git.iko.soy/grenade
on master help sign in
Cleanup imports and move examples to new project
e6293b8Huw Campbell
LICENSE+1−1
compare with master
unifiedsplit
@@ -1,4 +1,4 @@
1−Copyright (c) 2016, Huw Campbell
1+Copyright (c) 2016-2017, Huw Campbell
2All rights reserved.
2All rights reserved.
3
3
4Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
4Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
README.md+6−2
@@ -20,8 +20,12 @@ specified and initialised with random weights in a few lines of code with
20```haskell
20```haskell
21type MNIST
21type MNIST
22 = Network
22 = Network
23+ '[ Convolution 1 10 5 5 1 1, Pooling 2 2 2 2, Relu
24+ , Convolution 10 16 5 5 1 1, Pooling 2 2 2 2, FlattenLayer, Relu
23− '[ Convolution 1 10 5 5 1 1, Pooling 2 2 2 2, Relu, Convolution 10 16 5 5 1 1, Pooling 2 2 2 2, FlattenLayer, Relu, FullyConnected 256 80, Logit, FullyConnected 80 10, Logit]
25+ , FullyConnected 256 80, Logit, FullyConnected 80 10, Logit]
24− '[ 'D2 28 28, 'D3 24 24 10, 'D3 12 12 10, 'D3 12 12 10, 'D3 8 8 16, 'D3 4 4 16, 'D1 256, 'D1 256, 'D1 80, 'D1 80, 'D1 10, 'D1 10]
26+ '[ 'D2 28 28, 'D3 24 24 10, 'D3 12 12 10, 'D3 12 12 10
27+ , 'D3 8 8 16, 'D3 4 4 16, 'D1 256, 'D1 256
28+ , 'D1 80, 'D1 80, 'D1 10, 'D1 10]
25
29
26randomMnist :: MonadRandom m => m MNIST
30randomMnist :: MonadRandom m => m MNIST
27randomMnist = randomNetwork
31randomMnist = randomNetwork
examples/LICENSEnew file+10
@@ -0,0 +1,10 @@
1+Copyright (c) 2016-2017, Huw Campbell
2+All rights reserved.
3+
4+Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
5+
6+1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
7+
8+2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
9+
10+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
examples/grenade-examples.cabalnew file+108
@@ -0,0 +1,108 @@
1+name: grenade-examples
2+version: 0.0.1
3+license: BSD2
4+license-file: LICENSE
5+author: Huw Campbell <huw.campbell@gmail.com>
6+maintainer: Huw Campbell <huw.campbell@gmail.com>
7+copyright: (c) 2016-2017 Huw Campbell.
8+synopsis: grenade-examples
9+category: System
10+cabal-version: >= 1.8
11+build-type: Simple
12+description: grenade-examples
13+
14+source-repository head
15+ type: git
16+ location: https://github.com/HuwCampbell/grenade.git
17+
18+library
19+
20+executable feedforward
21+ ghc-options: -Wall -threaded -O2
22+ main-is: main/feedforward.hs
23+ build-depends: base
24+ , grenade
25+ , attoparsec
26+ , bytestring
27+ , cereal
28+ , either
29+ , optparse-applicative == 0.13.*
30+ , text == 1.2.*
31+ , mtl >= 2.2.1 && < 2.3
32+ , hmatrix
33+ , transformers
34+ , singletons
35+ , semigroups
36+ , MonadRandom
37+
38+executable mnist
39+ ghc-options: -Wall -threaded -O2
40+ main-is: main/mnist.hs
41+ build-depends: base
42+ , grenade
43+ , attoparsec
44+ , either
45+ , optparse-applicative == 0.13.*
46+ , text == 1.2.*
47+ , mtl >= 2.2.1 && < 2.3
48+ , hmatrix >= 0.18 && < 0.19
49+ , transformers
50+ , semigroups
51+ , singletons
52+ , MonadRandom
53+ , vector
54+
55+executable gan-mnist
56+ ghc-options: -Wall -threaded -O2
57+ main-is: main/gan-mnist.hs
58+ build-depends: base
59+ , grenade
60+ , attoparsec
61+ , bytestring
62+ , cereal
63+ , either
64+ , optparse-applicative == 0.13.*
65+ , text == 1.2.*
66+ , mtl >= 2.2.1 && < 2.3
67+ , hmatrix >= 0.18 && < 0.19
68+ , transformers
69+ , semigroups
70+ , singletons
71+ , MonadRandom
72+ , vector
73+
74+executable recurrent
75+ ghc-options: -Wall -threaded -O2
76+ main-is: main/recurrent.hs
77+ build-depends: base
78+ , grenade
79+ , attoparsec
80+ , either
81+ , optparse-applicative == 0.13.*
82+ , text == 1.2.*
83+ , mtl >= 2.2.1 && < 2.3
84+ , hmatrix >= 0.18 && < 0.19
85+ , transformers
86+ , semigroups
87+ , singletons
88+ , MonadRandom
89+
90+executable shakespeare
91+ ghc-options: -Wall -threaded -O2
92+ main-is: main/shakespeare.hs
93+ build-depends: base
94+ , grenade
95+ , attoparsec
96+ , bytestring
97+ , cereal
98+ , either
99+ , optparse-applicative == 0.13.*
100+ , text == 1.2.*
101+ , mtl >= 2.2.1 && < 2.3
102+ , hmatrix >= 0.18 && < 0.19
103+ , transformers
104+ , semigroups
105+ , singletons
106+ , vector
107+ , MonadRandom
108+ , containers
main/feedforward.hs → examples/main/feedforward.hsrenamed

The content is the same.

