[Fix] Remove dockerfile (#69)

2021-09-10 17:58:07 +08:00 · 2021-09-10 17:58:07 +08:00 · 745c51f965
parent 667318c268
commit 745c51f965
3 changed files with 0 additions and 156 deletions
--- a/docker/Dockerfile
+++ b/docker/Dockerfile
@ -1,75 +0,0 @@
-# This is a dockerfile that can be directly used for mmlab deployment,
-# including onnxruntime stuff. But this will be deprivecated in the future and
-# should not be open to custmers!!!
-ARG OS_VERSION=18.04
-ARG PYTHON_VERSION=3.7.2
-ARG PYTORCH_VERSION="1.8.1"
-ARG CUDA_VERSION="11.1"
-ARG CUDNN_VERSION="8"
-
-FROM pytorch/pytorch:${PYTORCH_VERSION}-cuda${CUDA_VERSION}-cudnn${CUDNN_VERSION}-devel as torch
-RUN --mount=type=cache,id=apt-dev,target=/var/cache/apt \
-    apt-get update && apt-get install -y --no-install-recommends \
-        build-essential \
-        ca-certificates \
-        ccache \
-        cmake \
-        wget \
-        git \
-    && rm -rf /var/lib/apt/lists/*
-WORKDIR /workspace
-COPY TensorRT-7.2.3.4.Ubuntu-18.04.x86_64-gnu.cuda-11.1.cudnn8.1.tar.gz /workspace/TensorRT-7.2.3.4.Ubuntu-18.04.x86_64-gnu.cuda-11.1.cudnn8.1.tar.gz
-
-ENV TENSORRT_DIR=/workspace/TensorRT-7.2.3.4
-ENV ONNXRUNTIME_DIR=/workspace/onnxruntime-linux-x64-1.5.1
-ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$ONNXRUNTIME_DIR/lib:$TENSORRT_DIR/lib
-RUN conda install pytorch==1.6.0 torchvision==0.7.0 cudatoolkit=10.2 -c pytorch
-RUN tar -xvzf TensorRT-7.2.3.4.Ubuntu-18.04.x86_64-gnu.cuda-11.1.cudnn8.1.tar.gz \
-    && pip install $TENSORRT_DIR/python/tensorrt-7.2.3.4-cp38-none-linux_x86_64.whl \
-    && pip install $TENSORRT_DIR/onnx_graphsurgeon/onnx_graphsurgeon-0.2.6-py2.py3-none-any.whl \
-    && pip install $TENSORRT_DIR/graphsurgeon/graphsurgeon-0.4.5-py2.py3-none-any.whl \
-    && wget https://github.com/microsoft/onnxruntime/releases/download/v1.5.1/onnxruntime-linux-x64-1.5.1.tgz \
-    && tar -zxvf onnxruntime-linux-x64-1.5.1.tgz \
-    && rm -rf TensorRT-7.2.3.4.Ubuntu-18.04.x86_64-gnu.cuda-11.1.cudnn8.1.tar.gz onnxruntime-linux-x64-1.5.1.tgz \
-    && pip --no-cache-dir install onnxruntime==1.5.1 \
-    && git clone https://github.com/open-mmlab/mmcv/ /workspace/mmcv \
-    && cd mmcv \
-    && MMCV_WITH_OPS=1 MMCV_WITH_TRT=1 MMCV_WITH_ORT=1 pip install -e . \
-    && pip --no-cache-dir install onnx-simplifier==0.3.6 \
-    && pip --no-cache-dir install onnxruntime==1.6.0 onnx==1.9.0 pycocotools terminaltables
-
-#FROM ubuntu:${OS_VERSION} as official
-ARG PYTORCH_VERSION
-LABEL com.nvidia.volumes.needed="nvidia_driver"
-RUN --mount=type=cache,id=apt-final,target=/var/cache/apt \
-    apt-get update && apt-get install -y --no-install-recommends \
-        ca-certificates \
-        libjpeg-dev \
-        libpng-dev \
-        # MMDet Requirements
-        ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6 \
-        && rm -rf /var/lib/apt/lists/*
-
-
-WORKDIR /workspace
-ENV NVIDIA_VISIBLE_DEVICES all
-ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
-ENV LD_LIBRARY_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64
-ENV PYTORCH_VERSION ${PYTORCH_VERSION}
-ENV TENSORRT_DIR=/workspace/TensorRT-7.2.3.4
-ENV ONNXRUNTIME_DIR=/workspace/onnxruntime-linux-x64-1.5.1
-ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$ONNXRUNTIME_DIR/lib:$TENSORRT_DIR/lib
-ENV PATH /opt/conda/bin:$PATH
-
-ENV TORCH_CUDA_ARCH_LIST="6.0 6.1 7.0+PTX"
-ENV TORCH_NVCC_FLAGS="-Xfatbin -compress-all"
-ENV CMAKE_PREFIX_PATH="$(dirname $(which conda))/../"
-ENV FORCE_CUDA="1"
-
-RUN git clone https://github.com/open-mmlab/mmdetection \
-    && cd mmdetection \
-    && export ONNX_BACKEND=MMCVTensorRT \
-    && export PYTHONPATH=$PYTHONPATH:pwd \
-    && python tools/deployment/pytorch2onnx.py configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py https://download.openmmlab.com/mmdetection/v2.0/mask_rcnn/mask_rcnn_r50_fpn_1x_coco/mask_rcnn_r50_fpn_1x_coco_20200205-d4b0c5d6.pth --input-img demo/demo.jpg --test-img  demo/demo.jpg --dynamic-export
-#    && python tools/deployment/onnx2tensorrt.py configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py tmp.onnx --trt-file tmp.trt --verify --min-shape 300 300 --max-shape 1600 1600
-CMD /bin/bash
--- a/docker/DockerfileOptimized
+++ b/docker/DockerfileOptimized
@ -1,68 +0,0 @@
-# This is an optimized dockerfile but not for directly usage of developing when
-# it involves onnruntime stuff.
