adf7312 · grenade · git.iko.soy

src/Grenade.hs+1−1

compare with master

unifiedsplit

@@ -46,7 +46,7 @@ is a simple example which runs a logistic regression.

46> randomMyNet = randomNetwork

47

48The function `randomMyNet` witnesses the `CreatableNetwork`

49−constraint of the neural network, that is, it ensures the network

49+constraint of the neural network, and in doing so, ensures the network

50can be built, and hence, that the architecture is sound.

51-}

52

src/Grenade/Layers/Elu.hs+7

@@ -2,6 +2,13 @@

2{-# LANGUAGE TypeOperators #-}

3{-# LANGUAGE TypeFamilies #-}

4{-# LANGUAGE MultiParamTypeClasses #-}

5+{-|

6+Module : Grenade.Layers.Logit

7+Description : Exponential linear unit layer

8+Copyright : (c) Huw Campbell, 2016-2017

9+License : BSD2

10+Stability : experimental

11+-}

5module Grenade.Layers.Elu (

12module Grenade.Layers.Elu (

6 Elu (..)

13 Elu (..)

7 ) where

14 ) where

src/Grenade/Layers/Logit.hs+8

@@ -3,6 +3,13 @@

3{-# LANGUAGE TypeFamilies #-}

4{-# LANGUAGE FlexibleInstances #-}

5{-# LANGUAGE MultiParamTypeClasses #-}

6+{-|

7+Module : Grenade.Layers.Logit

8+Description : Sigmoid nonlinear layer

9+Copyright : (c) Huw Campbell, 2016-2017

10+License : BSD2

11+Stability : experimental

12+-}

6module Grenade.Layers.Logit (

13module Grenade.Layers.Logit (

7 Logit (..)

14 Logit (..)

8 ) where

15 ) where

@@ -14,6 +21,7 @@ import Data.Singletons

14import Grenade.Core

21import Grenade.Core

15

22

16-- | A Logit layer.

23-- | A Logit layer.

24+--

17-- A layer which can act between any shape of the same dimension, perfoming an sigmoid function.

25-- A layer which can act between any shape of the same dimension, perfoming an sigmoid function.

18-- This layer should be used as the output layer of a network for logistic regression (classification)

26-- This layer should be used as the output layer of a network for logistic regression (classification)

19-- problems.

27-- problems.

src/Grenade/Layers/Pad.hs+9

@@ -5,6 +5,13 @@

5{-# LANGUAGE TypeFamilies #-}

6{-# LANGUAGE MultiParamTypeClasses #-}

7{-# LANGUAGE FlexibleContexts #-}

8+{-|

9+Module : Grenade.Core.Pad

10+Description : Padding layer for 2D and 3D images

11+Copyright : (c) Huw Campbell, 2016-2017

12+License : BSD2

13+Stability : experimental

14+-}

8module Grenade.Layers.Pad (

15module Grenade.Layers.Pad (

9 Pad (..)

16 Pad (..)

10 ) where

17 ) where

@@ -22,6 +29,8 @@ import Numeric.LinearAlgebra (konst, subMatrix, diagBlock)

22import Numeric.LinearAlgebra.Static (extract, create)

29import Numeric.LinearAlgebra.Static (extract, create)

23

30

24-- | A padding layer for a neural network.

31-- | A padding layer for a neural network.

32+--

33+-- Pads on the X and Y dimension of an image.

25data Pad :: Nat

34data Pad :: Nat

26 -> Nat

35 -> Nat

27 -> Nat

36 -> Nat

src/Grenade/Layers/Pooling.hs+8

@@ -6,6 +6,13 @@

6{-# LANGUAGE TypeFamilies #-}

7{-# LANGUAGE MultiParamTypeClasses #-}

8{-# LANGUAGE FlexibleContexts #-}

9+{-|

10+Module : Grenade.Core.Pooling

11+Description : Max Pooling layer for 2D and 3D images

12+Copyright : (c) Huw Campbell, 2016-2017

13+License : BSD2

14+Stability : experimental

15+-}

9module Grenade.Layers.Pooling (

16module Grenade.Layers.Pooling (

10 Pooling (..)

17 Pooling (..)

11 ) where

18 ) where

@@ -22,6 +29,7 @@ import Grenade.Layers.Internal.Pooling

22import Numeric.LinearAlgebra.Static as LAS hiding ((|||), build, toRows)

29import Numeric.LinearAlgebra.Static as LAS hiding ((|||), build, toRows)

23

30

24-- | A pooling layer for a neural network.

31-- | A pooling layer for a neural network.

32+--

25-- Does a max pooling, looking over a kernel similarly to the convolution network, but returning

33-- Does a max pooling, looking over a kernel similarly to the convolution network, but returning

26-- maxarg only. This layer is often used to provide minor amounts of translational invariance.

34-- maxarg only. This layer is often used to provide minor amounts of translational invariance.