main/gan-mnist.hs → examples/main/gan-mnist.hsrenamed+4−3
@@ -58,7 +58,7 @@ import Grenade
58import Grenade.Utils.OneHot
58import Grenade.Utils.OneHot
59
59
60type Discriminator = Network '[ Convolution 1 10 5 5 1 1, Pooling 2 2 2 2, Relu, Convolution 10 16 5 5 1 1, Pooling 2 2 2 2, Reshape, Relu, FullyConnected 256 80, Logit, FullyConnected 80 1, Logit]
60type Discriminator = Network '[ Convolution 1 10 5 5 1 1, Pooling 2 2 2 2, Relu, Convolution 10 16 5 5 1 1, Pooling 2 2 2 2, Reshape, Relu, FullyConnected 256 80, Logit, FullyConnected 80 1, Logit]
61− '[ 'D2 28 28, 'D3 24 24 10, 'D3 12 12 10, 'D3 12 12 10, 'D3 8 8 16, 'D3 4 4 16, 'D1 256, 'D1 256, 'D1 80, 'D1 80, 'D1 1, 'D1 1]
61+ '[ 'D2 28 28, 'D3 24 24 10, 'D3 12 12 10, 'D3 12 12 10, 'D3 8 8 16, 'D3 4 4 16, 'D1 256, 'D1 256, 'D1 80, 'D1 80, 'D1 1, 'D1 1]
62
62
63type Generator = Network '[ FullyConnected 100 10240, Relu, Reshape, Convolution 10 10 5 5 1 1, Relu, Convolution 10 1 1 1 1 1, Logit, Reshape]
63type Generator = Network '[ FullyConnected 100 10240, Relu, Reshape, Convolution 10 10 5 5 1 1, Relu, Convolution 10 1 1 1 1 1, Logit, Reshape]
64 '[ 'D1 100, 'D1 10240, 'D1 10240, 'D3 32 32 10, 'D3 28 28 10, 'D3 28 28 10, 'D3 28 28 1, 'D3 28 28 1, 'D2 28 28 ]
64 '[ 'D1 100, 'D1 10240, 'D1 10240, 'D3 32 32 10, 'D3 28 28 10, 'D3 28 28 10, 'D3 28 28 1, 'D3 28 28 1, 'D2 28 28 ]
@@ -77,9 +77,10 @@ trainExample rate discriminator generator realExample noiseSource
77 (discriminatorTapeFake, guessFake) = runNetwork discriminator fakeExample
77 (discriminatorTapeFake, guessFake) = runNetwork discriminator fakeExample
78
78
79 (discriminator'real, _) = runGradient discriminator discriminatorTapeReal ( guessReal - 1 )
79 (discriminator'real, _) = runGradient discriminator discriminatorTapeReal ( guessReal - 1 )
80+ (discriminator'fake, _) = runGradient discriminator discriminatorTapeFake guessFake
80− (discriminator'fake, push) = runGradient discriminator discriminatorTapeFake guessFake
81+ (_, push) = runGradient discriminator discriminatorTapeFake ( guessFake - 1)
81
82
82− (generator', _) = runGradient generator generatorTape (-push)
83+ (generator', _) = runGradient generator generatorTape push
83
84
84 newDiscriminator = foldl' (applyUpdate rate { learningRegulariser = learningRegulariser rate * 10}) discriminator [ discriminator'real, discriminator'fake ]
85 newDiscriminator = foldl' (applyUpdate rate { learningRegulariser = learningRegulariser rate * 10}) discriminator [ discriminator'real, discriminator'fake ]
85 newGenerator = applyUpdate rate generator generator'
86 newGenerator = applyUpdate rate generator generator'
main/mnist.hs → examples/main/mnist.hsrenamed+18−2
@@ -34,8 +34,24 @@ import Grenade.Utils.OneHot
34
34
35-- With the mnist data from Kaggle normalised to doubles between 0 and 1, learning rate of 0.01 and 15 iterations,
35-- With the mnist data from Kaggle normalised to doubles between 0 and 1, learning rate of 0.01 and 15 iterations,
36-- this network should get down to about a 1.3% error rate.
36-- this network should get down to about a 1.3% error rate.
37−type MNIST = Network '[ Convolution 1 10 5 5 1 1, Pooling 2 2 2 2, Relu, Convolution 10 16 5 5 1 1, Pooling 2 2 2 2, Reshape, Relu, FullyConnected 256 80, Logit, FullyConnected 80 10, Logit]
37+--
38− '[ 'D2 28 28, 'D3 24 24 10, 'D3 12 12 10, 'D3 12 12 10, 'D3 8 8 16, 'D3 4 4 16, 'D1 256, 'D1 256, 'D1 80, 'D1 80, 'D1 10, 'D1 10]
38+-- /NOTE:/ This model is actually too complex for MNIST, and one should use the type given in the readme instead.
39+-- This one is just here to demonstrate Inception layers in use.
40+--
41+type MNIST =
42+ Network
43+ '[ Reshape
44+ , Inception 28 28 1 5 5 5, Pooling 2 2 2 2, Relu
45+ , Inception 14 14 15 5 5 5, Pooling 2 2 2 2, Relu
46+ , Reshape
47+ , FullyConnected 735 80, Logit
48+ , FullyConnected 80 10, Logit]
49+ '[ 'D2 28 28, 'D3 28 28 1
50+ , 'D3 28 28 15, 'D3 14 14 15, 'D3 14 14 15
51+ , 'D3 14 14 15, 'D3 7 7 15, 'D3 7 7 15
52+ , 'D1 735
53+ , 'D1 80, 'D1 80
54+ , 'D1 10, 'D1 10]
39
55
40randomMnist :: MonadRandom m => m MNIST
56randomMnist :: MonadRandom m => m MNIST
41randomMnist = randomNetwork
57randomMnist = randomNetwork
main/recurrent.hs → examples/main/recurrent.hsrenamed

The content is the same.

