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Merge pull request #43 from facebookresearch/update-docs-template
Update docs install instructions, docker images and github issue template
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‎.github/ISSUE_TEMPLATE.md‎

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@@ -15,6 +15,9 @@ When submitting a bug report, please include the following information (where re
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- Docker image (if using docker):
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- GCC/GXX version (if compiling from source):
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- LLVM/Tapir git hash used (if compiling from source):
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To get the hash, run: `$HOME/clang+llvm-tapir5.0/bin/clang --version`
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- Commit hash of our repo and submodules (if compiling from source):
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In addition, including the following information will also be very helpful for us to diagnose the problem:

‎docs/source/installation_conda.rst‎

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@@ -74,10 +74,11 @@ Now, clone the repo, build and install LLVM+Tapir:
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$ git clone --recursive https://github.com/wsmoses/Tapir-LLVM llvm
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$ mkdir -p ${LLVM_SOURCES}/llvm_build && cd ${LLVM_SOURCES}/llvm_build
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$ ${CMAKE_VERSION} -DCMAKE_INSTALL_PREFIX=${CLANG_PREFIX} -DLLVM_TARGETS_TO_BUILD=X86 -DCOMPILER_RT_BUILD_CILKTOOLS=OFF -DLLVM_ENABLE_CXX1Y=ON -DLLVM_ENABLE_TERMINFO=OFF -DLLVM_BUILD_TESTS=OFF -DLLVM_ENABLE_ASSERTIONS=ON -DCMAKE_BUILD_TYPE=Release -DLLVM_BUILD_LLVM_DYLIB=ON -DLLVM_ENABLE_RTTI=ON ../llvm/
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$ ${CMAKE_VERSION} -DLLVM_ENABLE_OCAMLDOC=OFF -DLLVM_INSTALL_OCAMLDOC_HTML_DIR=/tmp -DLLVM_OCAML_INSTALL_PATH=/tmp -DCMAKE_INSTALL_PREFIX=${CLANG_PREFIX} -DLLVM_TARGETS_TO_BUILD=X86 -DCOMPILER_RT_BUILD_CILKTOOLS=OFF -DLLVM_ENABLE_CXX1Y=ON -DLLVM_ENABLE_TERMINFO=OFF -DLLVM_BUILD_TESTS=OFF -DLLVM_ENABLE_ASSERTIONS=ON -DCMAKE_BUILD_TYPE=Release -DLLVM_BUILD_LLVM_DYLIB=ON -DLLVM_ENABLE_RTTI=ON ../llvm/
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$ make -j $CORES -s && make install -j $CORES -s
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$ cd $HOME && rm -rf $LLVM_SOURCES
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Step 4: Install Anaconda3
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^^^^^^^^^^^^^^^^^^^^^^^^^^
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In order to contribute to TC python/C++ API, you need to install TC from source. For this,
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$ CUDNN_TAR_FILE="cudnn-8.0-linux-x64-v6.0.tgz"
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$ wget http://developer.download.nvidia.com/compute/redist/cudnn/v6.0/${CUDNN_TAR_FILE}
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$ tar -xzvf ${CUDNN_TAR_FILE}
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$ sudo cp -P cuda/include/cudnn.h /usr/local/cuda/include
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$ sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda/lib64/
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$ sudo chmod a+r /usr/local/cuda/lib64/libcudnn*
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$ cp -P cuda/include/cudnn.h /usr/local/cuda/include
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$ cp -P cuda/lib64/libcudnn* /usr/local/cuda/lib64/
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$ chmod a+r /usr/local/cuda/lib64/libcudnn*
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.. note::
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Please use :code:`sudo` to run the command that might fail with permission issues. Otherwise, run
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the commands as is.
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Set environment variables:
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$ mkdir -p /tmp/proto-install && cd /tmp/proto-install
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$ wget --quiet https://github.com/google/protobuf/archive/v3.4.0.zip -O proto.zip && unzip -qq proto.zip -d .
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$ cd protobuf-3.4.0 && ./autogen.sh && ./configure && make -j 8 && sudo make install && sudo ldconfig
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$ cd protobuf-3.4.0 && ./autogen.sh && ./configure && make -j 8 && make install && ldconfig
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.. note::
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Please use :code:`sudo` to run the command that might fail with permission issues. Otherwise, run
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the commands as is.
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Now check your proto version by running:
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‎docs/source/installation_conda_dep.rst‎

