50 lines
1.5 KiB
Haskell
50 lines
1.5 KiB
Haskell
module Main where
|
|
import Numeric.Sibe
|
|
import Numeric.LinearAlgebra
|
|
import Data.List
|
|
import Debug.Trace
|
|
import Data.Default.Class
|
|
|
|
main = do
|
|
let alpha = 0.5
|
|
epochs = 1000
|
|
a = (sigmoid, sigmoid')
|
|
rnetwork = randomNetwork 0 (-0.1, 0.1) 4 [(2, a)] (4, a)
|
|
|
|
inputs = [vector [1, 0, 0, 0],
|
|
vector [0, 1, 0, 0],
|
|
vector [0, 0, 1, 0],
|
|
vector [0, 0, 0, 1]]
|
|
|
|
labels = [vector [1, 0, 0, 0],
|
|
vector [0, 1, 0, 0],
|
|
vector [0, 0, 1, 0],
|
|
vector [0, 0, 0, 1]]
|
|
|
|
session = def { network = rnetwork
|
|
, learningRate = 0.5
|
|
, epochs = 1000
|
|
, training = zip inputs labels
|
|
, test = zip inputs labels
|
|
} :: Session
|
|
|
|
let initialCost = crossEntropy session
|
|
|
|
newsession <- run gd session
|
|
|
|
let results = map (`forward` newsession) inputs
|
|
rounded = map (map round . toList) results
|
|
|
|
cost = crossEntropy newsession
|
|
|
|
putStrLn "parameters: "
|
|
putStrLn $ "- inputs: " ++ show inputs
|
|
putStrLn $ "- labels: " ++ show labels
|
|
putStrLn $ "- learning rate: " ++ show alpha
|
|
putStrLn $ "- epochs: " ++ show epochs
|
|
putStrLn $ "- initial cost (cross-entropy): " ++ show initialCost
|
|
putStrLn "results: "
|
|
putStrLn $ "- actual result: " ++ show results
|
|
putStrLn $ "- rounded result: " ++ show rounded
|
|
putStrLn $ "- cost (cross-entropy): " ++ show cost
|