-
-ARG OS_VERSION=18.04
-ARG PYTHON_VERSION=3.7.2
-ARG PYTORCH_VERSION="1.8.1"
-ARG CUDA_VERSION="11.1"
-ARG CUDNN_VERSION="8"
-# TensorRT version fixed by downloaded .tar package
-
-FROM pytorch/pytorch:${PYTORCH_VERSION}-cuda${CUDA_VERSION}-cudnn${CUDNN_VERSION}-devel as torch
-ARG ONNXRUNTIME_VERSION=1.5.1
-ARG ONNX_VERSION=1.9.0
-ARG ONNX_SIMP_VERSION=0.3.6
-RUN --mount=type=cache,id=apt-dev,target=/var/cache/apt \
-    apt-get update && apt-get install -y --no-install-recommends \
-        build-essential \
-        ca-certificates \
-        ccache \
-        cmake \
-        wget \
-        git \
-    && rm -rf /var/lib/apt/lists/*
-WORKDIR /workspace
-COPY TensorRT-7.2.3.4.Ubuntu-18.04.x86_64-gnu.cuda-11.1.cudnn8.1.tar.gz /workspace/TensorRT-7.2.3.4.Ubuntu-18.04.x86_64-gnu.cuda-11.1.cudnn8.1.tar.gz
-ENV TENSORRT_DIR=/workspace/TensorRT-7.2.3.4
-ENV ONNXRUNTIME_DIR=/workspace/onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}
-ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$ONNXRUNTIME_DIR/lib:$TENSORRT_DIR/lib
-RUN tar -xvzf TensorRT-7.2.3.4.Ubuntu-18.04.x86_64-gnu.cuda-11.1.cudnn8.1.tar.gz \
-    && pip install $TENSORRT_DIR/python/tensorrt-7.2.3.4-cp38-none-linux_x86_64.whl \
-    && pip install $TENSORRT_DIR/onnx_graphsurgeon/onnx_graphsurgeon-0.2.6-py2.py3-none-any.whl \
-    && pip install $TENSORRT_DIR/graphsurgeon/graphsurgeon-0.4.5-py2.py3-none-any.whl \
-    && wget "https://github.com/microsoft/onnxruntime/releases/download/v${ONNXRUNTIME_VERSION}/onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}.tgz" \
-    && tar -zxvf onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}.tgz \
-    && rm -rf TensorRT-7.2.3.4.Ubuntu-18.04.x86_64-gnu.cuda-11.1.cudnn8.1.tar.gz onnxruntime-linux-x64-${ONNXRUNTIME_VERSION}.tgz \
-    && pip --no-cache-dir install onnxruntime==${ONNXRUNTIME_VERSION} \
-    && git clone https://github.com/open-mmlab/mmcv/ /workspace/mmcv \
-    && cd mmcv \
-    && MMCV_WITH_OPS=1 MMCV_WITH_TRT=1 MMCV_WITH_ORT=1 pip install -e . \
-    && pip --no-cache-dir install onnx-simplifier==${ONNX_SIMP_VERSION} onnx==${ONNX_VERSION} pycocotools terminaltables
-
-FROM ubuntu:${OS_VERSION} as official
-ARG PYTORCH_VERSION="1.8.1"
-RUN --mount=type=cache,id=apt-dev,target=/var/cache/apt \
-    apt-get update && apt-get install -y --no-install-recommends \
-        ca-certificates \
-        libjpeg-dev \
-        libpng-dev \
-        ccache \
-        cmake \
-        gcc \
-        git \
-        # MMDet Requirements
-        ffmpeg libsm6 libxext6 git ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6 \
-    && rm -rf /var/lib/apt/lists/*
-ENV PATH /opt/conda/bin:$PATH
-ENV NVIDIA_VISIBLE_DEVICES all
-ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
-ENV LD_LIBRARY_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64
-ENV PYTORCH_VERSION ${PYTORCH_VERSION}
-WORKDIR /workspace
-
-FROM official as final
-COPY --from=torch /workspace /workspace
-COPY --from=torch /opt/conda /opt/conda
-RUN /opt/conda/bin/conda clean -ya
-WORKDIR /workspace
-CMD /bin/bash
--- a/docker/README.md
+++ b/docker/README.md
@ -1,13 +0,0 @@
-## Use the container
-Place the Dockerfile and the [TensorRT-7.2.3.4.Ubuntu-18.04.x86_64-gnu.cuda-11.1.cudnn8.1.tar.gz](https://developer.nvidia.com/compute/machine-learning/tensorrt/secure/7.2.3/tars/TensorRT-7.2.3.4.Ubuntu-16.04.x86_64-gnu.cuda-11.1.cudnn8.1.tar.gz) package togather under a folder named docker.
-Run the following command to build the docker image:
-```
-sudo docker build docker/ -t mmdeploy
-```
-Then run the command bellow to play with the docker image:
-```
-sudo docker run --gpus all --shm-size=8g -it -p 8084:8084 mmdeploy
-```
-
-## Use the optimized container
-The optimized docker file is provided and it can be used in the future.