thereadme/sibe
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rm(sin): remove sin example

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fix(ignoreBiases): was ignoring nodes, lol
fix(w2v): better logging and implementation
This commit is contained in:
Mahdi Dibaiee
2016-09-16 13:31:23 +04:30
parent c0083f5c05
commit d4ac90bbd5
6 changed files with 1119 additions and 146 deletions
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23
src/Sibe.hs
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@@ -10,7 +10,9 @@ module Sibe
Output,
Activation,
forward,
forward',
runLayer,
runLayer',
randomLayer,
randomNetwork,
buildNetwork,
@@ -84,7 +86,6 @@ module Sibe
, batchSize :: Int
, chart :: [(Int, Double, Double)]
, momentum :: Double
, biases :: Bool
} deriving (Show)
emptyNetwork = randomNetwork 0 (0, 0) 0 [] (0, (id, id))
@@ -98,7 +99,6 @@ module Sibe
, batchSize = 0
, chart = []
, momentum = 0
, biases = True
}
saveNetwork :: Network -> String -> IO ()
@@ -133,6 +133,12 @@ module Sibe
compute input (O l@(Layer _ _ (fn, _))) = fn $ runLayer input l
compute input (l@(Layer _ _ (fn, _)) :- n) = compute ((fst . activation $ l) $ runLayer input l) n
forward' :: Input -> Session -> Output
forward' input session = compute input (network session)
where
compute input (O l@(Layer _ _ (fn, _))) = fn $ runLayer' input l
compute input (l@(Layer _ _ (fn, _)) :- n) = compute ((fst . activation $ l) $ runLayer' input l) n
randomLayer :: Seed -> (Int, Int) -> (Double, Double) -> Activation -> Layer
randomLayer seed (wr, wc) (l, u) =
let weights = uniformSample seed wr $ replicate wc (l, u)
@@ -209,14 +215,12 @@ module Sibe
o = fn y
delta = o - target
de = delta * fn' y
-- de = delta / fromIntegral (V.length o) -- cross entropy cost
biases' = biases - scale alpha de
weights' = weights - scale alpha (input `outer` de) -- small inputs learn slowly
layer = Layer biases' weights' (fn, fn') -- updated layer
pass = weights #> de
-- pass = weights #> de
in (O layer, pass)
run input (l@(Layer biases weights (fn, fn')) :- n) =
@@ -226,12 +230,11 @@ module Sibe
de = delta * fn' y
biases' = biases - cmap (*alpha) de
weights' = weights - cmap (*alpha) (input `outer` de)
biases' = biases - scale alpha de
weights' = weights - scale alpha (input `outer` de)
layer = Layer biases' weights' (fn, fn')
pass = weights #> de
-- pass = weights #> de
in (layer :- n', pass)
gd :: Session -> IO Session
@@ -280,8 +283,6 @@ module Sibe
let el = map (\(e, l, _) -> (e, l)) (chart session)
ea = map (\(e, _, a) -> (e, a)) (chart session)
putStrLn $ (show $ epoch session) ++ " => " ++ (show cost) ++ " @ " ++ (show $ learningRate session)
toFile Chart.def "sgd.png" $ do
Chart.layoutlr_title Chart..= "loss over time"
Chart.plotLeft (Chart.line "loss" [el])
@@ -312,8 +313,8 @@ module Sibe
ignoreBiases session =
session { network = rmbias (network session) }
where
rmbias (O (Layer nodes biases a)) = O $ Layer nodes (biases * 0) a
rmbias ((Layer nodes biases a) :- n) = Layer nodes (biases * 0) a :- rmbias n
rmbias (O (Layer biases nodes a)) = O $ Layer (biases * 0) nodes a
rmbias ((Layer biases nodes a) :- n) = Layer (biases * 0) nodes a :- rmbias n
run :: (Session -> IO Session)
-> Session -> IO Session