Updated concat layer and code generation structure

Author: leopiney

src/TensorSafe/Commands/Examples.hs

@@ -2,7 +2,8 @@
 module TensorSafe.Commands.Examples (examples) where
 
 import TensorSafe.Examples.Examples
-  ( mnistConcatenateExample,
+  ( mnistConcatenateComplexExample,
+    mnistConcatenateExample,
     mnistExample,
     mnistExampleDense,
     simpleExample,
@@ -18,3 +19,5 @@ examples = do
   mnistExampleDense
   putStrLn "\n\n"
   mnistConcatenateExample
+  putStrLn "\n\n"
+  mnistConcatenateComplexExample

src/TensorSafe/Compile/Expr.hs

@@ -40,7 +40,7 @@ data DLayer
 
 -- | Defines the
 data CNetwork
-  = CNSequence CNetwork
+  = CNSequence (Map String String) CNetwork
   | CNConcatenate CNetwork CNetwork
   | CNCons CNetwork CNetwork
   | CNLayer DLayer (Map String String)
@@ -98,21 +98,53 @@ class Generator l where
   -- have the CNetwork compiled at a separate file.
   generateFile :: l -> CNetwork -> Text
 
+data Model = Model String Integer
+
+instance Show Model where
+  show (Model name level) = name ++ "_" ++ show level
+
+newModel :: Model
+newModel = Model "x" 0
+
+nextModel :: String -> Model -> Model
+nextModel name (Model _ level) = Model name (level + 1)
+
 instance Generator JavaScript where
   generate l =
-    T.intercalate "\n" . generateJS
+    T.intercalate "\n" . generateJS newModel
     where
-      generateJS :: CNetwork -> [Text]
-      generateJS (CNSequence cn) = "var model = tf.sequential();" : generateJS cn
-      generateJS (CNConcatenate cn1 cn2) = generateJS cn1 ++ generateJS cn2 -- FIX
-      generateJS (CNCons cn1 cn2) = generateJS cn1 ++ generateJS cn2
-      generateJS CNNil = []
-      generateJS CNReturn = []
-      generateJS (CNLayer layer params) =
+      generateJS :: Model -> CNetwork -> [Text]
+      generateJS model (CNSequence params cn) =
+        format ("var input = tf.input(" % string % ");") (paramsToJS params) :
+        format ("var " % string % " = input;") (show model) :
+        generateJS model cn
+          ++ [ format
+                 ("model = tf.model({ inputs: input, outputs: " % string % " });")
+                 (show model)
+             ]
+      generateJS model (CNConcatenate cn1 cn2) =
+        let modelA = nextModel "a" model
+            modelB = nextModel "b" model
+         in format ("var " % string % " = " % string % ";") (show modelA) (show model) :
+            generateJS modelA cn1
+              ++ format ("var " % string % " = " % string % ";") (show modelB) (show model) :
+            generateJS modelB cn2
+              ++ [ format
+                     (string % " = tf.layers.concatenate().apply([" % string % ", " % string % "])")
+                     (show model)
+                     (show modelA)
+                     (show modelB)
+                 ]
+      generateJS model (CNCons cn1 cn2) = generateJS model cn1 ++ generateJS model cn2
+      generateJS _ CNNil = []
+      generateJS _ CNReturn = []
+      generateJS model (CNLayer layer params) =
         [ format
-            ("model.add(tf.layers." % string % "(" % string % "));")
+            (string % " = tf.layers." % string % "(" % string % ").apply(" % string % ")")
+            (show model)
             (generateName l layer)
             (paramsToJS params)
+            (show model)
         ]
 
   generateFile l cn =
@@ -152,7 +184,7 @@ instance Generator Python where
     T.intercalate "\n" . generatePy
     where
       generatePy :: CNetwork -> [Text]
-      generatePy (CNSequence cn) = "model = tf.keras.models.Sequential()" : generatePy cn
+      generatePy (CNSequence params cn) = "model = tf.keras.models.Sequential()" : generatePy cn
       generatePy (CNConcatenate cn1 cn2) = generatePy cn1 ++ generatePy cn2 -- FIX
       generatePy (CNCons cn1 cn2) = generatePy cn1 ++ generatePy cn2
       generatePy CNNil = []

src/TensorSafe/Examples/ConcatenateExample.hs

@@ -4,18 +4,20 @@
 -- | This module implements the MNIST model using some Concatenate layers
 module TensorSafe.Examples.ConcatenateExample
   ( mnistConcatenate,
+    mnistConcatenateComplex,
   )
 where
 
 import TensorSafe.Layers
-  ( Conv2D,
+  ( Concatenate,
+    Conv2D,
     Dense,
     Flatten,
     MaxPooling,
     Relu,
     Sigmoid,
   )
-import TensorSafe.Network (Concatenate, MkINetwork, mkINetwork)
+import TensorSafe.Network (MkINetwork, mkINetwork)
 import TensorSafe.Shape (Shape (D1, D3))
 
 type Ls1 =
@@ -25,26 +27,80 @@ type Ls1 =
        MaxPooling 2 2 2 2,
        Flatten
      ]
-    ('D3 64 64 1) -- Input
-    ('D1 28800) -- Output
+    ('D3 28 28 1) -- Input
+    ('D1 4608) -- Output
 
 type Ls2 =
   MkINetwork
     '[Conv2D 1 16 8 8 1 1, Relu, MaxPooling 2 2 2 2, Flatten]
-    ('D3 64 64 1) -- Input
-    ('D1 12544) -- Output
+    ('D3 28 28 1) -- Input
+    ('D1 1600) -- Output
 
 type MNISTConcatenate =
   MkINetwork
     '[ Concatenate Ls1 Ls2,
-       Dense 41344 1024,
+       Dense 6208 1024,
        Relu,
        Dense 1024 10,
        Sigmoid
      ]
-    ('D3 64 64 1) -- Input
+    ('D3 28 28 1) -- Input
     ('D1 10) -- Output
 
