From f8219134eb4ef961b3d6c672db41490c0055a723 Mon Sep 17 00:00:00 2001 From: Hang Su Date: Mon, 15 Oct 2018 13:54:11 -0400 Subject: [PATCH] removes NCCL depencency --- Dockerfile | 4 +--- INSTALL.md | 23 +++++++++-------------- data/README.md | 3 ++- 3 files changed, 12 insertions(+), 18 deletions(-) diff --git a/Dockerfile b/Dockerfile index 89dbb7a..3ffcb4e 100644 --- a/Dockerfile +++ b/Dockerfile @@ -27,8 +27,6 @@ RUN apt-get update && apt-get install -y --no-install-recommends \ RUN wget --quiet https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda.sh && \ /bin/bash ~/miniconda.sh -b -p /opt/conda && rm ~/miniconda.sh -RUN git clone https://github.com/NVIDIA/nccl.git && cd nccl && make -j install && cd .. && rm -rf nccl - ENV CAFFE_ROOT=/opt/caffe WORKDIR $CAFFE_ROOT @@ -48,7 +46,7 @@ RUN git clone -b ${CLONE_TAG} --depth 1 https://github.com/BVLC/caffe.git . && \ rm -rf caffe-patch RUN /bin/bash -c "source /opt/conda/bin/activate caffe && mkdir build && cd build && \ - cmake -DUSE_CUDNN=1 -DUSE_NCCL=1 -Dpython_version=3 .. && \ + cmake -DUSE_CUDNN=1 -Dpython_version=3 .. && \ make -j$(nproc)" WORKDIR $CAFFE_ROOT/python diff --git a/INSTALL.md b/INSTALL.md index 0fc50c9..d706d18 100644 --- a/INSTALL.md +++ b/INSTALL.md @@ -3,7 +3,7 @@ Step-by-step installation instructions for Ubuntu 16.04. * Make sure CUDA and cuDNN are installed - We use CUDA 8 and cuDNN 6. But Caffe typically supports a wide range of CUDA/cuDNN versions. + We tested on CUDA8/cuDNN6 and CUDA9/cuDNN7. But Caffe typically supports a wide range of CUDA/cuDNN versions. * Install system-wide dependencies ```bash @@ -30,15 +30,6 @@ Step-by-step installation instructions for Ubuntu 16.04. protobuf-compiler ``` -* Install NCCL - ```bash - git clone https://github.com/NVIDIA/nccl.git - cd nccl - sudo make -j install - cd .. - sudo rm -rf nccl - ``` - * Install conda and additional packages ```bash wget --quiet https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh @@ -62,7 +53,7 @@ Step-by-step installation instructions for Ubuntu 16.04. rm -rf caffe-patch source activate caffe mkdir build && cd build - cmake -DUSE_CUDNN=1 -DUSE_NCCL=1 -Dpython_version=3 .. + cmake -DUSE_CUDNN=1 -Dpython_version=3 .. make -j$(nproc) cd $CAFFE_ROOT/python sed -i -e "s/python-dateutil>=1.4,<2/python-dateutil>=2.0/g" requirements.txt @@ -73,14 +64,18 @@ Step-by-step installation instructions for Ubuntu 16.04. export PYCAFFE_ROOT=$(pwd)/python export PYTHONPATH=\$PYCAFFE_ROOT:\$PYTHONPATH export PATH=\$CAFFE_ROOT/build/tools:\$PYCAFFE_ROOT:\$PATH - " >> ~/.bashrc // this puts path in your .bashrc file -- it will take effect at next login + " >> ~/.bashrc # this puts path in your .bashrc file + source ~/.bashrc sudo /bin/bash -c 'echo "$(pwd)/build/lib" >> /etc/ld.so.conf.d/caffe.conf' sudo ldconfig ``` * Ready to use! ```bash - # enter conda environment - # you will need to use a new terminal for the first time + # enter conda environment if you are not already in one source activate caffe ``` + +Note that for multi-GPU usage (not used or tested in our experiments and demos) you will also need NCCL: +* Before installing Caffe, install NCCL following [official instructions](https://github.com/NVIDIA/nccl). +* Add `-DUSE_NCCL=1` flag for cmake. diff --git a/data/README.md b/data/README.md index b242080..29aa12e 100644 --- a/data/README.md +++ b/data/README.md @@ -2,7 +2,8 @@ ### Ruemonge428 1. Request data access from the [VarCity 3D Semantic Segmentation Challenge](https://varcity.ethz.ch/3dchallenge/) website. -2. Download and place the folder `ruemonge428` under `data/`. For the 3D segmentation task, make sure these 3 files are present: +2. Download and place the folder [ruemonge428](https://bitbucket.org/hayko/varcity3dchallenge/src/master/data/ruemonge428/) +under `data/`. For the 3D segmentation task, make sure these 3 files are present: * `pcl.ply` * `pcl_gt_train.ply` * `pcl_gt_test.ply`