Please check the build logs for more information.
See Builds for ideas on how to fix a failed build, or Metadata for how to configure docs.rs builds.
If you believe this is docs.rs' fault, open an issue.
Rust Lighter
This project was started as my RUST exercise to abstract the Rust minimalist ML framework Candle (https://github.com/huggingface/candle) and introduce a more convenient way of programming neural network machine learning models.
The behaviour is inspired by Python KERAS (https://keras.io) and the initial step based on the Rust-Keras-like code (https://github.com/AhmedBoin/Rust-Keras-Like).
So let's call the project Candle Lighter 🕯, because it helps to turn on the candle light and is even easier to implement.
Examples can be found below the lib/examples/ directory.
To use it as library just call 'cargo add candlelighter'
CONTRIBUTORS ARE HIGHLY WELCOME
Note: It is by far not production ready and is only used for own training purposes. No warranty and liability is given. I am a private person and not targeting any commercial benefits.
Supported Layer types
Meta Layer | Type | State | Example |
---|---|---|---|
Sequential model | - | ✅ | |
- | Feature scaling | 🏃 | DNN and TNN |
- | Dense | ✅ | DNN |
- | Convolution | ✅ | CNN |
- | Pooling | ✅ | - |
- | Normalization | ✅ | - |
- | Flatten | ✅ | - |
- | Recurrent | ✅ | RNN 1st throw |
- | Regulation | ✅ | - |
- | Feature embedding | ✅ | S2S 1st throw |
- | Attention | 🏃 | TNN 1st throw |
- | Mixture of Experts | 🏃 | ENN 1st throw |
- | Feature masking and -quantization | 🏃 | - |
Parallel model (in sense of split) | - | 🏃 | PNN 1st throw |
Parallel model | Merging | 🏃 | PNN 1st throw |
- | Model fine tuning | 🏃 | - |
License
Tripple-licensed to be compatible with the Rust project and the source roots.
Licensed under the MPL 2.0, MIT license or the Apache license, Version 2.0 at your option.