main/shakespeare.hs → examples/main/shakespeare.hsrenamed

The content is the same.

grenade.cabal+36−121
@@ -4,7 +4,7 @@ license: BSD2
4license-file: LICENSE
4license-file: LICENSE
5author: Huw Campbell <huw.campbell@gmail.com>
5author: Huw Campbell <huw.campbell@gmail.com>
6maintainer: Huw Campbell <huw.campbell@gmail.com>
6maintainer: Huw Campbell <huw.campbell@gmail.com>
7−copyright: (c) 2015 Huw Campbell.
7+copyright: (c) 2016-2017 Huw Campbell.
8synopsis: grenade
8synopsis: grenade
9category: System
9category: System
10cabal-version: >= 1.8
10cabal-version: >= 1.8
@@ -12,12 +12,12 @@ build-type: Simple
12description: grenade.
12description: grenade.
13
13
14extra-source-files:
14extra-source-files:
15− cbits/im2col.h
15+ cbits/im2col.h
16− cbits/im2col.c
16+ cbits/im2col.c
17− cbits/gradient_decent.h
17+ cbits/gradient_decent.h
18− cbits/gradient_decent.c
18+ cbits/gradient_decent.c
19− cbits/pad.h
19+ cbits/pad.h
20− cbits/pad.c
20+ cbits/pad.c
21
21
22source-repository head
22source-repository head
23 type: git
23 type: git
@@ -27,25 +27,26 @@ library
27 build-depends:
27 build-depends:
28 base >= 4.8 && < 5
28 base >= 4.8 && < 5
29 , bytestring == 0.10.*
29 , bytestring == 0.10.*
30− , containers
30+ , containers >= 0.5 && < 0.6
31+ , cereal >= 0.5 && < 0.6
31− , deepseq
32+ , deepseq >= 1.4 && < 1.5
32− , either == 4.4.*
33− , cereal
34 , exceptions == 0.8.*
33 , exceptions == 0.8.*
35 , hmatrix == 0.18.*
34 , hmatrix == 0.18.*
36− , MonadRandom
35+ , MonadRandom >= 0.4 && < 0.6
37− , mtl >= 2.2.1 && < 2.3
36+ , mtl >= 2.2.1 && < 2.3
38− , primitive
37+ , primitive >= 0.6 && < 0.7
39 , text == 1.2.*
38 , text == 1.2.*
40− , transformers
41− , singletons >= 2.1 && < 2.3
39+ , singletons >= 2.1 && < 2.3
42− , vector == 0.11.*
40+ , vector >= 0.11 && < 0.13
43
41
44 ghc-options:
42 ghc-options:
45 -Wall
43 -Wall
46 hs-source-dirs:
44 hs-source-dirs:
47 src
45 src
48
46
47+ if impl(ghc < 8.0)
48+ ghc-options: -fno-warn-incomplete-patterns
49+
49
50
50 exposed-modules:
51 exposed-modules:
51 Grenade
52 Grenade
@@ -55,19 +56,24 @@ library
55 Grenade.Core.Network
56 Grenade.Core.Network
56 Grenade.Core.Runner
57 Grenade.Core.Runner
57 Grenade.Core.Shape
58 Grenade.Core.Shape
59+
58− Grenade.Layers.Crop
60+ Grenade.Layers
59 Grenade.Layers.Concat
61 Grenade.Layers.Concat
60 Grenade.Layers.Convolution
62 Grenade.Layers.Convolution
63+ Grenade.Layers.Crop
61 Grenade.Layers.Dropout
64 Grenade.Layers.Dropout
65+ Grenade.Layers.Elu
62 Grenade.Layers.FullyConnected
66 Grenade.Layers.FullyConnected
63− Grenade.Layers.Reshape
67+ Grenade.Layers.Inception
64 Grenade.Layers.Logit
68 Grenade.Layers.Logit
65 Grenade.Layers.Merge
69 Grenade.Layers.Merge
66− Grenade.Layers.Relu
67− Grenade.Layers.Elu
68− Grenade.Layers.Tanh
69 Grenade.Layers.Pad
70 Grenade.Layers.Pad
70 Grenade.Layers.Pooling
71 Grenade.Layers.Pooling
72+ Grenade.Layers.Relu
73+ Grenade.Layers.Reshape
74+ Grenade.Layers.Softmax
75+ Grenade.Layers.Tanh
76+ Grenade.Layers.Trivial
71
77
72 Grenade.Layers.Internal.Convolution
78 Grenade.Layers.Internal.Convolution
73 Grenade.Layers.Internal.Pad
79 Grenade.Layers.Internal.Pad
@@ -81,111 +87,20 @@ library
81 Grenade.Recurrent.Core.Network
87 Grenade.Recurrent.Core.Network
82 Grenade.Recurrent.Core.Runner
88 Grenade.Recurrent.Core.Runner
83
89
90+ Grenade.Recurrent.Layers
84 Grenade.Recurrent.Layers.BasicRecurrent
91 Grenade.Recurrent.Layers.BasicRecurrent
85 Grenade.Recurrent.Layers.LSTM
92 Grenade.Recurrent.Layers.LSTM
86
93
87 Grenade.Utils.OneHot
94 Grenade.Utils.OneHot
88
95
89− includes: cbits/im2col.h
96+ includes: cbits/im2col.h
90− cbits/gradient_decent.h
97+ cbits/gradient_decent.h
91− cbits/pad.h
98+ cbits/pad.h
92− c-sources: cbits/im2col.c
99+ c-sources: cbits/im2col.c
93− cbits/gradient_decent.c
100+ cbits/gradient_decent.c
94− cbits/pad.c
101+ cbits/pad.c
95−
96− cc-options: -std=c99 -O3 -msse4.2 -Wall -Werror -DCABAL=1
97−
98−executable feedforward
99− ghc-options: -Wall -threaded -O2
