name: grenade version: 0.1.0 license: BSD2 license-file: LICENSE author: Huw Campbell maintainer: Huw Campbell copyright: (c) 2016-2017 Huw Campbell. synopsis: Practical Deep Learning in Haskell category: AI, Machine Learning cabal-version: >= 1.10 build-type: Simple description: Grenade is a composable, dependently typed, practical, and fast recurrent neural network library for precise specifications and complex deep neural networks in Haskell. . Grenade provides an API for composing layers of a neural network into a sequence parallel graph in a type safe manner; running networks with reverse automatic differentiation to calculate their gradients; and applying gradient descent for learning. . Documentation and examples are available on github . extra-source-files: README.md cbits/im2col.h cbits/im2col.c cbits/gradient_descent.h cbits/gradient_descent.c cbits/pad.h cbits/pad.c source-repository head type: git location: https://github.com/HuwCampbell/grenade.git library build-depends: base >= 4.8 && < 5 , bytestring == 0.10.* , containers >= 0.5 && < 0.7 , cereal >= 0.5 && < 0.6 , deepseq >= 1.4 && < 1.5 , hmatrix >= 0.18 && < 0.20 , MonadRandom >= 0.4 && < 0.6 , primitive >= 0.6 && < 0.7 -- Versions of singletons are *tightly* coupled with the -- GHC version so its fine to drop version bounds. , singletons , vector >= 0.11 && < 0.13 ghc-options: -Wall hs-source-dirs: src default-language: Haskell2010 if impl(ghc < 8.0) ghc-options: -fno-warn-incomplete-patterns cpp-options: -DType=* if impl(ghc >= 8.6) default-extensions: NoStarIsType exposed-modules: Grenade Grenade.Core Grenade.Core.Layer Grenade.Core.LearningParameters Grenade.Core.Network Grenade.Core.Runner Grenade.Core.Shape Grenade.Layers Grenade.Layers.Concat Grenade.Layers.Convolution Grenade.Layers.Crop Grenade.Layers.Deconvolution Grenade.Layers.Dropout Grenade.Layers.Elu Grenade.Layers.FullyConnected Grenade.Layers.Inception Grenade.Layers.Logit Grenade.Layers.Merge Grenade.Layers.Pad Grenade.Layers.Pooling Grenade.Layers.Relu Grenade.Layers.Reshape Grenade.Layers.Sinusoid Grenade.Layers.Softmax Grenade.Layers.Tanh Grenade.Layers.Trivial Grenade.Layers.Internal.Convolution Grenade.Layers.Internal.Pad Grenade.Layers.Internal.Pooling Grenade.Layers.Internal.Update Grenade.Recurrent Grenade.Recurrent.Core Grenade.Recurrent.Core.Layer Grenade.Recurrent.Core.Network Grenade.Recurrent.Core.Runner Grenade.Recurrent.Layers Grenade.Recurrent.Layers.BasicRecurrent Grenade.Recurrent.Layers.ConcatRecurrent Grenade.Recurrent.Layers.LSTM Grenade.Utils.OneHot includes: cbits/im2col.h cbits/gradient_descent.h cbits/pad.h c-sources: cbits/im2col.c cbits/gradient_descent.c cbits/pad.c cc-options: -std=c99 -O3 -msse4.2 -Wall -Werror -DCABAL=1 test-suite test type: exitcode-stdio-1.0 main-is: test.hs ghc-options: -Wall -threaded -O2 hs-source-dirs: test default-language: Haskell2010 other-modules: Test.Hedgehog.Compat Test.Hedgehog.Hmatrix Test.Hedgehog.TypeLits Test.Grenade.Network Test.Grenade.Layers.Convolution Test.Grenade.Layers.FullyConnected Test.Grenade.Layers.Nonlinear Test.Grenade.Layers.PadCrop Test.Grenade.Layers.Pooling Test.Grenade.Layers.Internal.Convolution Test.Grenade.Layers.Internal.Pooling Test.Grenade.Layers.Internal.Reference Test.Grenade.Recurrent.Layers.LSTM Test.Grenade.Recurrent.Layers.LSTM.Reference if impl(ghc < 8.0) ghc-options: -fno-warn-incomplete-patterns cpp-options: -DType=* if impl(ghc >= 8.6) default-extensions: NoStarIsType build-depends: base , grenade , hedgehog >= 0.5 && < 0.7 , hmatrix , mtl , singletons , text == 1.2.* , typelits-witnesses , transformers , constraints , MonadRandom , random , ad , reflection , vector benchmark bench type: exitcode-stdio-1.0 main-is: bench.hs ghc-options: -Wall -threaded -O2 hs-source-dirs: bench default-language: Haskell2010 build-depends: base , bytestring , criterion >= 1.1 && < 1.5 , grenade , hmatrix benchmark bench-lstm type: exitcode-stdio-1.0 main-is: bench-lstm.hs ghc-options: -Wall -threaded -O2 hs-source-dirs: bench default-language: Haskell2010 build-depends: base , bytestring , criterion , grenade , hmatrix