# Rust builder FROM lukemathwalker/cargo-chef:latest-rust-1.79 AS chef WORKDIR /usr/src ARG CARGO_REGISTRIES_CRATES_IO_PROTOCOL=sparse FROM chef AS planner COPY Cargo.lock Cargo.lock COPY Cargo.toml Cargo.toml COPY rust-toolchain.toml rust-toolchain.toml COPY proto proto COPY benchmark benchmark COPY router router COPY launcher launcher RUN cargo chef prepare --recipe-path recipe.json FROM chef AS builder RUN PROTOC_ZIP=protoc-21.12-linux-x86_64.zip && \ curl -OL https://github.com/protocolbuffers/protobuf/releases/download/v21.12/$PROTOC_ZIP && \ unzip -o $PROTOC_ZIP -d /usr/local bin/protoc && \ unzip -o $PROTOC_ZIP -d /usr/local 'include/*' && \ rm -f $PROTOC_ZIP COPY --from=planner /usr/src/recipe.json recipe.json RUN cargo chef cook --profile release-opt --recipe-path recipe.json ARG GIT_SHA ARG DOCKER_LABEL COPY Cargo.toml Cargo.toml COPY rust-toolchain.toml rust-toolchain.toml COPY proto proto COPY benchmark benchmark COPY router router COPY launcher launcher RUN cargo build --profile release-opt # Python builder # Adapted from: https://github.com/pytorch/pytorch/blob/master/Dockerfile FROM nvidia/cuda:12.1.0-devel-ubuntu22.04 AS pytorch-install # NOTE: When updating PyTorch version, beware to remove `pip install nvidia-nccl-cu12==2.22.3` below in the Dockerfile. Context: https://github.com/huggingface/text-generation-inference/pull/2099 ARG PYTORCH_VERSION=2.3.0 ARG PYTHON_VERSION=3.10 # Keep in sync with `server/pyproject.toml ARG CUDA_VERSION=12.1 ARG MAMBA_VERSION=24.3.0-0 ARG CUDA_CHANNEL=nvidia ARG INSTALL_CHANNEL=pytorch # Automatically set by buildx ARG TARGETPLATFORM ENV PATH /opt/conda/bin:$PATH RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \ build-essential \ ca-certificates \ ccache \ curl \ git && \ rm -rf /var/lib/apt/lists/* # Install conda # translating Docker's TARGETPLATFORM into mamba arches RUN case ${TARGETPLATFORM} in \ "linux/arm64") MAMBA_ARCH=aarch64 ;; \ *) MAMBA_ARCH=x86_64 ;; \ esac && \ curl -fsSL -v -o ~/mambaforge.sh -O "https://github.com/conda-forge/miniforge/releases/download/${MAMBA_VERSION}/Mambaforge-${MAMBA_VERSION}-Linux-${MAMBA_ARCH}.sh" RUN chmod +x ~/mambaforge.sh && \ bash ~/mambaforge.sh -b -p /opt/conda && \ rm ~/mambaforge.sh # Install pytorch # On arm64 we exit with an error code RUN case ${TARGETPLATFORM} in \ "linux/arm64") exit 1 ;; \ *) /opt/conda/bin/conda update -y conda && \ /opt/conda/bin/conda install -c "${INSTALL_CHANNEL}" -c "${CUDA_CHANNEL}" -y "python=${PYTHON_VERSION}" "pytorch=$PYTORCH_VERSION" "pytorch-cuda=$(echo $CUDA_VERSION | cut -d'.' -f 1-2)" ;; \ esac && \ /opt/conda/bin/conda clean -ya # CUDA kernels builder image FROM pytorch-install AS kernel-builder ARG MAX_JOBS=8 RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \ ninja-build cmake \ && rm -rf /var/lib/apt/lists/* # Build Flash Attention CUDA kernels FROM kernel-builder AS flash-att-builder WORKDIR /usr/src COPY server/Makefile-flash-att Makefile # Build specific version of flash attention RUN make build-flash-attention # Build Flash Attention v2 CUDA kernels FROM kernel-builder AS flash-att-v2-builder WORKDIR /usr/src COPY server/Makefile-flash-att-v2 Makefile # Build specific version of flash attention v2 RUN make build-flash-attention-v2-cuda # Build Transformers exllama kernels FROM kernel-builder AS exllama-kernels-builder WORKDIR /usr/src COPY server/exllama_kernels/ . RUN TORCH_CUDA_ARCH_LIST="8.0;8.6+PTX" python setup.py build # Build Transformers exllama kernels FROM kernel-builder AS exllamav2-kernels-builder WORKDIR /usr/src COPY server/exllamav2_kernels/ . # Build specific version of transformers RUN TORCH_CUDA_ARCH_LIST="8.0;8.6+PTX" python setup.py build # Build Transformers awq kernels FROM kernel-builder AS awq-kernels-builder WORKDIR /usr/src COPY server/Makefile-awq Makefile # Build specific version of transformers RUN TORCH_CUDA_ARCH_LIST="8.0;8.6+PTX" make build-awq # Build eetq kernels FROM kernel-builder AS eetq-kernels-builder WORKDIR /usr/src COPY server/Makefile-eetq Makefile # Build specific version of transformers RUN TORCH_CUDA_ARCH_LIST="8.0;8.6+PTX" make build-eetq # Build marlin kernels FROM kernel-builder AS marlin-kernels-builder WORKDIR /usr/src COPY server/marlin/ . # Build specific version of transformers RUN TORCH_CUDA_ARCH_LIST="8.0;8.6+PTX" python setup.py build # Build Lorax Punica kernels FROM kernel-builder AS lorax-punica-builder WORKDIR /usr/src COPY server/Makefile-lorax-punica Makefile # Build specific version of transformers RUN TORCH_CUDA_ARCH_LIST="8.0;8.6+PTX" make build-lorax-punica # Build Transformers CUDA kernels FROM kernel-builder AS custom-kernels-builder WORKDIR /usr/src COPY server/custom_kernels/ . # Build specific version of transformers RUN python setup.py build # Build FBGEMM CUDA kernels FROM kernel-builder