100− main-is: main/feedforward.hs
101− build-depends: base
102− , grenade
103− , attoparsec
104− , bytestring
105− , cereal
106− , either
107− , optparse-applicative == 0.13.*
108− , text == 1.2.*
109− , mtl >= 2.2.1 && < 2.3
110− , hmatrix
111− , transformers
112− , singletons
113− , semigroups
114− , MonadRandom
115−
116−executable mnist
117− ghc-options: -Wall -threaded -O2
118− main-is: main/mnist.hs
119− build-depends: base
120− , grenade
121− , attoparsec
122− , either
123− , optparse-applicative == 0.13.*
124− , text == 1.2.*
125− , mtl >= 2.2.1 && < 2.3
126− , hmatrix >= 0.18 && < 0.19
127− , transformers
128− , semigroups
129− , singletons
130− , MonadRandom
131− , vector
132−
133−executable gan-mnist
134− ghc-options: -Wall -threaded -O2
135− main-is: main/gan-mnist.hs
136− build-depends: base
137− , grenade
138− , attoparsec
139− , bytestring
140− , cereal
141− , either
142− , optparse-applicative == 0.13.*
143− , text == 1.2.*
144− , mtl >= 2.2.1 && < 2.3
145− , hmatrix >= 0.18 && < 0.19
146− , transformers
147− , semigroups
148− , singletons
149− , MonadRandom
150− , vector
151−
152−executable recurrent
153− ghc-options: -Wall -threaded -O2
154− main-is: main/recurrent.hs
155− build-depends: base
156− , grenade
157− , attoparsec
158− , either
159− , optparse-applicative == 0.13.*
160− , text == 1.2.*
161− , mtl >= 2.2.1 && < 2.3
162− , hmatrix >= 0.18 && < 0.19
163− , transformers
164− , semigroups
165− , singletons
166− , MonadRandom
167−
168−
169−executable shakespeare
170− ghc-options: -Wall -threaded -O2
171− main-is: main/shakespeare.hs
172− build-depends: base
173− , grenade
174− , attoparsec
175− , bytestring
176− , cereal
177− , either
178− , optparse-applicative == 0.13.*
179− , text == 1.2.*
180− , mtl >= 2.2.1 && < 2.3
181− , hmatrix >= 0.18 && < 0.19
182− , transformers
183− , semigroups
184− , singletons
185− , vector
186− , MonadRandom
187− , containers
188
102
103+ cc-options: -std=c99 -O3 -msse4.2 -Wall -Werror -DCABAL=1
189
104
190test-suite test
105test-suite test
191 type: exitcode-stdio-1.0
106 type: exitcode-stdio-1.0
src/Grenade.hs+49−20
@@ -1,23 +1,52 @@
1module Grenade (
1module Grenade (
2+ -- | This is an empty module which simply re-exports public definitions
3+ -- for machine learning with Grenade.
4+
5+ -- * Exported modules
6+ --
7+ -- | The core types and runners for Grenade.
2− module X
8+ module Grenade.Core
9+
10+ -- | The neural network layer zoo
11+ , module Grenade.Layers
12+
13+
14+ -- * Overview of the library
15+ -- $library
16+
17+ -- * Example usage
18+ -- $example
19+
3 ) where
20 ) where
4
21
5−import Grenade.Core.LearningParameters as X
22+import Grenade.Core
6−import Grenade.Core.Layer as X
23+import Grenade.Layers
7−import Grenade.Core.Network as X
24+
8−import Grenade.Core.Runner as X
25+{- $library
9−import Grenade.Core.Shape as X
26+Grenade is a purely functional deep learning library.
10−import Grenade.Layers.Concat as X
27+
11−import Grenade.Layers.Crop as X
28+It provides an expressive type level API for the construction
12−import Grenade.Layers.Dropout as X
29+of complex neural network architectures. Backing this API is and
13−import Grenade.Layers.Pad as X
30+implementation written using BLAS and LAPACK, mostly provided by
14−import Grenade.Layers.Pooling as X
31+the hmatrix library.
15−import Grenade.Layers.Reshape as X
32+-}
16−import Grenade.Layers.FullyConnected as X
33+
17−import Grenade.Layers.Logit as X
34+{- $example
18−import Grenade.Layers.Merge as X
35+A few examples are provided at https://github.com/HuwCampbell/grenade
19−import Grenade.Layers.Convolution as X
36+under the examples folder.
20−import Grenade.Layers.Relu as X
37+
21−import Grenade.Layers.Elu as X
38+The starting place is to write your neural network type and a
22−import Grenade.Layers.Tanh as X
39+function to create a random layer of that type. The following
23−import Grenade.Layers.Softmax as X
40+is a simple example which runs a logistic regression.
