collenchyma plugin providing Neural Network operations

plugin, neural-network, computation, collenchyma, hpc


Maximilian Goisser Homu Michael Hirn (MJ) Ewan Higgs

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collenchyma-NN • Join the chat at Build Status License

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,

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:

collenchyma = "0.0.8"
collenchyma-nn = "0.3.4"

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

$ cargo add collenchyma-nn


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
    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);


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.


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.


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at your option.