303 lines
10 KiB
Docker
303 lines
10 KiB
Docker
# Rust builder
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FROM lukemathwalker/cargo-chef:latest-rust-1.80 AS chef
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WORKDIR /usr/src
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ARG CARGO_REGISTRIES_CRATES_IO_PROTOCOL=sparse
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FROM chef AS planner
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COPY Cargo.lock Cargo.lock
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COPY Cargo.toml Cargo.toml
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COPY rust-toolchain.toml rust-toolchain.toml
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COPY proto proto
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COPY benchmark benchmark
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COPY router router
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COPY backends backends
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COPY launcher launcher
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RUN cargo chef prepare --recipe-path recipe.json
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FROM chef AS builder
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RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
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python3.11-dev
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RUN PROTOC_ZIP=protoc-21.12-linux-x86_64.zip && \
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curl -OL https://github.com/protocolbuffers/protobuf/releases/download/v21.12/$PROTOC_ZIP && \
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unzip -o $PROTOC_ZIP -d /usr/local bin/protoc && \
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unzip -o $PROTOC_ZIP -d /usr/local 'include/*' && \
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rm -f $PROTOC_ZIP
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COPY --from=planner /usr/src/recipe.json recipe.json
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RUN cargo chef cook --profile release-opt --recipe-path recipe.json
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ARG GIT_SHA
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ARG DOCKER_LABEL
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COPY Cargo.toml Cargo.toml
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COPY rust-toolchain.toml rust-toolchain.toml
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COPY proto proto
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COPY benchmark benchmark
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COPY router router
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COPY backends backends
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COPY launcher launcher
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RUN cargo build --profile release-opt
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RUN cargo build --profile release-opt
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# Python builder
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# Adapted from: https://github.com/pytorch/pytorch/blob/master/Dockerfile
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FROM nvidia/cuda:12.4.1-devel-ubuntu22.04 AS pytorch-install
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# NOTE: When updating PyTorch version, beware to remove `pip install nvidia-nccl-cu12==2.22.3` below in the Dockerfile. Context: https://github.com/huggingface/text-generation-inference/pull/2099
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ARG PYTORCH_VERSION=2.4.0
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ARG PYTHON_VERSION=3.11
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# Keep in sync with `server/pyproject.toml
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ARG CUDA_VERSION=12.4
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ARG MAMBA_VERSION=24.3.0-0
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ARG CUDA_CHANNEL=nvidia
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ARG INSTALL_CHANNEL=pytorch
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# Automatically set by buildx
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ARG TARGETPLATFORM
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ENV PATH /opt/conda/bin:$PATH
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RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
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build-essential \
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ca-certificates \
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ccache \
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curl \
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git && \
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rm -rf /var/lib/apt/lists/*
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# Install conda
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# translating Docker's TARGETPLATFORM into mamba arches
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RUN case ${TARGETPLATFORM} in \
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"linux/arm64") MAMBA_ARCH=aarch64 ;; \
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*) MAMBA_ARCH=x86_64 ;; \
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esac && \
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curl -fsSL -v -o ~/mambaforge.sh -O "https://github.com/conda-forge/miniforge/releases/download/${MAMBA_VERSION}/Mambaforge-${MAMBA_VERSION}-Linux-${MAMBA_ARCH}.sh"
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RUN chmod +x ~/mambaforge.sh && \
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bash ~/mambaforge.sh -b -p /opt/conda && \
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rm ~/mambaforge.sh
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# Install pytorch
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# On arm64 we exit with an error code
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RUN case ${TARGETPLATFORM} in \
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"linux/arm64") exit 1 ;; \
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*) /opt/conda/bin/conda update -y conda && \
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/opt/conda/bin/conda install -c "${INSTALL_CHANNEL}" -c "${CUDA_CHANNEL}" -y "python=${PYTHON_VERSION}" "pytorch=$PYTORCH_VERSION" "pytorch-cuda=$(echo $CUDA_VERSION | cut -d'.' -f 1-2)" ;; \
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esac && \
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/opt/conda/bin/conda clean -ya
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# CUDA kernels builder image
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FROM pytorch-install AS kernel-builder
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ARG MAX_JOBS=8
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ENV TORCH_CUDA_ARCH_LIST="8.0;8.6;9.0+PTX"
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RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
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ninja-build cmake \
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&& rm -rf /var/lib/apt/lists/*
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# Build Flash Attention CUDA kernels
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FROM kernel-builder AS flash-att-builder
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WORKDIR /usr/src
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COPY server/Makefile-flash-att Makefile
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# Build specific version of flash attention
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RUN make build-flash-attention
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# Build Flash Attention v2 CUDA kernels
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FROM kernel-builder AS flash-att-v2-builder
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WORKDIR /usr/src
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COPY server/Makefile-flash-att-v2 Makefile
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# Build specific version of flash attention v2
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RUN make build-flash-attention-v2-cuda
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# Build Transformers exllama kernels
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FROM kernel-builder AS exllama-kernels-builder
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WORKDIR /usr/src
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COPY server/exllama_kernels/ .