41+
42+> type MyNet = Network '[ FullyConnected 10 1, Logit ] '[ 'D1 10, 'D1 1, 'D1 1 ]
43+>
44+> randomMyNet :: MonadRandom MyNet
45+> randomMyNet = randomNetwork
46+
47+The function `randomMyNet` witnesses the `CreatableNetwork`
48+constraint of the neural network, that is it ensures the network
49+can be built, and hence, that the architecture is sound.
50+-}
51+
52+
src/Grenade/Core.hs+10−5
@@ -1,8 +1,13 @@
1module Grenade.Core (
1module Grenade.Core (
2− module X
2+ module Grenade.Core.Layer
3+ , module Grenade.Core.LearningParameters
4+ , module Grenade.Core.Network
5+ , module Grenade.Core.Runner
6+ , module Grenade.Core.Shape
3 ) where
7 ) where
4
8
5−import Grenade.Core.Layer as X
9+import Grenade.Core.Layer
6−import Grenade.Core.LearningParameters as X
10+import Grenade.Core.LearningParameters
7−import Grenade.Core.Shape as X
8−import Grenade.Core.Network as X
11+import Grenade.Core.Network
12+import Grenade.Core.Runner
13+import Grenade.Core.Shape
src/Grenade/Core/LearningParameters.hs+4
@@ -1,4 +1,8 @@
1module Grenade.Core.LearningParameters (
1module Grenade.Core.LearningParameters (
2+ -- | This module contains learning algorithm specific
3+ -- code. Currently, this module should be consifered
4+ -- unstable, due to issue #26.
5+
2 LearningParameters (..)
6 LearningParameters (..)
3 ) where
7 ) where
4
8
src/Grenade/Core/Network.hs+2−7
@@ -1,4 +1,3 @@
1−{-# LANGUAGE CPP #-}
2{-# LANGUAGE DataKinds #-}
1{-# LANGUAGE DataKinds #-}
3{-# LANGUAGE BangPatterns #-}
2{-# LANGUAGE BangPatterns #-}
4{-# LANGUAGE GADTs #-}
3{-# LANGUAGE GADTs #-}
@@ -19,10 +18,6 @@ This module defines the core data types and functions
19for non-recurrent neural networks.
18for non-recurrent neural networks.
20-}
19-}
21
20
22−#if __GLASGOW_HASKELL__ < 800
23−{-# OPTIONS_GHC -fno-warn-incomplete-patterns #-}
24−#endif
25−
26module Grenade.Core.Network (
21module Grenade.Core.Network (
27 Network (..)
22 Network (..)
28 , Gradients (..)
23 , Gradients (..)
@@ -47,9 +42,9 @@ import Grenade.Core.Shape
47
42
48-- | Type of a network.
43-- | Type of a network.
49--
44--
50−-- The [*] type specifies the types of the layers.
45+-- The @[*]@ type specifies the types of the layers.
51--
46--
52−-- The [Shape] type specifies the shapes of data passed between the layers.
47+-- The @[Shape]@ type specifies the shapes of data passed between the layers.
53--
48--
54-- Can be considered to be a heterogeneous list of layers which are able to
49-- Can be considered to be a heterogeneous list of layers which are able to
55-- transform the data shapes of the network.
50-- transform the data shapes of the network.
src/Grenade/Core/Shape.hs−9
@@ -1,4 +1,3 @@
1−{-# LANGUAGE CPP #-}
2{-# LANGUAGE DataKinds #-}
1{-# LANGUAGE DataKinds #-}
3{-# LANGUAGE GADTs #-}
2{-# LANGUAGE GADTs #-}
4{-# LANGUAGE KindSignatures #-}
3{-# LANGUAGE KindSignatures #-}
@@ -8,11 +7,6 @@
8{-# LANGUAGE FlexibleContexts #-}
7{-# LANGUAGE FlexibleContexts #-}
9{-# LANGUAGE ScopedTypeVariables #-}
8{-# LANGUAGE ScopedTypeVariables #-}
10{-# LANGUAGE RankNTypes #-}
9{-# LANGUAGE RankNTypes #-}
11−
12−-- Ghc 7.10 fails to recognise n2 is complete.
13−#if __GLASGOW_HASKELL__ < 800
14−{-# OPTIONS_GHC -fno-warn-incomplete-patterns #-}
15−#endif
16{-|
10{-|
17Module : Grenade.Core.Shape
11Module : Grenade.Core.Shape
18Description : Core definition of the Shapes of data we understand
12Description : Core definition of the Shapes of data we understand
@@ -65,17 +59,14 @@ data Shape
65-- All shapes are held in contiguous memory.
59-- All shapes are held in contiguous memory.
66-- 3D is held in a matrix (usually row oriented) which has height depth * rows.
60-- 3D is held in a matrix (usually row oriented) which has height depth * rows.