AS fbgemm-builder WORKDIR /usr/src COPY server/Makefile-fbgemm Makefile COPY server/fbgemm_remove_unused.patch fbgemm_remove_unused.patch COPY server/fix_torch90a.sh fix_torch90a.sh RUN make build-fbgemm # Build vllm CUDA kernels FROM kernel-builder AS vllm-builder WORKDIR /usr/src ENV TORCH_CUDA_ARCH_LIST="7.0 7.5 8.0 8.6 8.9 9.0+PTX" COPY server/Makefile-vllm Makefile # Build specific version of vllm RUN make build-vllm-cuda # Build mamba kernels FROM kernel-builder AS mamba-builder WORKDIR /usr/src COPY server/Makefile-selective-scan Makefile RUN make build-all # Text Generation Inference base image FROM nvidia/cuda:12.1.0-base-ubuntu22.04 AS base # Conda env ENV PATH=/opt/conda/bin:$PATH \ CONDA_PREFIX=/opt/conda # Text Generation Inference base env ENV HUGGINGFACE_HUB_CACHE=/data \ HF_HUB_ENABLE_HF_TRANSFER=1 \ PORT=80 WORKDIR /usr/src RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \ libssl-dev \ ca-certificates \ make \ curl \ git \ && rm -rf /var/lib/apt/lists/* # Copy conda with PyTorch installed COPY --from=pytorch-install /opt/conda /opt/conda # Copy build artifacts from flash attention builder COPY --from=flash-att-builder /usr/src/flash-attention/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages COPY --from=flash-att-builder /usr/src/flash-attention/csrc/layer_norm/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages COPY --from=flash-att-builder /usr/src/flash-attention/csrc/rotary/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages # Copy build artifacts from flash attention v2 builder COPY --from=flash-att-v2-builder /opt/conda/lib/python3.10/site-packages/flash_attn_2_cuda.cpython-310-x86_64-linux-gnu.so /opt/conda/lib/python3.10/site-packages # Copy build artifacts from custom kernels builder COPY --from=custom-kernels-builder /usr/src/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages # Copy build artifacts from exllama kernels builder COPY --from=exllama-kernels-builder /usr/src/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages # Copy build artifacts from exllamav2 kernels builder COPY --from=exllamav2-kernels-builder /usr/src/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages # Copy build artifacts from awq kernels builder COPY --from=awq-kernels-builder /usr/src/llm-awq/awq/kernels/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages # Copy build artifacts from eetq kernels builder COPY --from=eetq-kernels-builder /usr/src/eetq/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages # Copy build artifacts from marlin kernels builder COPY --from=marlin-kernels-builder /usr/src/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages COPY --from=lorax-punica-builder /usr/src/lorax-punica/server/punica_kernels/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages # Copy build artifacts from fbgemm builder COPY --from=fbgemm-builder /usr/src/fbgemm/fbgemm_gpu/_skbuild/linux-x86_64-3.10/cmake-install /opt/conda/lib/python3.10/site-packages # Copy build artifacts from vllm builder COPY --from=vllm-builder /usr/src/vllm/build/lib.linux-x86_64-cpython-310 /opt/conda/lib/python3.10/site-packages # Copy build artifacts from mamba builder COPY --from=mamba-builder /usr/src/mamba/build/lib.linux-x86_64-cpython-310/ /opt/conda/lib/python3.10/site-packages COPY --from=mamba-builder /usr/src/causal-conv1d/build/lib.linux-x86_64-cpython-310/ /opt/conda/lib/python3.10/site-packages # Install flash-attention dependencies RUN pip install einops --no-cache-dir # Install server COPY proto proto COPY server server COPY server/Makefile server/Makefile RUN cd server && \ make gen-server && \ pip install -r requirements_cuda.txt && \ pip install ".[bnb, accelerate, quantize, peft, outlines]" --no-cache-dir && \ pip install nvidia-nccl-cu12==2.22.3 ENV LD_PRELOAD=/opt/conda/lib/python3.10/site-packages/nvidia/nccl/lib/libnccl.so.2 # Deps before the binaries # The binaries change on every build given we burn the SHA into them # The deps change less often. RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \ build-essential \ g++ \ && rm -rf /var/lib/apt/lists/* # Install benchmarker COPY --from=builder /usr/src/target/release-opt/text-generation-benchmark /usr/local/bin/text-generation-benchmark # Install router COPY --from=builder /usr/src/target/release-opt/text-generation-router /usr/local/bin/text-generation-router # Install launcher COPY --from=builder /usr/src/target/release-opt/text-generation-launcher /usr/local/bin/text-generation-launcher # AWS Sagemaker compatible image FROM base AS sagemaker COPY sagemaker-entrypoint.sh entrypoint.sh RUN chmod +x entrypoint.sh ENTRYPOINT ["./entrypoint.sh"] # Final image FROM base COPY ./tgi-entrypoint.sh /tgi-entrypoint.sh RUN chmod +x /tgi-entrypoint.sh ENTRYPOINT ["/tgi-entrypoint.sh"] # CMD ["--json-output"]