# AMD MIGraphX

AMD MIGraphX is AMD's graph inference engine, which accelerates machine learning model inference.
To use MIGraphX, you can install the binaries or build from source code. Refer to the following sections
for Ubuntu installation instructions (we'll provide instructions for other Linux distributions in the future).

```note
You must [install ROCm](https://rocm.docs.amd.com/en/latest/deploy/linux/quick_start.html) before
installing MIGraphX.
```

## Installing from binaries

Install binaries using:

```bash
sudo apt update && sudo apt install -y migraphx
```

Header files and libraries are installed under `/opt/rocm-<version>`, where `<version>` is the ROCm
version.

## Building from source

You have three options for building from source:

* [ROCm build tool](#use-the-rocm-build-tool-rbuild): Uses
  [rbuild](https://github.com/RadeonOpenCompute/rbuild) to install prerequisites, then you can build
  the libraries with a single command.

* [CMake](#use-cmake-to-build-migraphx): Uses a script to install prerequisites, then you can use
  CMake to build the source.

* [Docker](#use-docker): Builds a Docker image with all prerequisites installed, then you can build the
  MIGraphX sources inside a Docker container.

### Build prerequisites

The following is a list of prerequisites for building MIGraphX.

* [ROCm CMake modules](https://github.com/RadeonOpenCompute/rocm-cmake) **required**
* [MIOpen](https://github.com/ROCmSoftwarePlatform/MIOpen) for running on the GPU
* [rocBLAS](https://github.com/ROCmSoftwarePlatform/rocBLAS) for running on the GPU
* [HIP](https://github.com/ROCm-Developer-Tools/HIP) for running on the GPU
* [Protobuf](https://github.com/google/protobuf) for reading [onnx](https://github.com/onnx/onnx)
  files
* [Half](http://half.sourceforge.net/), an IEEE 754-based half-precision floating point library
* [pybind11](https://pybind11.readthedocs.io/en/stable/) for python bindings
* [JSON](https://github.com/nlohmann/json) for model serialization to json string format
* [MessagePack](https://msgpack.org/index.html) for model serialization to binary format
* [SQLite3](https://www.sqlite.org/index.html) to create database of kernels' tuning information or run queries on existing database

### Use the ROCm build tool [rbuild](https://github.com/RadeonOpenCompute/rbuild).

1. Install `rocm-cmake`, `pip3`, `rocblas`, and `miopen-hip`:

    ```bash
    sudo apt install -y rocm-cmake python3-pip rocblas miopen-hip
    ```

2. Install [rbuild](https://github.com/RadeonOpenCompute/rbuild) (sudo may be required):

    ```bash
    pip3 install https://github.com/RadeonOpenCompute/rbuild/archive/master.tar.gz
    ```

3. Build MIGraphX source code:

    ```bash
    rbuild build -d depend -B build
    ```

Once completed, all prerequisites are in the `depend` folder and MIGraphX is in the `build` directory.

```note
If you get an `rbuild: command not found` error, it's because `rbuild` is installed in `$HOME/.local/bin`,
which is not in `PATH`. You can either export PATH as `export PATH=$HOME/.local/bin:$PATH` to add
the folder to `PATH`, or add the option `--prefix /usr/local` in the pip3 command when installing `rbuild`.
```

### Use CMake to build MIGraphX

1. Install the prerequisites:

    ```bash
    rbuild prepare -d depend
    ```

    This puts all the prerequisites are in `depend` the folder. They can be used in the `cmake`
    configuration as `-DCMAKE_PREFIX_PATH=depend`.

    If you have sudo access, as an alternative to the `rbuild` command, you can install the prerequisites
    in the same way as a Dockerfile, by calling `./tools/install_prereqs.sh`.

    By default, all prerequisites are installed at the default location (`/usr/local`) and are accessible by all
    users. For the default location, `sudo` is required to run the script. You can also specify a different
    location using `./tools/install_prereqs.sh $custom_location`.

2. Go to the project folder and create a `build` directory:

    ```bash
    mkdir build
    cd build
    ```

3. Configure CMake. If the prerequisites are installed at the default location `/usr/local`, use:

    ```bash
    CXX=/opt/rocm/llvm/bin/clang++ cmake ..
    ```

    Otherwise, you need to set `-DCMAKE_PREFIX_PATH=$your_loc` to configure CMake.

4. Build MIGraphX source code:

    ```cpp
    make -j$(nproc)
    ```

    You can verify this using:

    ```cpp
    make -j$(nproc) check
    ```

5. Install MIGraphX libraries:

    ```cpp
    make install
    ```

### Use Docker

The easiest way to set up the development environment is to use Docker.

1. With the Dockerfile, build a Docker image:

    ```bash
        docker build -t migraphx .
    ```

2. Enter the development environment using `docker run`:

    ```bash
        docker run --device='/dev/kfd' --device='/dev/dri' -v=`pwd`:/code/AMDMIGraphX -w /code/AMDMIGraphX --group-add video -it migraphx
    ```

3. In the Docker container, all required prerequisites are already installed, so you can go to the folder
    `/code/AMDMIGraphX` and follow the steps (starting from 2) in the
    [Use CMake to build MIGraphX](#use-cmake-to-build-migraphx).

## Using the MIGraphX Python module

To use MIGraphX's Python module, you can set `PYTHONPATH` or use the `.deb` package:

* Setting `PYTHONPATH`:

    ```bash
    export PYTHONPATH=/opt/rocm/lib:$PYTHONPATH
    ```

* Creating the `deb` package:

    ```bash
    make package
    ```

    This provides the path for .deb package.

    To install:

    ```bash
    dpkg -i <path_to_deb_file>
    ```

## Calling MIGraphX APIs

To use MIGraphX's C/C++ API in your CMake project, you must set `CMAKE_PREFIX_PATH` to the
MIGraphX installation location and run:

```bash
find_package(migraphx)
target_link_libraries(myApp migraphx::c)
```

Where `myApp` is the CMake target in your project.

## Building for development

Using `rbuild`, you can install the dependencies for development with:

```bash
rbuild develop
```

This installs development dependencies in the `deps` directory and configures `cmake` to use those
dependencies in the `build` directory. You can change these directories by passing the `--deps-dir` and
`--build-dir` flags to the `rbuild` command:

```bash
rbuild develop --build-dir build_rocm_55 --deps-dir /home/user/deps_dir
```

## Building the documentation

HTML and PDF documentation can be built using:

`cmake --build . --config Release --target doc` **OR** `make doc`

This will build a local searchable web site inside the docs/html folder.

Documentation is built using [Doxygen](http://www.stack.nl/~dimitri/doxygen/download.html) and [rocm-docs-core](https://github.com/RadeonOpenCompute/rocm-docs-core)

Run the steps below to build documentation locally.

```
cd docs

pip3 install -r .sphinx/requirements.txt

python3 -m sphinx -T -E -b html -d _build/doctrees -D language=en . _build/html
```

Depending on your setup `sudo` may be required for the pip install.

## Formatting the code

All the code is formatted using clang-format. To format a file, use:

```clang
clang-format-10 -style=file -i <path-to-source-file>
```

Also, githooks can be installed to format the code per-commit:

```bash
./.githooks/install
```
