# Distiller Installation

These instructions will help get Distiller up and running on your local machine.

You may also want to refer to these resources:

- Dataset installation instructions.
- Jupyter installation instructions.

Notes: - Distiller has only been tested on Ubuntu 16.04 LTS, and with Python 3.5. - If you are not using a GPU, you might need to make small adjustments to the code.

## Clone Distiller

Clone the Distiller code repository from github:

    $ git clone https://github.com/NervanaSystems/distiller.git

The rest of the documentation that follows, assumes that you have cloned your repository to a directory called `distiller`.

## Create a Python virtual environment

We recommend using a Python virtual environment, but that of course, is up to you. There's nothing special about using Distiller in a virtual environment, but we provide some instructions, for completeness.
Before creating the virtual environment, make sure you are located in directory `distiller`. After creating the environment, you should see a directory called `distiller/env`.

### Using virtualenv

If you don't have virtualenv installed, you can find the installation instructions here.

To create the environment, execute:

    $ python3 -m virtualenv env

This creates a subdirectory named `env` where the python virtual environment is stored, and configures the current shell to use it as the default python environment.

### Using venv

If you prefer to use `venv`, then begin by installing it:

    $ sudo apt-get install python3-venv

Then create the environment:

    $ python3 -m venv env

As with virtualenv, this creates a directory called `distiller/env`.

### Activate the environment

The environment activation and deactivation commands for `venv` and `virtualenv` are the same.
!NOTE: Make sure to activate the environment, before proceeding with the installation of the dependency packages:

    $ source env/bin/activate

## Install the package

Finally, install the Distiller package and its dependencies using `pip3`:

    $ cd distiller
    $ pip3 install -e .

This installs Distiller in "development mode", meaning any changes made in the code are reflected in the environment without re-running the install command (so no need to re-install after pulling changes from the Git repository).

PyTorch is included in the `requirements.txt` file, and will currently download PyTorch version 1.0.1 for CUDA 9.0. This is the setup we've used for testing Distiller.

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