/ggerganov/llama.cpp.git .
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# Build llama.cpp, the ldconfig is important
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RUN echo "/usr/local/cuda-13.2/compat" > /etc/ld.so.conf.d/988-cuda-compat.conf && ldconfig
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RUN cmake -B build -S . \
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-DCMAKE_BUILD_TYPE=Release \
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-DGGML_CUDA=ON \
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-DCMAKE_INSTALL_PREFIX=/install \
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-DCMAKE_CUDA_ARCHITECTURES=120 \
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-DLLAMA_BUILD_TESTS=OFF \
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-DLLAMA_BUILD_EXAMPLES=ON \
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&& cmake --build build --config Release -j $(nproc) \
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&& cmake --install build \
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&& rm -rf build
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# Generate or stage manpages into /install/share/man
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# If manpages are prebuilt or markdown docs exist, compile/place them in standard sections:
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RUN mkdir -p /install/share/man/man1 && \
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for doc in docs/*.md; do \
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[ -f "$doc" ] || continue; \
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base=$(basename "$doc" .md); \
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pandoc "$doc" -s -t man -o "/install/share/man/man1/${base}.1" 2>/dev/null || true; \
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done
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# ---------- Python virtual environment builder
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FROM nvidia/cuda:13.2.1-cudnn-devel-ubuntu24.04 AS venv-builder
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RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
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--mount=type=cache,target=/var/lib/apt,sharing=locked \
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apt update && apt-get install -y --no-install-recommends \
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python3-pip \
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python3-dev \
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python3-venv \
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git
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WORKDIR /workspace
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RUN python3 -m venv /workspace/py-venv
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ENV PATH="/workspace/py-venv/bin:${PATH}"
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RUN --mount=type=cache,target=/root/.cache/pip,sharing=locked pip3 install torch torchvision torchaudio --upgrade --index-url \
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https://download.pytorch.org/whl/cu132/
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# Fetch convert_to_quant, and install it into our python venv.
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RUN git clone --depth=1 https://github.com/silveroxides/convert_to_quant && \
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cd convert_to_quant && pip3 install -r requirements.txt && pip3 install .
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# Install heretic-llm
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RUN --mount=type=cache,target=/root/.cache/pip,sharing=locked pip3 install heretic-llm
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# Install zefie's nvfp4 quant requirements
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COPY --chmod=0644 requirements.txt /workspace/requirements.txt
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RUN --mount=type=cache,target=/root/.cache/pip,sharing=locked pip3 install -r /workspace/requirements.txt
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# ---------- Main image
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FROM nvidia/cuda:13.2.1-cudnn-devel-ubuntu24.04 AS runner
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ENV DEBIAN_FRONTEND=noninteractive
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# "Unminify" nvidia container to enable man pages
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RUN rm -f /etc/dpkg/dpkg.cfg.d/excludes && \
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rm -f /etc/apt/apt.conf.d/docker-clean && \
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rm -f /etc/apt/apt.conf.d/01-nodoc && \
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rm -f /usr/bin/man && \
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dpkg-divert --quiet --remove /usr/bin/man
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RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
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--mount=type=cache,target=/var/lib/apt,sharing=locked \
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apt update && apt-get install -y \
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python3 \
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man \
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man-db \
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wget \
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bzip2 \
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curl
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WORKDIR /opt/nvfp4
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RUN mkdir nvfp4_gguf_quant
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COPY --exclude=__pycache__ nvfp4gguf ./nvfp4_gguf_quant/nvfp4gguf
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COPY --chmod=0644 gguf_to_nvfp4_gguf.py hf_to_nvfp4_gguf.py hf_to_nvfp4_safetensors.py safetensors_to_nvfp4_gguf.py hf_info.py gguf_info.py ./nvfp4_gguf_quant/
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COPY --chmod=0644 docker/README.txt /workspace/README.txt
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COPY --chmod=0755 --exclude=README.txt docker/* /usr/local/bin/
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# Install manpages for zefie's nvfp4 quant scripts, ctq and heretic
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RUN mkdir -p /usr/local/share/man/man1
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COPY --chmod=0644 man/man1/* /usr/local/share/man/man1/
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# Copy llama.cpp compiled binaries, manpages and shared libraries from builder
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COPY --from=builder /install/bin/ /usr/local/bin/
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COPY --from=builder /install/lib/ /usr/local/lib/
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COPY --from=builder /install/share/man/ /usr/share/man/
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# Set up a minimal llama.cpp source for conversions
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RUN mkdir /opt/nvfp4/llama.cpp
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COPY --from=builder /workspace/conversion /opt/nvfp4/llama.cpp/conversion/
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COPY --from=builder --chmod=0644 /workspace/*.py /opt/nvfp4/llama.cpp/
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COPY --from=venv-builder /workspace/py-venv /opt/nvfp4/py-venv
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ENV PATH="/opt/nvfp4/py-venv/bin:${PATH}"
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# Finalize and settle at /workspace
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ENV DEBIAN_FRONTEND=
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WORKDIR /workspace |