231 lines
7.5 KiB
Docker
231 lines
7.5 KiB
Docker
# Rust builder
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FROM lukemathwalker/cargo-chef:latest-rust-1.71 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.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 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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ARG GIT_SHA
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ARG DOCKER_LABEL
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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 $PROTOC_ZIP
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COPY --from=planner /usr/src/recipe.json recipe.json
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RUN cargo chef cook --release --recipe-path recipe.json
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COPY Cargo.toml Cargo.toml
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COPY rust-toolchain.toml rust-toolchain.toml
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COPY proto proto
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COPY benchmark benchmark
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COPY router router
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COPY launcher launcher
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RUN cargo build --release
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# Python builder
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# Adapted from: https://github.com/pytorch/pytorch/blob/master/Dockerfile
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FROM debian:bullseye-slim as pytorch-install
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ARG PYTORCH_VERSION=2.0.1
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ARG PYTHON_VERSION=3.9
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# Keep in sync with `server/pyproject.toml
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ARG CUDA_VERSION=11.8
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ARG MAMBA_VERSION=23.1.0-1
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ARG CUDA_CHANNEL=nvidia
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ARG INSTALL_CHANNEL=pytorch
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# Automatically set by buildx
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ARG TARGETPLATFORM
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ENV PATH /opt/conda/bin:$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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RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
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ninja-build \
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&& rm -rf /var/lib/apt/lists/*
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RUN /opt/conda/bin/conda install -c "nvidia/label/cuda-11.8.0" cuda==11.8 && \
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/opt/conda/bin/conda clean -ya
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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
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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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# Build specific version of transformers
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RUN TORCH_CUDA_ARCH_LIST="8.0;8.6+PTX" python setup.py build
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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 TORCH_CUDA_ARCH_LIST="8.0;8.6+PTX" 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 TORCH_CUDA_ARCH_LIST="8.0;8.6+PTX" make build-eetq
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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 vllm CUDA kernels
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FROM kernel-builder as vllm-builder
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WORKDIR /usr/src
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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
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# Text Generation Inference base image
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FROM nvidia/cuda:11.8.0-base-ubuntu20.04 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 HUGGINGFACE_HUB_CACHE=/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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&& 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-39 /opt/conda/lib/python3.9/site-packages
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COPY --from=flash-att-builder /usr/src/flash-attention/csrc/layer_norm/build/lib.linux-x86_64-cpython-39 /opt/conda/lib/python3.9/site-packages
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COPY --from=flash-att-builder /usr/src/flash-attention/csrc/rotary/build/lib.linux-x86_64-cpython-39 /opt/conda/lib/python3.9/site-packages
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# Copy build artifacts from flash attention v2 builder
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COPY --from=flash-att-v2-builder /usr/src/flash-attention-v2/build/lib.linux-x86_64-cpython-39 /opt/conda/lib/python3.9/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-39 /opt/conda/lib/python3.9/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-39 /opt/conda/lib/python3.9/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-39 /opt/conda/lib/python3.9/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-39 /opt/conda/lib/python3.9/site-packages
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# Copy builds artifacts from vllm builder
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COPY --from=vllm-builder /usr/src/vllm/build/lib.linux-x86_64-cpython-39 /opt/conda/lib/python3.9/site-packages
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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.txt && \
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pip install ".[bnb, accelerate, quantize]" --no-cache-dir
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# Install benchmarker
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COPY --from=builder /usr/src/target/release/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/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/text-generation-launcher /usr/local/bin/text-generation-launcher
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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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# AWS Sagemaker compatbile 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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ENTRYPOINT ["text-generation-launcher"]
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CMD ["--json-output"]
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