srtree 1.0.0.3 → 1.0.0.4

raw patch · 3 files changed

+5/−116 lines, 3 filesdep −criteriondep ~adPVP ok

version bump matches the API change (PVP)

Dependencies removed: criterion

Dependency ranges changed: ad

API changes (from Hackage documentation)

Files

• ChangeLog.md +4/−0
• app/Main.hs +0/−96
• srtree.cabal +1/−20

@@ -1,5 +1,9 @@ # Changelog for srtree +## 1.0.0.4++- Removed benchmarking code that demanded more dependencies+ ## 1.0.0.3  - Fixed issue with HUnit test

@@ -1,96 +0,0 @@-module Main where--import Data.SRTree-import Data.SRTree.Print-import Data.SRTree.Random-import Data.SRTree.Recursion hiding (fromList)-import Data.Vector (fromList, toList)-import System.Random-import Control.Monad.Reader-import Control.Monad.State-import Criterion.Main-import Numeric.AD.Double ( grad )--autograd t = grad (cata alg t)-  where-      alg (Var ix) = const 0-      alg (Param ix) = \xs -> xs !! ix-      alg (Const v) = const 1.0-      alg (Bin op l r) = \xs -> evalOp op (l xs) (r xs)-      alg (Uni f t) = \xs -> evalFun f (t xs)--xs = fromList [1.0, 2.0 .. 3000.0]-ps = fromList [0.1, 0.2 .. 110.0]--params = P [0,1] (-1.0, 1.0) (-2, 2) [Id] -- , Sin, Cos, Log, Exp]--runRnd g ns p = flip evalStateT g $ traverse (\n -> runReaderT (randomTree n) p) ns-runRndBalance g ns p = flip evalStateT g $ traverse (\n -> runReaderT (randomTreeBalanced n) p) ns--lens :: [Int]-lens = replicate 100 10 <> replicate 100 100 <> replicate 100 1000--g = mkStdGen 42--benchTree f h = do ts <- f g lens params-                   pure $ map (h xs ps id . relabelParams . fst . constsToParam) ts--benchAutodiff f = do ts <- f g lens params-                     let ps' = Data.Vector.toList ps-                     pure $ map ((`autograd` ps') . relabelParams . fst . constsToParam) ts-{--main :: IO ()-main = defaultMain [-       bgroup "unbalanced"-         [ -- bench "forwardMode" $ nfIO (benchTree runRnd forwardMode)-          bench "grad" $ nfIO (benchTree runRnd gradParams)-         , bench "grad2" $ nfIO (benchTree runRnd gradParams2)-         , bench "autodiff" $ nfIO (benchAutodiff runRnd)-         ] ,-       bgroup "balanced"-         [ -- bench "forwardMode" $ nfIO (benchTree runRndBalance forwardMode)-          bench "grad" $ nfIO (benchTree runRndBalance gradParams)-         , bench "grad2" $ nfIO (benchTree runRndBalance gradParams2)-         , bench "autodiff" $ nfIO (benchAutodiff runRndBalance)-         ]-                   ]--}--mkPySRTree :: Int -> Int -> Fix SRTree-mkPySRTree nvar np = relabelParams $ sum [mkWith ix | ix <- [0 .. nvar-1]]-  where-    mkWith ix = fst . (!!(np-1)) $ iterate (\(t, i) -> (cos (t + param i), i+1)) $ (cos (var ix + param 0), 1)--genBalancedTree :: Int -> Fix SRTree-genBalancedTree = relabelParams . go-  where-    go 0 = var 0-    go 1 = cos (var 0 + param 0)-    go n | even n = go (n `div` 2) * (param 0 + go (n `div` 2 - 1))-         | odd n  = cos (param 0 + go (n-1))--sizes = (,) <$> [1] <*> [10, 20 .. 1000]---sizes = (,) <$> [1] <*> [500, 600 .. 2000]---tests = map (\(ix, iy) -> (ix, iy, mkPySRTree ix iy)) sizes-tests = map (\(ix, iy) -> (ix, iy, genBalancedTree iy)) sizes--main :: IO ()-main = defaultMain [-       bgroup ("PySR " <> show ix <> " " <> show iy)-         [ bench "warmup" $ whnf (evalTree xs ps id) t-         -- , bench "forwardMode" $ whnf (sum . forwardMode xs ps id) t-         , bench "grad" $ whnf (sum . snd . gradParamsFwd xs ps id) t-         , bench "grad2" $ whnf (sum . snd . gradParamsRev xs ps id) t-         , bench "autodiff" $ whnf (sum . (`autograd` (Data.Vector.toList ps))) t-         ] | (ix, iy, t) <- tests-                   ]--{--comp (x, xs) (y, ys) = ((x + sum xs) - (y + sum ys))^2--main :: IO ()-main = do -    let g = mkStdGen 42-    trees <- runRndBalance g lens params-    mapM_ (\(t,a,b) -> print (showExpr t, a, b, comp a b)) $ filter (\(t,a,b) -> let c = comp a b in not (isNaN c) && c >= 1e-20) [(t, gradParams xs ps id t, gradParams2 xs ps id t) | t' <- trees, let t = relabelParams (fst $ constsToParam t')] --}

@@ -5,7 +5,7 @@ -- see: https://github.com/sol/hpack  name:           srtree-version:        1.0.0.3+version:        1.0.0.4 synopsis:       A general framework to work with Symbolic Regression expression trees. description:    A Symbolic Regression Tree data structure to work with mathematical expressions with support to first order derivative and simplification; category:       Math, Data, Data Structures@@ -42,25 +42,6 @@     , dlist ==1.0.*     , mtl ==2.2.*     , random ==1.2.*-    , vector >=0.12 && <0.14-  default-language: Haskell2010--executable bench-srtree-  main-is: Main.hs-  other-modules:-      Paths_srtree-  hs-source-dirs:-      app-  ghc-options: -threaded -rtsopts -with-rtsopts=-N -O2 -optc-O3-  build-depends:-      ad >=4.5.0 && <4.6-    , base >=4.16 && <4.18-    , containers ==0.6.*-    , criterion >=1.5.0 && <1.7-    , dlist ==1.0.*-    , mtl ==2.2.*-    , random ==1.2.*-    , srtree     , vector >=0.12 && <0.14   default-language: Haskell2010