https://github.com/locuslab/stable_dynamics

Companion code to "Learning Stable Deep Dynamics Models" (Manek and Kolter, 2019)
https://github.com/locuslab/stable_dynamics

Last synced: about 2 months ago
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Companion code to "Learning Stable Deep Dynamics Models" (Manek and Kolter, 2019)

• Host: GitHub
• URL: https://github.com/locuslab/stable_dynamics
• Owner: locuslab
• Created: 2019-06-04T19:41:00.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2019-12-02T17:42:24.000Z (about 5 years ago)
• Last Synced: 2024-04-14T05:52:01.492Z (9 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 26 MB
• Stars: 28
• Watchers: 3
• Forks: 12
• Open Issues: 2
• Metadata Files:
  • Readme: README.md

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README

        
# Learning Stable Deep Dynamics Models

Companion code to "Learning Stable Deep Dynamics Models" (Manek and Kolter, 2019)

## Installation

You need Python 3.6 or later, with packages listed in `requirements.txt`. Ensure that the directories `experiments/` and `runs/` are writable.

## Running

All training commands produce output in the `experiments/` folder, automatically named with the hyperparameters used in training. You can track training progress using `tensorboard runs/`.

### Pendulum

To train the models for an ``-link pendulum, you should first run the command:

```sh

./train_pendulum_simple 

```

which will create and cache the training data and the evaluation data. (Warning: this is a cpu-heavy task that may take hours to complete.) Once that is complete, you can train multiple models in parallel with:

```sh

./train_many 

```

You can concurrently train train models with different ``.

Ensure that `pendulum-cache/` is writable.

### VAE

To train the VAE, you need to convert videos to sequentially-numbered frames in `youtube//fr_[0-9]*.jpg`. A good place to start is [this](https://www.youtube.com/watch?v=I4dYM1biVq0) video, which you can download and convert with:

```sh

mkdir youtube

cd youtube

youtube-dl -o bonfire.%(ext) -f 134 I4dYM1biVq0

ffmpeg -ss 0:01:00 -i bonfire.mp4 -t 3:20 -vf scale=320:240 bonfire/fr_%06d.png

```

(You need to install `youtube-dl` and `ffmpeg`.)

Once that is done, you can train the simple VAE model with:

```sh

./train_vae_simple bonfire

```

And the stable VAE with:

```sh

./train_vae_stable stable_exp bonfire 0.0005 -0.25 0.00 PSICNN 0.001

```