https://github.com/mayukhdeb/torch-dreams-runwayml
model server template for torch-dreams on runwayML
https://github.com/mayukhdeb/torch-dreams-runwayml
deep-dream-experiments pytorch runwayml
Last synced: about 2 months ago
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model server template for torch-dreams on runwayML
- Host: GitHub
- URL: https://github.com/mayukhdeb/torch-dreams-runwayml
- Owner: Mayukhdeb
- Created: 2020-12-30T10:59:31.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2022-12-08T07:51:18.000Z (over 2 years ago)
- Last Synced: 2025-02-13T19:47:47.711Z (3 months ago)
- Topics: deep-dream-experiments, pytorch, runwayml
- Language: Python
- Homepage:
- Size: 2.37 MB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
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README
# torch-dreams :handshake: runwayML
## How to run
0. Clone the repo and navigate into the folder.
```
$ git clone https://github.com/Mayukhdeb/torch-dreams-runwayML.git
$ cd torch-dreams-runwayML
$ pip install -r requirements.txt
```
1. Start the server with:
```
$ python runway_model.py
```
You should see an output similar to this:
```
Initializing model...
dreamer init on: cuda
Model initialized (0.04s)
Starting model server at http://0.0.0.0:9000...
```
2. Open a new workspace in [RunwayML](https://learn.runwayml.com/#/getting-started/installation) and press `connect`. Make sure your localhost port matches the one given by the server script (in our case it's `9000`)
3. Select the image you want to work with.
4. Play around with the inference parameters and have fun!
Try reading the [torch-dreams docs](https://app.gitbook.com/@mayukh09/s/torch-dreams/) to create fancier visualizations.
## Architecture
Each Runway model consists of two special files:
- [`runway_model.py`](runway_model.py): A Python script that imports the runway module (SDK) and exposes its interface via one or more `@runway.command()` functions. This file is used as the **entrypoint** to your model.
- [`runway.yml`](runway.yml): A configuration file that describes dependencies and build steps needed to build and run the model.
### The `runway_model.py` Entrypoint File
The [`runway_model.py`](runway_model.py) entrypoint file is the file the Runway app will use to query the model. This file can have any name you want, but we recommend calling it `runway_model.py`.
### The `runway.yml` Config File
Each Runway model must have a [`runway.yml`](runway.yml) configuration file in its root directory. This file defines the steps needed to build and run your model for use with Runway. This file is written in YAML, a human-readable superset of JSON. Below is an example of a `runway.yml` file. This example file illustrates how you can provision your model’s environment.
```yaml
version: 0.1
python: 3.6
entrypoint: python runway_model.py
cuda: 10.2
framework: pytorch
files:
ignore:
- image_dataset/*
build_steps:
- pip install runway-python==0.1.0
- pip install -r requirements.txt
```