27--

35--

src/Grenade/Layers/Relu.hs+7

@@ -2,6 +2,13 @@

2{-# LANGUAGE TypeOperators #-}

3{-# LANGUAGE TypeFamilies #-}

4{-# LANGUAGE MultiParamTypeClasses #-}

5+{-|

6+Module : Grenade.Layers.Relu

7+Description : Rectifying linear unit layer

8+Copyright : (c) Huw Campbell, 2016-2017

9+License : BSD2

10+Stability : experimental

11+-}

5module Grenade.Layers.Relu (

12module Grenade.Layers.Relu (

6 Relu (..)

13 Relu (..)

7 ) where

14 ) where

src/Grenade/Layers/Reshape.hs+10−3

@@ -3,6 +3,13 @@

3{-# LANGUAGE TypeFamilies #-}

4{-# LANGUAGE MultiParamTypeClasses #-}

5{-# LANGUAGE FlexibleContexts #-}

6+{-|

7+Module : Grenade.Layers.Reshape

8+Description : Multipurpose reshaping layer

9+Copyright : (c) Huw Campbell, 2016-2017

10+License : BSD2

11+Stability : experimental

12+-}

6module Grenade.Layers.Reshape (

13module Grenade.Layers.Reshape (

7 Reshape (..)

14 Reshape (..)

8 ) where

15 ) where

@@ -19,9 +26,9 @@ import Grenade.Core

19

26

20-- | Reshape Layer

27-- | Reshape Layer

21--

28--

22−-- Flattens input down to D1 from either 2D or 3D data.

29+-- The Reshape layer can flatten any 2D or 3D image to 1D vector with the

23−--

30+-- same number of activations, as well as cast up from 1D to a 2D or 3D

24−-- Casts input D1 up to either 2D or 3D data if the shapes are good.

31+-- shape.

25--

32--

26-- Can also be used to turn a 3D image with only one channel into a 2D image

33-- Can also be used to turn a 3D image with only one channel into a 2D image

27-- or vice versa.

34-- or vice versa.

src/Grenade/Layers/Softmax.hs+11

@@ -3,6 +3,13 @@

3{-# LANGUAGE TypeFamilies #-}

4{-# LANGUAGE FlexibleInstances #-}

5{-# LANGUAGE MultiParamTypeClasses #-}

6+{-|

7+Module : Grenade.Core.Softmax

8+Description : Softmax loss layer

9+Copyright : (c) Huw Campbell, 2016-2017

10+License : BSD2

11+Stability : experimental

12+-}

6module Grenade.Layers.Softmax (

13module Grenade.Layers.Softmax (

7 Softmax (..)

14 Softmax (..)

8 , softmax

15 , softmax

@@ -17,8 +24,12 @@ import Grenade.Core

17import Numeric.LinearAlgebra.Static as LAS

24import Numeric.LinearAlgebra.Static as LAS

18

25

19-- | A Softmax layer

26-- | A Softmax layer

27+--

20-- This layer is like a logit layer, but normalises

28-- This layer is like a logit layer, but normalises

21-- a set of matricies to be probabilities.

29-- a set of matricies to be probabilities.

30+--

31+-- One can use this layer as the last layer in a network

32+-- if they need normalised probabilities.

22data Softmax = Softmax

33data Softmax = Softmax

23 deriving Show

34 deriving Show

24

35

src/Grenade/Layers/Tanh.hs+7

@@ -3,6 +3,13 @@

3{-# LANGUAGE TypeFamilies #-}

4{-# LANGUAGE FlexibleInstances #-}

5{-# LANGUAGE MultiParamTypeClasses #-}

6+{-|

7+Module : Grenade.Layers.Tanh

8+Description : Hyperbolic tangent nonlinear layer

9+Copyright : (c) Huw Campbell, 2016-2017

10+License : BSD2

11+Stability : experimental

12+-}

6module Grenade.Layers.Tanh (

13module Grenade.Layers.Tanh (

7 Tanh (..)

14 Tanh (..)

8 ) where

15 ) where

src/Grenade/Layers/Trivial.hs+11−1

@@ -3,6 +3,13 @@

3{-# LANGUAGE TypeFamilies #-}

4{-# LANGUAGE MultiParamTypeClasses #-}

5{-# LANGUAGE FlexibleInstances #-}

6+{-|

7+Module : Grenade.Core.Trivial

8+Description : Trivial layer which perfoms no operations on the data

9+Copyright : (c) Huw Campbell, 2016-2017

10+License : BSD2

11+Stability : experimental

12+-}

6module Grenade.Layers.Trivial (

13module Grenade.Layers.Trivial (

7 Trivial (..)

14 Trivial (..)

8 ) where

15 ) where

@@ -11,7 +18,10 @@ import Data.Serialize

11

18

12import Grenade.Core

19import Grenade.Core

13

20

14−-- | A trivial layer.

21+-- | A Trivial layer.

22+--

23+-- This can be used to pass an unchanged value up one side of a

24+-- graph, for a Residual network for example.

15data Trivial = Trivial

25data Trivial = Trivial

16 deriving Show

26 deriving Show

17

27