TensorRT-LLMs/docker/Dockerfile.multi

# Multi-stage Dockerfile
ARG BASE_IMAGE=nvcr.io/nvidia/pytorch
ARG TRITON_IMAGE=nvcr.io/nvidia/tritonserver
ARG BASE_TAG=25.04-py3
ARG TRITON_BASE_TAG=25.04-py3
ARG DEVEL_IMAGE=devel

FROM ${BASE_IMAGE}:${BASE_TAG} AS base

# Add NVIDIA EULA and AI Terms labels
LABEL com.nvidia.eula="https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-software-license-agreement/"
LABEL com.nvidia.ai-terms="https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/"

# https://www.gnu.org/software/bash/manual/html_node/Bash-Startup-Files.html
# The default values come from `nvcr.io/nvidia/pytorch`
ENV BASH_ENV=${BASH_ENV:-/etc/bash.bashrc}
ENV ENV=${ENV:-/etc/shinit_v2}
ARG GITHUB_MIRROR=""
ENV GITHUB_MIRROR=$GITHUB_MIRROR
RUN echo "Using GitHub mirror: $GITHUB_MIRROR"
SHELL ["/bin/bash", "-c"]

# Clean up the pip constraint file from the base NGC PyTorch image.
RUN [ -f /etc/pip/constraint.txt ] && : > /etc/pip/constraint.txt || true

FROM base AS devel

ARG PYTHON_VERSION="3.12.3"
RUN echo "Using Python version: $PYTHON_VERSION"
COPY docker/common/install_base.sh install_base.sh
RUN bash ./install_base.sh $PYTHON_VERSION && rm install_base.sh

COPY docker/common/install_cmake.sh install_cmake.sh
RUN bash ./install_cmake.sh && rm install_cmake.sh

COPY docker/common/install_ccache.sh install_ccache.sh
RUN bash ./install_ccache.sh && rm install_ccache.sh

# Only take effect when the base image is Rocky Linux 8 with old CUDA version.
COPY docker/common/install_cuda_toolkit.sh install_cuda_toolkit.sh
RUN bash ./install_cuda_toolkit.sh && rm install_cuda_toolkit.sh

# Download & install latest TRT release
ARG TRT_VER
ARG CUDA_VER
ARG CUDNN_VER
ARG NCCL_VER
ARG CUBLAS_VER
COPY docker/common/install_tensorrt.sh install_tensorrt.sh
RUN bash ./install_tensorrt.sh \
    --TRT_VER=${TRT_VER} \
    --CUDA_VER=${CUDA_VER} \
    --CUDNN_VER=${CUDNN_VER} \
    --NCCL_VER=${NCCL_VER} \
    --CUBLAS_VER=${CUBLAS_VER} && \
    rm install_tensorrt.sh

# Install latest Polygraphy
COPY docker/common/install_polygraphy.sh install_polygraphy.sh
RUN bash ./install_polygraphy.sh && rm install_polygraphy.sh

# Install mpi4py
COPY docker/common/install_mpi4py.sh install_mpi4py.sh
RUN bash ./install_mpi4py.sh && rm install_mpi4py.sh

# Install PyTorch
ARG TORCH_INSTALL_TYPE="skip"
COPY docker/common/install_pytorch.sh install_pytorch.sh
RUN bash ./install_pytorch.sh $TORCH_INSTALL_TYPE && rm install_pytorch.sh

# Install OpenCV with FFMPEG support
RUN pip3 uninstall -y opencv && rm -rf /usr/local/lib/python3*/dist-packages/cv2/
RUN pip3 install opencv-python-headless --force-reinstall --no-deps --no-cache-dir