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@@ -65,6 +65,12 @@ to install the protobuf.
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$ wget --quiet https://github.com/google/protobuf/archive/v3.4.0.zip -O proto.zip && unzip -qq proto.zip -d .
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$ cd protobuf-3.4.0 && ./autogen.sh && ./configure && make -j 8 && make install && ldconfig
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.. note::
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Please use :code:`sudo` to run the command that might fail with permission issues. Otherwise, run
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the commands as is.
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Now check your proto version by running:
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.. code-block:: bash
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$ cp -P cuda/lib64/libcudnn* /usr/local/cuda/lib64/
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$ chmod a+r /usr/local/cuda/lib64/libcudnn*
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.. note::
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Please use :code:`sudo` to run the command that might fail with permission issues. Otherwise, run
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the commands as is.
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Set environment variables:
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.. code-block:: bash
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$ conda create -y --name tc-build-conda python=3.6
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$ source activate tc-build-conda
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$ conda install -y -c prigoyal tapir50 llvm isl-tc gflags glog
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$ conda install -y -c prigoyal llvm-tapir50 isl-tc gflags glog
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$ conda install -y -c pytorch pytorch
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$ cd $HOME && git clone https://github.com/facebookresearch/TensorComprehensions.git --recursive
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$ cd TensorComprehensions

‎docs/source/installation_docker_image.rst‎

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@@ -19,7 +19,7 @@ The conda and non-conda images for each setup are below:
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.. code-block:: bash
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$ docker run -i -t tensorcomprehensions/linux-trusty-gcc4.8-tapir5.0-cuda8-cudnn6-py3-conda:x86
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$ docker run -i -t tensorcomprehensions/linux-trusty-gcc4.8-tapir5.0-cuda8-cudnn6-py3-conda:x86_1
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.. code-block:: bash
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$ docker run -i -t tensorcomprehensions/linux-trusty-gcc4.8-tapir5.0-cuda8-cudnn6-py3:x86
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$ docker run -i -t tensorcomprehensions/linux-trusty-gcc4.8-tapir5.0-cuda8-cudnn6-py3:x86_1
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Now, to install TC, follow :ref:`non_conda_install_tc`
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.. code-block:: bash
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$ docker run -i -t tensorcomprehensions/linux-xenial-gcc5-tapir5.0-cuda9-cudnn7-py3-conda:x86
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$ docker run -i -t tensorcomprehensions/linux-xenial-gcc5-tapir5.0-cuda9-cudnn7-py3-conda:x86_1
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We don't ship the conda packages for TC dependencies that are compatible with gcc5 yet, so you have to
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build them from source. To install TC, see instructions here: :ref:`conda_install_tc`
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.. code-block:: bash
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$ docker run -i -t tensorcomprehensions/linux-xenial-gcc5-tapir5.0-cuda9-cudnn7-py3:x86
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$ docker run -i -t tensorcomprehensions/linux-xenial-gcc5-tapir5.0-cuda9-cudnn7-py3:x86_1
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Now, to install TC, follow :ref:`non_conda_install_tc`
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.. code-block:: bash
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$ nvidia-docker run --rm -i -t tensorcomprehensions/trusty-gcc4.8-py3-conda-cuda:x86
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$ nvidia-docker run --rm -i -t tensorcomprehensions/trusty-gcc4.8-py3-conda-cuda:x86_1
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Now, follow the instructions below to build TC:
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‎docs/source/installation_non_conda.rst‎

