Dockerfile.trt_llm_backend

ARG BASE_IMAGE=nvcr.io/nvidia/tritonserver
ARG BASE_TAG=24.07-py3

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

RUN apt-get update && apt-get install -y --no-install-recommends rapidjson-dev python-is-python3 ccache git-lfs

COPY requirements.txt /tmp/
RUN pip3 install -r /tmp/requirements.txt --extra-index-url https://pypi.ngc.nvidia.com

# Remove previous TRT installation
# We didn't remove libnvinfer* here because tritonserver depends on the pre-installed libraries.
RUN apt-get remove --purge -y tensorrt*
RUN pip uninstall -y tensorrt

FROM base as dev

# Download & install internal TRT release
COPY tensorrt_llm/docker/common/install_tensorrt.sh /tmp/
RUN bash /tmp/install_tensorrt.sh && rm /tmp/install_tensorrt.sh
ENV LD_LIBRARY_PATH=/usr/local/tensorrt/lib:${LD_LIBRARY_PATH}
ENV TRT_ROOT=/usr/local/tensorrt

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

# CMake
COPY tensorrt_llm/docker/common/install_cmake.sh /tmp/
RUN bash /tmp/install_cmake.sh && rm /tmp/install_cmake.sh
ENV PATH="/usr/local/cmake/bin:${PATH}"

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

# Use "pypi" (default) for x86_64 arch and "src_non_cxx11_abi" for aarch64 arch
ARG TORCH_INSTALL_TYPE="pypi"
COPY tensorrt_llm/docker/common/install_pytorch.sh install_pytorch.sh
RUN bash ./install_pytorch.sh $TORCH_INSTALL_TYPE && rm install_pytorch.sh

FROM dev as trt_llm_builder

WORKDIR /app
COPY scripts scripts
COPY tensorrt_llm tensorrt_llm
RUN cd tensorrt_llm && python3 scripts/build_wheel.py --trt_root="${TRT_ROOT}" -i -c && cd ..

FROM trt_llm_builder as trt_llm_backend_builder

WORKDIR /app/
COPY inflight_batcher_llm inflight_batcher_llm
RUN cd inflight_batcher_llm && bash scripts/build.sh && cd ..

FROM trt_llm_backend_builder as final

# Install TensorRT-LLM
WORKDIR /app/
COPY --from=trt_llm_builder /app/tensorrt_llm/build /app/tensorrt_llm/build
RUN cd /app/tensorrt_llm/build && pip3 install *.whl

# Install TensorRT-LLM backend
ENV LD_LIBRARY_PATH=/opt/tritonserver/backends/tensorrtllm:${LD_LIBRARY_PATH}