name: neural version: 0.3.0.0 cabal-version: >=1.10 build-type: Simple license: MIT license-file: LICENSE copyright: Copyright: (c) 2016 Lars Bruenjes maintainer: brunjlar@gmail.com stability: provisional homepage: https://github.com/brunjlar/neural bug-reports: https://github.com/brunjlar/neural/issues synopsis: Neural Networks in native Haskell description: The goal of `neural` is to provide a modular and flexible neural network library written in native Haskell. . Features include . * /composability/ via arrow-like instances and , . * /automatic differentiation/ for automatic gradient descent/ backpropagation training (using Edward Kmett's fabulous library). . The idea is to be able to easily define new components and wire them up in flexible, possibly complicated ways (convolutional deep networks etc.). . Three examples are included as proof of concept: . * A simple neural network that approximates the sqrt function on [0,4]. . * A slightly more complicated neural network that solves the famous problem. . * A first (still simple) neural network for recognizing handwritten digits from the equally famous database. . The library is still very much experimental at this point. category: Machine Learning author: Lars Bruenjes tested-with: GHC ==7.10.3 GHC ==8.0.1 extra-source-files: .travis.yml .gitignore .ghci stack.yaml README.markdown source-repository head type: git location: https://github.com/brunjlar/neural.git source-repository this type: git location: https://github.com/brunjlar/neural.git tag: 0.3.0.0 library exposed-modules: Numeric.Neural Numeric.Neural.Layer Numeric.Neural.Model Numeric.Neural.Normalization Numeric.Neural.Pipes Data.MyPrelude Data.Utils Data.Utils.Analytic Data.Utils.Arrow Data.Utils.List Data.Utils.Matrix Data.Utils.Pipes Data.Utils.Random Data.Utils.Stack Data.Utils.Statistics Data.Utils.Traversable Data.Utils.Vector build-depends: base >=4.7 && <5, ad >=4.3.2.1 && <4.4, array >=0.5.1.1 && <0.6, bytestring >=0.10.8.1 && <0.11, deepseq >=1.4.2.0 && <1.5, directory >=1.2.6.2 && <1.3, filepath >=1.4.1.0 && <1.5, ghc-typelits-natnormalise >=0.4.1 && <0.5, hspec >=2.2.3 && <2.3, kan-extensions >=5.0.1 && <5.1, lens ==4.14.*, MonadRandom >=0.4.2.3 && <0.5, monad-par >=0.3.4.7 && <0.4, monad-par-extras >=0.3.3 && <0.4, mtl >=2.2.1 && <2.3, parallel >=3.2.1.0 && <3.3, pipes >=4.1.9 && <4.2, pipes-bytestring >=2.1.3 && <2.2, pipes-safe >=2.2.4 && <2.3, profunctors ==5.2.*, reflection >=2.1.2 && <2.2, STMonadTrans >=0.3.3 && <0.4, text >=1.2.2.1 && <1.3, transformers >=0.5.2.0 && <0.6, typelits-witnesses >=0.2.3.0 && <0.3, vector >=0.11.0.0 && <0.12 default-language: Haskell2010 hs-source-dirs: src ghc-options: -Wall -fexcess-precision -optc-O3 -optc-ffast-math executable iris main-is: iris.hs build-depends: base >=4.7 && <5, attoparsec >=0.13.0.2 && <0.14, neural >=0.3.0.0 && <0.4, text >=1.2.2.1 && <1.3 default-language: Haskell2010 hs-source-dirs: examples/iris ghc-options: -Wall -threaded -rtsopts -with-rtsopts=-N -fexcess-precision -optc-O3 -optc-ffast-math executable sqrt main-is: sqrt.hs build-depends: base >=4.7 && <5, MonadRandom >=0.4.2.3 && <0.5, neural >=0.3.0.0 && <0.4 default-language: Haskell2010 hs-source-dirs: examples/sqrt ghc-options: -Wall -threaded -rtsopts -with-rtsopts=-N -fexcess-precision -optc-O3 -optc-ffast-math executable MNIST main-is: MNIST.hs build-depends: base >=4.7 && <5, array >=0.5.1.1 && <0.6, JuicyPixels >=3.2.7.1 && <3.3, neural >=0.3.0.0 && <0.4, pipes >=4.1.9 && <4.2, pipes-zlib >=0.4.4 && <0.5 default-language: Haskell2010 hs-source-dirs: examples/MNIST ghc-options: -Wall -threaded -rtsopts -with-rtsopts=-N -fexcess-precision -optc-O3 -optc-ffast-math test-suite neural-test type: exitcode-stdio-1.0 main-is: Spec.hs build-depends: base >=4.7 && <5, hspec >=2.2.3 && <2.3, MonadRandom >=0.4.2.3 && <0.5, neural >=0.3.0.0 && <0.4 default-language: Haskell2010 hs-source-dirs: test other-modules: Utils.MatrixSpec Utils.VectorSpec ghc-options: -Wall -threaded -rtsopts -with-rtsopts=-N -fexcess-precision -optc-O3 -optc-ffast-math test-suite neural-doctest type: exitcode-stdio-1.0 main-is: doctest.hs build-depends: base >=4.7 && <5, doctest >=0.11.0 && <0.12, Glob >=0.7.5 && <0.8 default-language: Haskell2010 hs-source-dirs: doctest ghc-options: -Wall -threaded -rtsopts -with-rtsopts=-N -fexcess-precision -optc-O3 -optc-ffast-math benchmark neural-bench type: exitcode-stdio-1.0 main-is: benchmark.hs build-depends: base >=4.7 && <5, criterion >=1.1.1.0 && <1.2, neural >=0.3.0.0 && <0.4 default-language: Haskell2010 hs-source-dirs: benchmark ghc-options: -Wall -threaded -rtsopts -with-rtsopts=-N -fexcess-precision -optc-O3 -optc-ffast-math