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.. code-block:: bash
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$ apt-get update
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$ apt-get install -y libgoogle-glog-dev curl build-essential cmake git automake libgmp3-dev libtool ssh libyaml-dev realpath wget valgrind software-properties-common unzip
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$ apt-get install -y libgoogle-glog-dev curl build-essential cmake git automake libgmp3-dev libtool ssh libyaml-dev realpath wget valgrind software-properties-common unzip libz-dev
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You might additionally need to install :code:`cmake3` and :code:`libz-dev`, if these packages are not found by apt-get, you can proceed otherwise install them by running :code:`apt-get install libz-dev`
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You might additionally need to install :code:`cmake3`, if this package is not found by apt-get, you can proceed.
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Step 2: Setup gcc / g++
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$ git clone --recursive https://github.com/wsmoses/Tapir-LLVM llvm
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$ mkdir -p ${LLVM_SOURCES}/llvm_build && cd ${LLVM_SOURCES}/llvm_build
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$ ${CMAKE_VERSION} -DCMAKE_INSTALL_PREFIX=${CLANG_PREFIX} -DLLVM_TARGETS_TO_BUILD=X86 -DCOMPILER_RT_BUILD_CILKTOOLS=OFF -DLLVM_ENABLE_CXX1Y=ON -DLLVM_ENABLE_TERMINFO=OFF -DLLVM_BUILD_TESTS=OFF -DLLVM_ENABLE_ASSERTIONS=ON -DCMAKE_BUILD_TYPE=Release -DLLVM_BUILD_LLVM_DYLIB=ON -DLLVM_ENABLE_RTTI=ON ../llvm/
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$ ${CMAKE_VERSION} -DLLVM_ENABLE_OCAMLDOC=OFF -DLLVM_INSTALL_OCAMLDOC_HTML_DIR=/tmp -DLLVM_OCAML_INSTALL_PATH=/tmp -DCMAKE_INSTALL_PREFIX=${CLANG_PREFIX} -DLLVM_TARGETS_TO_BUILD=X86 -DCOMPILER_RT_BUILD_CILKTOOLS=OFF -DLLVM_ENABLE_CXX1Y=ON -DLLVM_ENABLE_TERMINFO=OFF -DLLVM_BUILD_TESTS=OFF -DLLVM_ENABLE_ASSERTIONS=ON -DCMAKE_BUILD_TYPE=Release -DLLVM_BUILD_LLVM_DYLIB=ON -DLLVM_ENABLE_RTTI=ON ../llvm/
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$ make -j $CORES -s && make install -j $CORES -s
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$ cd $HOME && rm -rf $LLVM_SOURCES
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Step 4: Get CUDA and CUDNN
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^^^^^^^^^^^^^^^^^^^^^^^^^^
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In order to build TC, you also need to have :code:`CUDA` and :code:`CUDNN`. If you already have it
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$ CUDNN_TAR_FILE="cudnn-8.0-linux-x64-v6.0.tgz"
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$ wget http://developer.download.nvidia.com/compute/redist/cudnn/v6.0/${CUDNN_TAR_FILE}
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$ tar -xzvf ${CUDNN_TAR_FILE}
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$ sudo cp -P cuda/include/cudnn.h /usr/local/cuda/include
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$ sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda/lib64/
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$ sudo chmod a+r /usr/local/cuda/lib64/libcudnn*
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$ cp -P cuda/include/cudnn.h /usr/local/cuda/include
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$ cp -P cuda/lib64/libcudnn* /usr/local/cuda/lib64/
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$ chmod a+r /usr/local/cuda/lib64/libcudnn*
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.. note::
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Please use :code:`sudo` to run the command that might fail with permission issues. Otherwise, run
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the commands as is.
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$ mkdir -p /tmp/proto-install && cd /tmp/proto-install
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$ wget --quiet https://github.com/google/protobuf/archive/v3.4.0.zip -O proto.zip && unzip -qq proto.zip -d .
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$ cd protobuf-3.4.0 && ./autogen.sh && ./configure && make -j 8 && sudo make install && sudo ldconfig
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$ cd protobuf-3.4.0 && ./autogen.sh && ./configure && make -j 8 && make install && ldconfig
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.. note::
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Now check your proto version by running:
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.. code-block:: bash
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$ sudo apt-get install -y python3-dev python3-pip python3-setuptools
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$ apt-get install -y python3-dev python3-pip python3-setuptools
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$ pip3 install --upgrade pip
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$ pip3 install numpy pyyaml
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