Install TVM and NNVM from source

In this guide, we will walk you through the process of installing TVM and NNVM compiler from source along with all its dependencies such as HalideIR, DMLC-CORE, DLPACK and COMPILER-RT. Once installed, you can enjoy compiling models in any frameworks on any backend of your choice.

Installation

Step 1: Clone the source

Clone the source code of TVM using the following command:

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

Once done, move to the cloned repository using the following command:

cd tvm

Step 2: Prepare your build settings

Update your system and install the dependencies:

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

mkdir build
cp cmake/config.cmake build

Edit build/config.cmake to change SET(USE_LLVM OFF) to SET(USE_LLVM ON).

If you want to use another backend like CUDA, then change SET(USE_CUDA OFF) to SET(USE_CUDA ON) and accordingly for other available backends.

vi build/config.cmake

Step 3: Install LLVM as a backend

For TVM, you need a backend like LLVM, CUDA, METAL and others. We will install LLVM as a backend:

sudo apt-get install clang-6.0 lldb-6.0 lld-6.0

Step 4: Build the shared libraries

cd build
cmake ..
make -j4

Step 5: Build dependent libraries

First, we need to build the Python libraries of TVM:

cd ..
cd python
python setup.py install --user
cd ..

Next, we need to build NNVM:

cd nnvm
python setup.py install --user
cd ..

Next, we need to build the dependent libraries like HalideIR:

cd 3rdparty
cd HalideIR
make -j4
cd ..
cd dmlc-core
make -j4
cd ..
cd dlpack
make -j4
cd ..
cd ..

Step 6: Install some other dependencies

pip install --user numpy decorator
pip install --user tornado psutil xgboost
pip install --user tornado

Congratulations, you have successfully installed TVM Stack

You can, now, move to using TVM and realizing its performance compared to other frameworks.