FROM ${TRITON_IMAGE}:${TRITON_BASE_TAG} AS triton

FROM devel AS tritondevel

COPY --from=triton /opt/tritonserver/backends/python /opt/tritonserver/backends/python
COPY --from=triton /opt/tritonserver/lib /opt/tritonserver/lib
COPY --from=triton /opt/tritonserver/include /opt/tritonserver/include
COPY --from=triton /opt/tritonserver/bin /opt/tritonserver/bin
COPY --from=triton /opt/tritonserver/caches /opt/tritonserver/caches
COPY docker/common/install_triton.sh install_triton.sh
RUN bash ./install_triton.sh && rm install_triton.sh

# Install NIXL
COPY docker/common/install_nixl.sh install_nixl.sh
RUN bash ./install_nixl.sh && rm install_nixl.sh

# Install etcd
COPY docker/common/install_etcd.sh install_etcd.sh
RUN bash ./install_etcd.sh && rm install_etcd.sh


FROM ${DEVEL_IMAGE} AS wheel
WORKDIR /src/tensorrt_llm
COPY benchmarks benchmarks
COPY cpp cpp
COPY benchmarks benchmarks
COPY scripts scripts
COPY tensorrt_llm tensorrt_llm
COPY 3rdparty 3rdparty
COPY .gitmodules setup.py requirements.txt requirements-dev.txt ./

# Create cache directories for pip and ccache
RUN mkdir -p /root/.cache/pip /root/.cache/ccache
ENV CCACHE_DIR=/root/.cache/ccache
# Build the TRT-LLM wheel
ARG BUILD_WHEEL_ARGS="--clean --python_bindings --benchmarks"
RUN --mount=type=cache,target=/root/.cache/pip --mount=type=cache,target=/root/.cache/ccache \
    python3 scripts/build_wheel.py ${BUILD_WHEEL_ARGS}

FROM ${DEVEL_IMAGE} AS release

# Create a cache directory for pip
RUN mkdir -p /root/.cache/pip

WORKDIR /app/tensorrt_llm
COPY --from=wheel /src/tensorrt_llm/build/tensorrt_llm*.whl .
RUN --mount=type=cache,target=/root/.cache/pip \
    pip install tensorrt_llm*.whl && \
    rm tensorrt_llm*.whl && \
    pip cache purge

COPY README.md ./
COPY docs docs
COPY cpp/include include

RUN ln -sv $(python3 -c 'import site; print(f"{site.getsitepackages()[0]}/tensorrt_llm/bin")') bin && \
    test -f bin/executorWorker && \
    ln -sv $(python3 -c 'import site; print(f"{site.getsitepackages()[0]}/tensorrt_llm/libs")') lib && \
    test -f lib/libnvinfer_plugin_tensorrt_llm.so && \
    echo "/app/tensorrt_llm/lib" > /etc/ld.so.conf.d/tensorrt_llm.conf && \
    ldconfig && \
    ! ( ldd -v bin/executorWorker | grep tensorrt_llm | grep -q "not found" )

ARG SRC_DIR=/src/tensorrt_llm
COPY --from=wheel ${SRC_DIR}/benchmarks benchmarks
ARG CPP_BUILD_DIR=${SRC_DIR}/cpp/build
COPY --from=wheel \
     ${CPP_BUILD_DIR}/benchmarks/bertBenchmark \
     ${CPP_BUILD_DIR}/benchmarks/gptManagerBenchmark \
     ${CPP_BUILD_DIR}/benchmarks/gptSessionBenchmark \
     ${CPP_BUILD_DIR}/benchmarks/disaggServerBenchmark \
     benchmarks/cpp/

COPY examples examples
RUN chmod -R a+w examples && \
    rm -v \
      benchmarks/cpp/bertBenchmark.cpp \
      benchmarks/cpp/gptManagerBenchmark.cpp \
      benchmarks/cpp/gptSessionBenchmark.cpp \
      benchmarks/cpp/disaggServerBenchmark.cpp \
      benchmarks/cpp/CMakeLists.txt && \
    rm -rf /root/.cache/pip

ARG GIT_COMMIT
ARG TRT_LLM_VER
ENV TRT_LLM_GIT_COMMIT=${GIT_COMMIT} \
    TRT_LLM_VERSION=${TRT_LLM_VER}