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A simple neural net implementation written in Rust with a focus on cache-efficiency and sequential performance.
Currently only supports supervised learning with fully connected layers.
The preferred way to receive prophet is via cargo or github.
Compile prophet with
cargo build
Run the test suite with
cargo test --release
Note: It is recommended to use --release
for testing since optimizations are insanely effective for prophet.
For additional information while running some long tests use
cargo test --release --verbose -- --nocapture
Run performance test with
cargo bench --features benches
- Convolutional Layers: Foundations have been layed out already!
- GPGPU Support by Vulkano
- Even more flexible learning methods
Licensed under either of
- Apache License, Version 2.0, (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
- MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)
at your option.
- Relicensed the library under the dual license model where the user can choose between MIT or APACHE version 2.0.
- Improved performance of learning algorithms by up to 27%*. (*Tested on my local machine.)
- Updated ndarray from 0.10.10 to 0.10.11 and itertools from 0.6.5 to 0.7.0.
- Relaxed dependency version constraints for rand, num, log and ndarray.
- Usability: Added a HOW TO USE section to the README.
- Dev
- Added some unit tests for
NeuralNet
components for improved stability and maintainability.
- Added some unit tests for
- Fixed long-standing undeterministic bug.
- Reverted
ChaChaRng
usage inNeuralLayer::random
- it is much faster andChaChaRng
's safety is not needed.
- Updated
ndarray
dependency version from0.9
to0.10
- Updated
serde
dependency version from0.9
to1.0
- Enabled
serde
feature by default. NeuralLayer::random
now usesChaChaRng
internally instead ofweak_rng
- Devel:
- travisCI now using new trusty environment
- travisCI now uploads code coverage to coveralls and codecov.io
- travisCI no longer requires
sudo