.. _install-from-source:

Install from Source
===================
This page gives instructions on how to build and install the tvm package from
scratch on various systems. It consists of two steps:

1. First build the shared library from the C++ codes (`libtvm.so` for linux/osx and `libtvm.dll` for windows).
2. Setup for the language packages (e.g. Python Package).

To get started, clone tvm repo from github. It is important to clone the submodules along, with ``--recursive`` option.

.. code:: bash

    git clone --recursive https://github.com/dmlc/tvm

For windows users who use github tools, you can open the git shell, and type the following command.

.. code:: bash

   git submodule init
   git submodule update


Build the Shared Library
------------------------

Our goal is to build the shared libraries:

- On Linux the target library are `libtvm.so, libtvm_topi.so`
- On OSX the target library are `libtvm.dylib, libtvm_topi.dylib`
- On Windows the target library are `libtvm.dll, libtvm_topi.dll`


.. code:: bash

    sudo apt-get update
    sudo apt-get install -y python python-dev python-setuptools gcc libtinfo-dev zlib1g-dev

The minimal building requirements are

- A recent c++ compiler supporting C++ 11 (g++-4.8 or higher)
- CMake 3.5 or higher
- We highly recommend to build with LLVM to enable all the features.
- It is possible to build TVM without the LLVM dependency if we only want to use CUDA/OpenCL
- If we want to use the NNVM compiler, then LLVM is required

We use cmake to build the library.
The configuration of tvm can be modified by `config.cmake`.


- First, check the cmake in your system, you do not have cmake
  you can obtain the latest version from `official website <https://cmake.org/download/>`_
- First create a build directory, copy the ``cmake/config.cmake`` to the directory.

  .. code:: bash

      mkdir build
      cp cmake/config.cmake build

- Edit ``build/config.cmake`` to customize the compilation options

  - On macOS, for some versions of XCode, you need to add ``-lc++abi`` in the LDFLAGS or you'll get link errors.
  - Change ``set(USE_CUDA OFF)`` to ``set(USE_CUDA ON)`` to enable CUDA backend. So do other backends and libraries
    (OpenCL, RCOM, METAL, VULKAN, ...).

- TVM optionally depends on LLVM. LLVM is required for CPU codegen that needs LLVM.

  - LLVM 4.0 or higher is needed for build with LLVM. Note that verison of LLVM from default apt may lower than 4.0.
  - Since LLVM takes long time to build from source, you can download pre-built version of LLVM from
    `LLVM Download Page <http://releases.llvm.org/download.html>`_.


    - Unzip to a certain location, modify ``build/config.cmake`` to add ``set(USE_LLVM /path/to/your/llvm/bin/llvm-config)``
    - You can also directly set ``set(USE_LLVM ON)`` and let cmake search for a usable version of LLVM.

  - You can also use `LLVM Nightly Ubuntu Build <https://apt.llvm.org/>`_

    - Note that apt-package append ``llvm-config`` with version number.
      For example, set ``set(LLVM_CONFIG llvm-config-4.0)`` if you installed 4.0 package

- We can then build tvm and related libraries.

  .. code:: bash

      cd build
      cmake ..
      make -j4

If everything goes well, we can go to :ref:`python-package-installation`

Building on Windows
~~~~~~~~~~~~~~~~~~~

TVM support build via MSVC using cmake. The minimum required VS version is **Visual Studio Community 2015 Update 3**.
In order to generate the VS solution file using cmake,
make sure you have a recent version of cmake added to your path and then from the tvm directory:

.. code:: bash

  mkdir build
  cd build
  cmake -G "Visual Studio 14 2015 Win64" -DCMAKE_BUILD_TYPE=Release -DCMAKE_CONFIGURATION_TYPES="Release" ..

This will generate the VS project using the MSVC 14 64 bit generator.
Open the .sln file in the build directory and build with Visual Studio.
In order to build with LLVM in windows, you will need to build LLVM from source.
You need to run build the nnvm by running the same script under the nnvm folder.

Building ROCm support
~~~~~~~~~~~~~~~~~~~~~

Currently, ROCm is supported only on linux, so all the instructions are written with linux in mind.

- Set ``set(USE_ROCM ON)``, set ROCM_PATH to the correct path.
- You need to first install HIP runtime from ROCm. Make sure the installation system has ROCm installed in it.
- Install latest stable version of LLVM (v6.0.1), and LLD, make sure ``ld.lld`` is available via command line.

.. _python-package-installation:

Python Package Installation
---------------------------

TVM package
~~~~~~~~~~~

The python package is located at `tvm/python`
There are two ways to install the package:

Method 1
   This method is **recommended for developers** who may change the codes.

   Set the environment variable `PYTHONPATH` to tell python where to find
   the library. For example, assume we cloned `tvm` on the home directory
   `~`. then we can added the following line in `~/.bashrc`.
   The changes will be immediately reflected once you pull the code and rebuild the project (no need to call ``setup`` again)

   .. code:: bash

       export TVM_HOME=/path/to/tvm
       export PYTHONPATH=$TVM_HOME/python:$TVM_HOME/topi/python:$TVM_HOME/nnvm/python:${PYTHONPATH}


Method 2
   Install tvm python bindings by `setup.py`:

   .. code:: bash

       # install tvm package for the current user
       # NOTE: if you installed python via homebrew, --user is not needed during installaiton
       #       it will be automatically installed to your user directory.
       #       providing --user flag may trigger error during installation in such case.
       export MACOSX_DEPLOYMENT_TARGET=10.9  # This is required for mac to avoid symbol conflicts with libstdc++
       cd python; python setup.py install --user; cd ..
       cd topi/python; python setup.py install --user; cd ../..
       cd nnvm/python; python setup.py install --user; cd ../..


Python dependencies
~~~~~~~~~~~~~~~~~~~
   * Necessary dependencies:

   .. code:: bash

       pip install --user numpy decorator

   * If you want to use RPC Tracker

   .. code:: bash

       pip install --user tornado

   * If you want to use auto-tuning module

   .. code:: bash

       pip install --user tornado psutil xgboost


Install Contrib Libraries
-------------------------

.. toctree::
   :maxdepth: 1

   nnpack