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RUN python setup.py build
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# Build Transformers exllama kernels
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FROM kernel-builder AS exllamav2-kernels-builder
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WORKDIR /usr/src
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COPY server/Makefile-exllamav2/ Makefile
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# Build specific version of transformers
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RUN make build-exllamav2
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# Build Transformers awq kernels
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FROM kernel-builder AS awq-kernels-builder
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WORKDIR /usr/src
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COPY server/Makefile-awq Makefile
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# Build specific version of transformers
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RUN make build-awq
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# Build eetq kernels
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FROM kernel-builder AS eetq-kernels-builder
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WORKDIR /usr/src
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COPY server/Makefile-eetq Makefile
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# Build specific version of transformers
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RUN make build-eetq
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# Build Lorax Punica kernels
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FROM kernel-builder AS lorax-punica-builder
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WORKDIR /usr/src
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COPY server/Makefile-lorax-punica Makefile
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# Build specific version of transformers
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RUN TORCH_CUDA_ARCH_LIST="8.0;8.6+PTX" make build-lorax-punica
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# Build Transformers CUDA kernels
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FROM kernel-builder AS custom-kernels-builder
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WORKDIR /usr/src
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COPY server/custom_kernels/ .
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# Build specific version of transformers
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RUN python setup.py build
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# Build FBGEMM CUDA kernels
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FROM kernel-builder AS fbgemm-builder
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WORKDIR /usr/src
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COPY server/Makefile-fbgemm Makefile
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RUN make build-fbgemm
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# Build vllm CUDA kernels
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FROM kernel-builder AS vllm-builder
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WORKDIR /usr/src
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ENV TORCH_CUDA_ARCH_LIST="7.0 7.5 8.0 8.6 8.9 9.0+PTX"
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COPY server/Makefile-vllm Makefile
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# Build specific version of vllm
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RUN make build-vllm-cuda
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# Build mamba kernels
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FROM kernel-builder AS mamba-builder
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WORKDIR /usr/src
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COPY server/Makefile-selective-scan Makefile
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RUN make build-all
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# Build flashinfer
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FROM kernel-builder AS flashinfer-builder
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WORKDIR /usr/src
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COPY server/Makefile-flashinfer Makefile
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RUN make install-flashinfer
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# Text Generation Inference base image
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FROM nvidia/cuda:12.1.0-base-ubuntu22.04 AS base
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# Conda env
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ENV PATH=/opt/conda/bin:$PATH \
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CONDA_PREFIX=/opt/conda
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# Text Generation Inference base env
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ENV HF_HOME=/data \
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HF_HUB_ENABLE_HF_TRANSFER=1 \
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PORT=80
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WORKDIR /usr/src
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RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
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libssl-dev \
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ca-certificates \
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make \
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curl \
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git \
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&& rm -rf /var/lib/apt/lists/*
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# Copy conda with PyTorch installed
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COPY --from=pytorch-install /opt/conda /opt/conda
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# Copy build artifacts from flash attention builder
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COPY --from=flash-att-builder /usr/src/flash-attention/build/lib.linux-x86_64-cpython-311 /opt/conda/lib/python3.11/site-packages
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COPY --from=flash-att-builder /usr/src/flash-attention/csrc/layer_norm/build/lib.linux-x86_64-cpython-311 /opt/conda/lib/python3.11/site-packages
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COPY --from=flash-att-builder /usr/src/flash-attention/csrc/rotary/build/lib.linux-x86_64-cpython-311 /opt/conda/lib/python3.11/site-packages
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# Copy build artifacts from flash attention v2 builder