67data S (n :: Shape) where
61data S (n :: Shape) where
68− -- | One dimensional data
69 S1D :: ( KnownNat len )
62 S1D :: ( KnownNat len )
70 => R len
63 => R len
71 -> S ('D1 len)
64 -> S ('D1 len)
72
65
73− -- | Two dimensional data
74 S2D :: ( KnownNat rows, KnownNat columns )
66 S2D :: ( KnownNat rows, KnownNat columns )
75 => L rows columns
67 => L rows columns
76 -> S ('D2 rows columns)
68 -> S ('D2 rows columns)
77
69
78− -- | Three dimensional data
79 S3D :: ( KnownNat rows
70 S3D :: ( KnownNat rows
80 , KnownNat columns
71 , KnownNat columns
81 , KnownNat depth
72 , KnownNat depth
src/Grenade/Layers.hsnew file+33
@@ -0,0 +1,33 @@
1+module Grenade.Layers (
2+ module Grenade.Layers.Concat
3+ , module Grenade.Layers.Convolution
4+ , module Grenade.Layers.Crop
5+ , module Grenade.Layers.Elu
6+ , module Grenade.Layers.FullyConnected
7+ , module Grenade.Layers.Inception
8+ , module Grenade.Layers.Logit
9+ , module Grenade.Layers.Merge
10+ , module Grenade.Layers.Pad
11+ , module Grenade.Layers.Pooling
12+ , module Grenade.Layers.Reshape
13+ , module Grenade.Layers.Relu
14+ , module Grenade.Layers.Softmax
15+ , module Grenade.Layers.Tanh
16+ , module Grenade.Layers.Trivial
17+ ) where
18+
19+import Grenade.Layers.Concat
20+import Grenade.Layers.Convolution
21+import Grenade.Layers.Crop
22+import Grenade.Layers.Elu
23+import Grenade.Layers.Pad
24+import Grenade.Layers.FullyConnected
25+import Grenade.Layers.Inception
26+import Grenade.Layers.Logit
27+import Grenade.Layers.Merge
28+import Grenade.Layers.Pooling
29+import Grenade.Layers.Reshape
30+import Grenade.Layers.Relu
31+import Grenade.Layers.Softmax
32+import Grenade.Layers.Tanh
33+import Grenade.Layers.Trivial
src/Grenade/Layers/Concat.hs+4−2
@@ -9,11 +9,13 @@
9{-# LANGUAGE ScopedTypeVariables #-}
9{-# LANGUAGE ScopedTypeVariables #-}
10{-# LANGUAGE StandaloneDeriving #-}
10{-# LANGUAGE StandaloneDeriving #-}
11{-|
11{-|
12−Module : Grenade.Core.Network
12+Module : Grenade.Layers.Concat
13−Description : Core definition a simple neural etwork
13+Description : Concatenation layer
14Copyright : (c) Huw Campbell, 2016-2017
14Copyright : (c) Huw Campbell, 2016-2017
15License : BSD2
15License : BSD2
16Stability : experimental
16Stability : experimental
17+
18+This module provides the concatenation layer, whic used to run two separate layers in parallel and combine their outputs.
17-}
19-}
18module Grenade.Layers.Concat (
20module Grenade.Layers.Concat (
19 Concat (..)
21 Concat (..)
src/Grenade/Layers/Inception.hs+26−12
@@ -9,10 +9,13 @@
9{-# LANGUAGE ScopedTypeVariables #-}
9{-# LANGUAGE ScopedTypeVariables #-}
10{-|
10{-|
11Module : Grenade.Core.Network
11Module : Grenade.Core.Network
12−Description : Core definition a simple neural etwork
12+Description : Inception style parallel convolutional network composition.
13Copyright : (c) Huw Campbell, 2016-2017
13Copyright : (c) Huw Campbell, 2016-2017
14License : BSD2
14License : BSD2
15Stability : experimental
15Stability : experimental
16+
17+Export an Inception style type, which can be used to build up
18+complex multiconvolution size networks.
16-}
19-}
17module Grenade.Layers.Inception (
20module Grenade.Layers.Inception (
18 Inception
21 Inception
@@ -25,24 +28,35 @@ import Grenade.Layers.Convolution
25import Grenade.Layers.Pad
28import Grenade.Layers.Pad
26import Grenade.Layers.Concat
29import Grenade.Layers.Concat
27
30
28−
31+-- | Type of an inception layer.
32+--
33+-- It looks like a bit of a handful, but is actually pretty easy to use.
34+--
35+-- The first three type parameters are the size of the (3D) data the
36+-- inception layer will take. It will emit 3D data with the number of
37+-- channels being the sum of @chx@, @chy@, @chz@, which are the number
38+-- of convolution filters in the 3x3, 5x5, and 7x7 convolutions Layers
39+-- respectively.
40+--
41+-- The network get padded effectively before each convolution filters
42+-- such that the output dimension is the same x and y as the input.
