Building DeepSpeech native client for Windows
=============================================
Now we can build the native client of DeepSpeech and run inference on Windows using the C# client, to do that we need to compile the ``native_client``.
**Table of Contents**
* `Prerequisites <#prerequisites>`_
* `Getting the code <#getting-the-code>`_
* `Configuring the paths <#configuring-the-paths>`_
* `Adding environment variables <#adding-environment-variables>`_
* `MSYS2 paths <#msys2-paths>`_
* `BAZEL path <#bazel-path>`_
* `Python path <#python-path>`_
* `CUDA paths <#cuda-paths>`_
* `Building the native_client <#building-the-native_client>`_
* `Build for CPU <#cpu>`_
* `Build with CUDA support <#gpu-with-cuda>`_
* `Using the generated library <#using-the-generated-library>`_
Prerequisites
-------------
* Windows 10
* `Windows 10 SDK <https://developer.microsoft.com/en-us/windows/downloads/windows-10-sdk>`_
* `Visual Studio 2019 Community <https://visualstudio.microsoft.com/vs/community/>`_
* `TensorFlow Windows pre-requisites <https://www.tensorflow.org/install/source_windows>`_
Inside the Visual Studio Installer enable ``MS Build Tools`` and ``VC++ 2019 v16.00 (v160) toolset for desktop``.
If you want to enable CUDA support you need to follow the steps in `the TensorFlow docs for building on Windows with CUDA <https://www.tensorflow.org/install/gpu#windows_setup>`_.
We highly recommend sticking to the recommended versions of CUDA/cuDNN in order to avoid compilation errors caused by incompatible versions. We only test with the versions recommended by TensorFlow.
Getting the code
----------------
We need to clone ``mozilla/DeepSpeech``.
.. code-block:: bash
git clone https://github.com/mozilla/DeepSpeech
git submodule sync tensorflow/
git submodule update --init tensorflow/
Configuring the paths
---------------------
There should already be a symbolic link, for this example let's suppose that we cloned into ``D:\cloned`` and now the structure looks like:
.. code-block::
.
├── D:\
│ ├── cloned # Contains DeepSpeech and tensorflow side by side
│ │ └── DeepSpeech # Root of the cloned DeepSpeech
│ │ ├── tensorflow # Root of the cloned mozilla/tensorflow
└── ...
Change your path accordingly to your path structure, for the structure above we are going to use the following command if the symbolic link does not exists:
.. code-block:: bash
mklink /d "D:\cloned\DeepSpeech\tensorflow\native_client" "D:\cloned\DeepSpeech\native_client"
Adding environment variables
----------------------------
After you have installed the requirements there are few environment variables that we need to add to our ``PATH`` variable of the system variables.
MSYS2 paths
~~~~~~~~~~~
For MSYS2 we need to add ``bin`` directory, if you installed in the default route the path that we need to add should looks like ``C:\msys64\usr\bin``. Now we can run ``pacman``:
.. code-block:: bash
pacman -Syu
pacman -Su
pacman -S patch unzip
BAZEL path
~~~~~~~~~~
For BAZEL we need to add the path to the executable, make sure you rename the executable to ``bazel``.
To check the version installed you can run:
.. code-block:: bash
bazel version
PYTHON path
~~~~~~~~~~~
Add your ``python.exe`` path to the ``PATH`` variable.
CUDA paths
~~~~~~~~~~
If you run CUDA enabled ``native_client`` we need to add the following to the ``PATH`` variable.
.. code-block::
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\bin
Building the native_client
^^^^^^^^^^^^^^^^^^^^^^^^^^
There's one last command to run before building, you need to run the `configure.py <https://github.com/mozilla/tensorflow/blob/master/configure.py>`_ inside ``tensorflow`` cloned directory.
At this point we are ready to start building the ``native_client``, go to ``tensorflow`` sub-directory, following our examples should be ``D:\cloned\DeepSpeech\tensorflow``.
CPU
~~~
We will add AVX/AVX2 support in the command, please make sure that your CPU supports these instructions before adding the flags, if not you can remove them.
.. code-block:: bash
bazel build --workspace_status_command="bash native_client/bazel_workspace_status_cmd.sh" -c opt --copt=/arch:AVX --copt=/arch:AVX2 //native_client:libdeepspeech.so
GPU with CUDA
~~~~~~~~~~~~~
If you enabled CUDA in `configure.py <https://github.com/mozilla/tensorflow/blob/master/configure.py>`_ configuration command now you can add ``--config=cuda`` to compile with CUDA support.
.. code-block:: bash
bazel build --workspace_status_command="bash native_client/bazel_workspace_status_cmd.sh" -c opt --config=cuda --copt=/arch:AVX --copt=/arch:AVX2 //native_client:libdeepspeech.so
Be patient, if you enabled AVX/AVX2 and CUDA it will take a long time. Finally you should see it stops and shows the path to the generated ``libdeepspeech.so``.
Using the generated library
---------------------------
As for now we can only use the generated ``libdeepspeech.so`` with the C# clients, go to `native_client/dotnet/ <https://github.com/mozilla/DeepSpeech/tree/master/native_client/dotnet>`_ in your DeepSpeech directory and open the Visual Studio solution, then we need to build in debug or release mode, finally we just need to copy ``libdeepspeech.so`` to the generated ``x64/Debug`` or ``x64/Release`` directory.
