installation.rst (1274B)
1 .. _installation: 2 3 Local Installation 4 ================== 5 6 Step 1: Get Miniconda 7 ^^^^^^^^^^^^^^^^^^^^^ 8 9 This is a Python package, and it depends on other packages to work. To manage 10 all this, it's recommended to use Miniconda. Get it from 11 https://docs.anaconda.com/miniconda/ 12 13 Step 2: Install NAM 14 ^^^^^^^^^^^^^^^^^^^ 15 16 Now that we have Miniconda, we can install NAM using it. 17 18 (Windows / Linux users) If your computer has an nVIDIA GPU, you should install a 19 GPU-compatible version of PyTorch first: 20 21 .. code-block:: console 22 23 $ conda install -y pytorch pytorch-cuda=12.1 -c pytorch -c nvidia 24 25 Finally, install NAM using pip: 26 27 .. code-block:: console 28 29 $ pip install neural-amp-modeler 30 31 To update an existing installation: 32 33 .. code-block:: console 34 35 pip install --upgrade neural-amp-modeler 36 37 Local development installation 38 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ 39 40 If you're interested in developing this package, there are Anaconda environment 41 definitions included in the ``environments/`` directory. Use the one that's 42 appropriate for the platform you're developing on. The 43 ``.github/workflows/python-pckage.yml`` is also helpful if you want to be sure 44 that you're testing your developments in the same way that contributions will be 45 automatically tested (via GitHub Actions).