29type Inception rows cols channels chx chy chz
43type Inception rows cols channels chx chy chz
30− = Network '[ Concat ('D3 (rows - 2) (cols - 2) (chx + chy)) (InceptionS rows cols channels chx chy) ('D3 (rows - 2) (cols - 2) chz) (Inception7x7 rows cols channels chz) ]
44+ = Network '[ Concat ('D3 rows cols (chx + chy)) (InceptionS rows cols channels chx chy) ('D3 rows cols chz) (Inception7x7 rows cols channels chz) ]
31− '[ 'D3 rows cols channels, 'D3 (rows -2) (cols -2) (chx + chy + chz) ]
45+ '[ 'D3 rows cols channels, 'D3 rows cols (chx + chy + chz) ]
32
46
33type InceptionS rows cols channels chx chy
47type InceptionS rows cols channels chx chy
34− = Network '[ Concat ('D3 (rows - 2) (cols - 2) chx) (Inception3x3 rows cols channels chx) ('D3 (rows - 2) (cols - 2) chy) (Inception5x5 rows cols channels chy) ]
48+ = Network '[ Concat ('D3 rows cols chx) (Inception3x3 rows cols channels chx) ('D3 rows cols chy) (Inception5x5 rows cols channels chy) ]
35− '[ 'D3 rows cols channels, 'D3 (rows -2) (cols -2) (chx + chy) ]
49+ '[ 'D3 rows cols channels, 'D3 rows cols (chx + chy) ]
36
50
37type Inception3x3 rows cols channels chx
51type Inception3x3 rows cols channels chx
38− = Network '[ Convolution channels chx 3 3 1 1 ]
52+ = Network '[ Pad 1 1 1 1, Convolution channels chx 3 3 1 1 ]
39− '[ 'D3 rows cols channels, 'D3 (rows -2) (cols -2) chx ]
53+ '[ 'D3 rows cols channels, 'D3 (rows + 2) (cols + 2) channels, 'D3 rows cols chx ]
40
54
41type Inception5x5 rows cols channels chx
55type Inception5x5 rows cols channels chx
42− = Network '[ Pad 1 1 1 1, Convolution channels chx 5 5 1 1 ]
56+ = Network '[ Pad 2 2 2 2, Convolution channels chx 5 5 1 1 ]
43− '[ 'D3 rows cols channels, 'D3 (rows + 2) (cols + 2) channels, 'D3 (rows - 2) (cols - 2) chx ]
57+ '[ 'D3 rows cols channels, 'D3 (rows + 4) (cols + 4) channels, 'D3 rows cols chx ]
44
58
45type Inception7x7 rows cols channels chx
59type Inception7x7 rows cols channels chx
46− = Network '[ Pad 2 2 2 2, Convolution channels chx 7 7 1 1 ]
60+ = Network '[ Pad 3 3 3 3, Convolution channels chx 7 7 1 1 ]
47− '[ 'D3 rows cols channels, 'D3 (rows + 4) (cols + 4) channels, 'D3 (rows - 2) (cols - 2) chx ]
61+ '[ 'D3 rows cols channels, 'D3 (rows + 6) (cols + 6) channels, 'D3 rows cols chx ]
48
62
src/Grenade/Layers/Trivial.hs+3−2
@@ -9,7 +9,7 @@ module Grenade.Layers.Trivial (
9
9
10import Data.Serialize
10import Data.Serialize
11
11
12−import Grenade.Core.Network
12+import Grenade.Core
13
13
14-- | A trivial layer.
14-- | A trivial layer.
15data Trivial = Trivial
15data Trivial = Trivial
@@ -25,5 +25,6 @@ instance UpdateLayer Trivial where
25 createRandom = return Trivial
25 createRandom = return Trivial
26
26
27instance (a ~ b) => Layer Trivial a b where
27instance (a ~ b) => Layer Trivial a b where
28+ type Tape Trivial a b = ()
28− runForwards _ = id
29+ runForwards _ a = ((), a)
29 runBackwards _ _ y = ((), y)
30 runBackwards _ _ y = ((), y)
src/Grenade/Recurrent.hs+4−6
@@ -1,9 +1,7 @@
1module Grenade.Recurrent (
1module Grenade.Recurrent (
2− module X
2+ module Grenade.Recurrent.Core
3+ , module Grenade.Recurrent.Layers
3 ) where
4 ) where
4
5
5−import Grenade.Recurrent.Core.Layer as X
6+import Grenade.Recurrent.Core
6−import Grenade.Recurrent.Core.Network as X
7−import Grenade.Recurrent.Core.Runner as X
8−import Grenade.Recurrent.Layers.BasicRecurrent as X
7+import Grenade.Recurrent.Layers
9−import Grenade.Recurrent.Layers.LSTM as X
src/Grenade/Recurrent/Core.hs+6−3
@@ -1,6 +1,9 @@
1module Grenade.Recurrent.Core (
1module Grenade.Recurrent.Core (
2− module X
2+ module Grenade.Recurrent.Core.Layer
3+ , module Grenade.Recurrent.Core.Network
4+ , module Grenade.Recurrent.Core.Runner
3 ) where
5 ) where
4
6
5−import Grenade.Recurrent.Core.Layer as X
7+import Grenade.Recurrent.Core.Layer
6−import Grenade.Recurrent.Core.Network as X
8+import Grenade.Recurrent.Core.Network
9+import Grenade.Recurrent.Core.Runner
src/Grenade/Recurrent/Core/Network.hs+1−5
@@ -1,4 +1,3 @@
1−{-# LANGUAGE CPP #-}
2{-# LANGUAGE DataKinds #-}
1{-# LANGUAGE DataKinds #-}