--- | MNIST implementation using Convolutional layers
+-- | MNIST implementation using Concatenate layer
 mnistConcatenate :: MNISTConcatenate
-mnistConcatenate = mkINetwork
+mnistConcatenate = mkINetwork
+
+--
+--
+--
+type Ls211 =
+  MkINetwork
+    '[ Conv2D 8 32 4 4 1 1,
+       Relu,
+       MaxPooling 2 2 2 2,
+       Flatten
+     ]
+    ('D3 14 14 8) -- Input
+    ('D1 800) -- Output
+
+type Ls212 =
+  MkINetwork
+    '[ Conv2D 8 64 8 8 1 1,
+       Relu,
+       MaxPooling 2 2 2 2,
+       Flatten
+     ]
+    ('D3 14 14 8) -- Input
+    ('D1 576) -- Output
+
+type Ls21 =
+  MkINetwork
+    '[ Concatenate Ls211 Ls212
+     ]
+    ('D3 14 14 8) -- Input
+    ('D1 1376) -- Output
+
+type Ls22 =
+  MkINetwork
+    '[Conv2D 8 16 8 8 1 1, Relu, MaxPooling 2 2 2 2, Flatten]
+    ('D3 14 14 8) -- Input
+    ('D1 144) -- Output
+
+type MNISTConcatenateComplex =
+  MkINetwork
+    '[ Conv2D 1 8 1 1 1 1,
+       Relu,
+       MaxPooling 2 2 2 2,
+       Concatenate Ls21 Ls22,
+       Dense 1520 512,
+       Relu,
+       Dense 512 10,
+       Sigmoid
+     ]
+    ('D3 28 28 1) -- Input
+    ('D1 10) -- Output
+
+-- | MNIST implementation using Convolutional layers
+mnistConcatenateComplex :: MNISTConcatenateComplex
+mnistConcatenateComplex = mkINetwork

src/TensorSafe/Examples/Examples.hs

@@ -7,12 +7,13 @@ module TensorSafe.Examples.Examples
     mnistExampleDense,
     simpleExample,
     mnistConcatenateExample,
+    mnistConcatenateComplexExample,
   )
 where
 
 import Data.Text.Lazy (unpack)
 import TensorSafe.Compile.Expr (JavaScript (..), generate)
-import TensorSafe.Examples.ConcatenateExample (mnistConcatenate)
+import TensorSafe.Examples.ConcatenateExample (mnistConcatenate, mnistConcatenateComplex)
 import TensorSafe.Examples.MnistExample (mnist, mnistDense)
 import TensorSafe.Examples.SimpleExample
   ( lstm,
@@ -84,4 +85,19 @@ mnistConcatenateExample =
     putStrLn "\n"
     putStrLn "MNIST Concatenate generation"
     putStrLn "------------------------------"
-    putStrLn $ unpack $ generate JavaScript (toCNetwork mnistConcatenate)
+    putStrLn $ unpack $ generate JavaScript (toCNetwork mnistConcatenate)
+
+mnistConcatenateComplexExample :: IO ()
+mnistConcatenateComplexExample =
+  do
+    putStrLn "MNIST Concatenate Complex with Concatenate example"
+    putStrLn "------------------------------"
+    print mnistConcatenateComplex
+    putStrLn "\n"
+    putStrLn "MNIST Concatenate Complex compilation"
+    putStrLn "------------------------------"
+    print (toCNetwork mnistConcatenateComplex)
+    putStrLn "\n"
+    putStrLn "MNIST Concatenate Complex generation"
+    putStrLn "------------------------------"
+    putStrLn $ unpack $ generate JavaScript (toCNetwork mnistConcatenateComplex)

src/TensorSafe/Layers.hs

@@ -1,6 +1,7 @@
 -- | This module exposes all Layers declared at TensorSafe.Layers.
 module TensorSafe.Layers
   ( BatchNormalization,
+    Concatenate (..),
     Conv2D,
     Dense,
     Dropout,
@@ -17,6 +18,7 @@ module TensorSafe.Layers
 where
 
 import TensorSafe.Layers.BatchNormalization (BatchNormalization)
+import TensorSafe.Layers.Concatenate (Concatenate (..))
 import TensorSafe.Layers.Conv2D (Conv2D)
 import TensorSafe.Layers.Dense (Dense)
 import TensorSafe.Layers.Dropout (Dropout)

src/TensorSafe/Layers/Concatenate.hs

@@ -0,0 +1,18 @@
+{-# LANGUAGE DataKinds #-}
+{-# LANGUAGE GADTs #-}
+{-# LANGUAGE ScopedTypeVariables #-}
+{-# LANGUAGE TypeFamilies #-}
+
+-- | This module declares the Concatenate layer data type.
+module TensorSafe.Layers.Concatenate where
+
+import Data.Kind (Type)
+
+-- | Concatenates two valid INetwork types
+data Concatenate :: Type -> Type -> Type where
+  Concatenate :: in1 -> in2 -> Concatenate in1 in2
+  deriving (Show)
+
+-- |
+-- | Layer instance of Concatenate defined at Network.hs module
+-- |