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COPY --from=flash-att-v2-builder /opt/conda/lib/python3.11/site-packages/flash_attn_2_cuda.cpython-311-x86_64-linux-gnu.so /opt/conda/lib/python3.11/site-packages
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# Copy build artifacts from custom kernels builder
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COPY --from=custom-kernels-builder /usr/src/build/lib.linux-x86_64-cpython-311 /opt/conda/lib/python3.11/site-packages
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# Copy build artifacts from exllama kernels builder
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COPY --from=exllama-kernels-builder /usr/src/build/lib.linux-x86_64-cpython-311 /opt/conda/lib/python3.11/site-packages
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# Copy build artifacts from exllamav2 kernels builder
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COPY --from=exllamav2-kernels-builder /usr/src/exllamav2/build/lib.linux-x86_64-cpython-311 /opt/conda/lib/python3.11/site-packages
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# Copy build artifacts from awq kernels builder
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COPY --from=awq-kernels-builder /usr/src/llm-awq/awq/kernels/build/lib.linux-x86_64-cpython-311 /opt/conda/lib/python3.11/site-packages
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# Copy build artifacts from eetq kernels builder
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COPY --from=eetq-kernels-builder /usr/src/eetq/build/lib.linux-x86_64-cpython-311 /opt/conda/lib/python3.11/site-packages
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# Copy build artifacts from lorax punica kernels builder
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COPY --from=lorax-punica-builder /usr/src/lorax-punica/server/punica_kernels/build/lib.linux-x86_64-cpython-311 /opt/conda/lib/python3.11/site-packages
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# Copy build artifacts from fbgemm builder
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COPY --from=fbgemm-builder /usr/src/fbgemm/fbgemm_gpu/_skbuild/linux-x86_64-3.11/cmake-install /opt/conda/lib/python3.11/site-packages
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# Copy build artifacts from vllm builder
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COPY --from=vllm-builder /usr/src/vllm/build/lib.linux-x86_64-cpython-311 /opt/conda/lib/python3.11/site-packages
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# Copy build artifacts from mamba builder
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COPY --from=mamba-builder /usr/src/mamba/build/lib.linux-x86_64-cpython-311/ /opt/conda/lib/python3.11/site-packages
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COPY --from=mamba-builder /usr/src/causal-conv1d/build/lib.linux-x86_64-cpython-311/ /opt/conda/lib/python3.11/site-packages
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COPY --from=flashinfer-builder /opt/conda/lib/python3.11/site-packages/flashinfer/ /opt/conda/lib/python3.11/site-packages/flashinfer/
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# Install flash-attention dependencies
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RUN pip install einops --no-cache-dir
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# Install server
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COPY proto proto
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COPY server server
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COPY server/Makefile server/Makefile
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RUN cd server && \
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make gen-server && \
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pip install -r requirements_cuda.txt && \
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pip install ".[bnb, accelerate, marlin, quantize, peft, outlines]" --no-cache-dir && \
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pip install nvidia-nccl-cu12==2.22.3
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ENV LD_PRELOAD=/opt/conda/lib/python3.11/site-packages/nvidia/nccl/lib/libnccl.so.2
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# Required to find libpython within the rust binaries
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ENV LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/opt/conda/lib/"
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# This is needed because exl2 tries to load flash-attn
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# And fails with our builds.
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ENV EXLLAMA_NO_FLASH_ATTN=1
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# Deps before the binaries
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# The binaries change on every build given we burn the SHA into them
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# The deps change less often.
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RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
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build-essential \
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g++ \
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&& rm -rf /var/lib/apt/lists/*
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# Install benchmarker
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COPY --from=builder /usr/src/target/release-opt/text-generation-benchmark /usr/local/bin/text-generation-benchmark
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# Install router
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COPY --from=builder /usr/src/target/release-opt/text-generation-router /usr/local/bin/text-generation-router
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# Install launcher
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COPY --from=builder /usr/src/target/release-opt/text-generation-launcher /usr/local/bin/text-generation-launcher
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# AWS Sagemaker compatible image
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FROM base AS sagemaker
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COPY sagemaker-entrypoint.sh entrypoint.sh
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RUN chmod +x entrypoint.sh
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ENTRYPOINT ["./entrypoint.sh"]
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# Final image
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FROM base
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COPY ./tgi-entrypoint.sh /tgi-entrypoint.sh
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RUN chmod +x /tgi-entrypoint.sh
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ENTRYPOINT ["/tgi-entrypoint.sh"]
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# CMD ["--json-output"]
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