3{-# LANGUAGE GADTs #-}
2{-# LANGUAGE GADTs #-}
4{-# LANGUAGE TypeOperators #-}
3{-# LANGUAGE TypeOperators #-}
@@ -10,10 +9,7 @@
10{-# LANGUAGE RankNTypes #-}
9{-# LANGUAGE RankNTypes #-}
11{-# LANGUAGE BangPatterns #-}
10{-# LANGUAGE BangPatterns #-}
12{-# LANGUAGE ScopedTypeVariables #-}
11{-# LANGUAGE ScopedTypeVariables #-}
13−
12+{-# LANGUAGE UndecidableInstances #-}
14−#if __GLASGOW_HASKELL__ < 800
15−{-# OPTIONS_GHC -fno-warn-incomplete-patterns #-}
16−#endif
17
13
18module Grenade.Recurrent.Core.Network (
14module Grenade.Recurrent.Core.Network (
19 Recurrent
15 Recurrent
src/Grenade/Recurrent/Core/Runner.hs−5
@@ -3,16 +3,11 @@
3{-# LANGUAGE DataKinds #-}
3{-# LANGUAGE DataKinds #-}
4{-# LANGUAGE ScopedTypeVariables #-}
4{-# LANGUAGE ScopedTypeVariables #-}
5{-# LANGUAGE TypeOperators #-}
5{-# LANGUAGE TypeOperators #-}
6−{-# LANGUAGE CPP #-}
7{-# LANGUAGE TypeFamilies #-}
6{-# LANGUAGE TypeFamilies #-}
8{-# LANGUAGE FlexibleContexts #-}
7{-# LANGUAGE FlexibleContexts #-}
9{-# LANGUAGE RankNTypes #-}
8{-# LANGUAGE RankNTypes #-}
10{-# LANGUAGE RecordWildCards #-}
9{-# LANGUAGE RecordWildCards #-}
11
10
12−#if __GLASGOW_HASKELL__ < 800
13−{-# OPTIONS_GHC -fno-warn-incomplete-patterns #-}
14−#endif
15−
16module Grenade.Recurrent.Core.Runner (
11module Grenade.Recurrent.Core.Runner (
17 trainRecurrent
12 trainRecurrent
18 , runRecurrent
13 , runRecurrent
src/Grenade/Recurrent/Layers.hsnew file+7
@@ -0,0 +1,7 @@
1+module Grenade.Recurrent.Layers (
2+ module Grenade.Recurrent.Layers.BasicRecurrent
3+ , module Grenade.Recurrent.Layers.LSTM
4+ ) where
5+
6+import Grenade.Recurrent.Layers.BasicRecurrent
7+import Grenade.Recurrent.Layers.LSTM
src/Grenade/Recurrent/Layers/BasicRecurrent.hs−5
@@ -1,4 +1,3 @@
1−{-# LANGUAGE CPP #-}
2{-# LANGUAGE DataKinds #-}
1{-# LANGUAGE DataKinds #-}
3{-# LANGUAGE GADTs #-}
2{-# LANGUAGE GADTs #-}
4{-# LANGUAGE RecordWildCards #-}
3{-# LANGUAGE RecordWildCards #-}
@@ -8,10 +7,6 @@
8{-# LANGUAGE FlexibleContexts #-}
7{-# LANGUAGE FlexibleContexts #-}
9{-# LANGUAGE UndecidableInstances #-}
8{-# LANGUAGE UndecidableInstances #-}
10
9
11−-- GHC 7.10 doesn't see recurrent run functions as total.
12−#if __GLASGOW_HASKELL__ < 800
13−{-# OPTIONS_GHC -fno-warn-incomplete-patterns #-}
14−#endif
15module Grenade.Recurrent.Layers.BasicRecurrent (
10module Grenade.Recurrent.Layers.BasicRecurrent (
16 BasicRecurrent (..)
11 BasicRecurrent (..)
17 , randomBasicRecurrent
12 , randomBasicRecurrent
src/Grenade/Recurrent/Layers/LSTM.hs−6
@@ -1,5 +1,4 @@
1{-# LANGUAGE BangPatterns #-}
1{-# LANGUAGE BangPatterns #-}
2−{-# LANGUAGE CPP #-}
3{-# LANGUAGE DataKinds #-}
2{-# LANGUAGE DataKinds #-}
4{-# LANGUAGE GADTs #-}
3{-# LANGUAGE GADTs #-}
5{-# LANGUAGE RankNTypes #-}
4{-# LANGUAGE RankNTypes #-}
@@ -11,11 +10,6 @@
11{-# LANGUAGE ViewPatterns #-}
10{-# LANGUAGE ViewPatterns #-}
12{-# LANGUAGE ScopedTypeVariables #-}
11{-# LANGUAGE ScopedTypeVariables #-}
13
12
14−-- GHC 7.10 doesn't see recurrent run functions as total.
15−#if __GLASGOW_HASKELL__ < 800
16−{-# OPTIONS_GHC -fno-warn-incomplete-patterns #-}
17−#endif
18−
19module Grenade.Recurrent.Layers.LSTM (
13module Grenade.Recurrent.Layers.LSTM (
20 LSTM (..)
14 LSTM (..)
21 , LSTMWeights (..)
15 , LSTMWeights (..)
test/Test/Grenade/Layers/PadCrop.hs+9
@@ -30,6 +30,15 @@ prop_pad_crop =
30 (_ , grad) = runBackwards net tapes d
30 (_ , grad) = runBackwards net tapes d
31 in d ~~~ res .&&. grad ~~~ d
31 in d ~~~ res .&&. grad ~~~ d
32
32
33+prop_pad_crop_2d :: Property
34+prop_pad_crop_2d =
35+ let net :: Network '[Pad 2 3 4 6, Crop 2 3 4 6] '[ 'D2 7 9, 'D2 16 15, 'D2 7 9 ]
36+ net = Pad :~> Crop :~> NNil
37+ in gamble genOfShape $ \(d :: S ('D2 7 9)) ->
38+ let (tapes, res) = runForwards net d
39+ (_ , grad) = runBackwards net tapes d
40+ in d ~~~ res .&&. grad ~~~ d
41+
33(~~~) :: S x -> S x -> Bool
42(~~~) :: S x -> S x -> Bool
34(S1D x) ~~~ (S1D y) = norm_Inf (x - y) < 0.00001
43(S1D x) ~~~ (S1D y) = norm_Inf (x - y) < 0.00001
35(S2D x) ~~~ (S2D y) = norm_Inf (x - y) < 0.00001
44(S2D x) ~~~ (S2D y) = norm_Inf (x - y) < 0.00001