collenchyma-NN •

collenchyma-NN provides Neural Network related algorithms for Collenchyma. Run NN operations on servers, desktops or mobiles, GPUs, FPGAs or CPUS, without carrying about OpenCL or CUDA support on the machine.

collenchyma-NN was started at Autumn to support the Machine Intelligence Framework Leaf with backend-agnostic, state-of-the-art performance.

For more information,

see collenchyma-NN's Documentation
visit Collenchyma for more information about portable operations and other Plugins.
or get in touch on Twitter or Gitter

Provided Operations

This Plugins provides the following operations to the Collenchyma Backend. Every Operation includes forward + backward. A - means not yet implemented. More information can be found in the Documentation.

Operation	CUDA	OpenCL	Native
Sigmoid	{ cuDNN v3, v4 }	-	Rust
SigmoidPointwise	{ cuDNN v3, v4 }	-
ReLU	{ cuDNN v3, v4 }	-	Rust
ReLUPointwise	{ cuDNN v3, v4 }	-
Tanh	{ cuDNN v3, v4 }	-	Rust
TanhPointwise	{ cuDNN v3, v4 }	-

Normalization (LRN)	{ cuDNN v3, v4 }	-	-

Convolution	{ cuDNN v3, v4 }	-	-

Softmax	{ cuDNN v3, v4 }	-	Rust
LogSoftmax	{ cuDNN v3, v4 }	-	Rust

Pooling Max	{ cuDNN v3, v4 }	-	-
Pooling Avg	{ cuDNN v3, v4 }	-	-

Kudos to ehiggs, for implementing the native Rust operations.

Getting Started

If you're using Cargo, just add collenchyma-NN to your Cargo.toml:

[dependencies]
collenchyma = "0.0.8"
collenchyma-nn = "0.3.4"

If you're using Cargo Edit, you can call:

$ cargo add collenchyma-nn

Usage

Bring the Plugin trait and the other important Collenchyma traits/structs in scope and you will be able to execute the here provided operations on your Collenchyma Backend.

extern crate collenchyma as co;
extern crate collenchyma_nn as nn;
use co::prelude::*;
use nn::*;
fn main() {
    // Initialize a CUDA Backend.
    let backend = Backend::<Cuda>::default().unwrap();
    // Initialize two SharedTensors.
    // Usually you would want also fill them with data.
    // More infos about that in the Collenchyma README.md
    let mut x = SharedTensor::<f32>::new(backend.device(), &(1, 1, 3)).unwrap();
    let mut result = SharedTensor::<f32>::new(backend.device(), &(1, 1, 3)).unwrap();
    // Use the operation provided by this Plugin.
    backend.sigmoid(&mut x, &mut result);
}

Contributing

Want to contribute? Awesome! We have instructions to help you get started contributing code or documentation. And high priority issues, that we could need your help with.

We have a mostly real-time collaboration culture and happens here on Github and on the Collenchyma Gitter Channel. You can also reach out to the Maintainers {@MJ, @hobofan}.

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as below, without any additional terms or conditions.

Changelog

A changelog is a log or record of all the changes made to a project, such as a website or software project, usually including such records as bug fixes, new features, etc. - Wikipedia

You can find the release history at the CHANGELOG file.

We are using Clog, the Rust tool for auto generating CHANGELOG files.