Merge pull request #255 from turion/dev_warnings_as_errors

Warnings as errors
tweag · Feb 10, 2023 · a4d0c92 · a4d0c92
2 parents 06d87a1 + d4ce1c9
commit a4d0c92
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Showing 19 changed files with 23 additions and 43 deletions.
diff --git a/.github/workflows/nix.yml b/.github/workflows/nix.yml
@@ -38,5 +38,5 @@ jobs:
           CACHIX_AUTH_TOKEN: ${{ secrets.CACHIX_AUTH_TOKEN }}
       - name: Build
         run: nix --print-build-logs build .#packages.${{ matrix.system }}.monad-bayes
-      - name: Development environenment
+      - name: Development environment
         run: nix --print-build-logs develop .#packages.${{ matrix.system }}.monad-bayes --command echo Ready
diff --git a/benchmark/Speed.hs b/benchmark/Speed.hs
@@ -4,7 +4,7 @@
 
 module Main (main) where
 
-import Control.Monad.Bayes.Class (MonadDistribution, MonadMeasure)
+import Control.Monad.Bayes.Class (MonadMeasure)
 import Control.Monad.Bayes.Inference.MCMC (MCMCConfig (MCMCConfig, numBurnIn, numMCMCSteps, proposal), Proposal (SingleSiteMH))
 import Control.Monad.Bayes.Inference.RMSMC (rmsmcDynamic)
 import Control.Monad.Bayes.Inference.SMC (SMCConfig (SMCConfig, numParticles, numSteps, resampler), smc)
@@ -27,7 +27,6 @@ import HMM qualified
 import LDA qualified
 import LogReg qualified
 import System.Process.Typed (runProcess)
-import System.Random.Stateful (IOGenM, StatefulGen, StdGen, mkStdGen, newIOGenM)
 
 data ProbProgSys = MonadBayes
   deriving stock (Show)

diff --git a/flake.nix b/flake.nix
@@ -85,7 +85,7 @@
             };
           };
 
-          cabal2nixOptions = "--benchmark";
+          cabal2nixOptions = "--benchmark -fdev";
         };
 
         jupyterEnvironment = mkJupyterlabFromPath ./kernels {inherit pkgs monad-bayes;};

diff --git a/models/LDA.hs b/models/LDA.hs
@@ -15,7 +15,7 @@ import Control.Monad.Bayes.Class
     MonadMeasure,
     factor,
   )
-import Control.Monad.Bayes.Sampler.Strict (sampleIO, sampleIOfixed)
+import Control.Monad.Bayes.Sampler.Strict (sampleIOfixed)
 import Control.Monad.Bayes.Traced (mh)
 import Control.Monad.Bayes.Weighted (unweighted)
 import Data.Map qualified as Map

diff --git a/monad-bayes.cabal b/monad-bayes.cabal
@@ -102,9 +102,9 @@ library
 
   if flag(dev)
     ghc-options:
-      -Wall -Wno-missing-local-signatures -Wno-trustworthy-safe
-      -Wno-missing-import-lists -Wno-implicit-prelude
-      -Wno-monomorphism-restriction
+      -Wall -Werror -Wno-missing-local-signatures -Wno-trustworthy-safe
+      -Wno-missing-import-lists -Wno-implicit-prelude -Wno-name-shadowing
+      -Wno-monomorphism-restriction -Wredundant-constraints
 
   else
     ghc-options: -Wall
@@ -136,7 +136,7 @@ executable example
 
   if flag(dev)
     ghc-options:
-      -Wall -Wcompat -Wincomplete-record-updates
+      -Wall -Werror -Wcompat -Wincomplete-record-updates
       -Wincomplete-uni-patterns -Wnoncanonical-monad-instances
 
   else
@@ -198,7 +198,7 @@ test-suite monad-bayes-test
 
   if flag(dev)
     ghc-options:
-      -Wall -Wno-missing-local-signatures -Wno-unsafe
+      -Wall -Werror -Wno-missing-local-signatures -Wno-unsafe
       -Wno-missing-import-lists -Wno-implicit-prelude
 
   else
@@ -252,7 +252,7 @@ benchmark speed-bench
 
   if flag(dev)
     ghc-options:
-      -Wall -Wno-missing-local-signatures -Wno-unsafe
+      -Wall -Werror -Wno-missing-local-signatures -Wno-unsafe
       -Wno-missing-import-lists -Wno-implicit-prelude
 
   else

diff --git a/src/Control/Monad/Bayes/Inference/MCMC.hs b/src/Control/Monad/Bayes/Inference/MCMC.hs
@@ -44,7 +44,7 @@ mcmcDynamic (MCMCConfig {..}) m = burnIn numBurnIn $ unweighted $ Dynamic.mh num
 
 -- -- | draw iid samples until you get one that has non-zero likelihood
 independentSamples :: Monad m => Static.Traced m a -> P.Producer (MHResult a) m (Trace a)
-independentSamples (Static.Traced w d) =
+independentSamples (Static.Traced _w d) =
   P.repeatM d
     >-> P.takeWhile' ((== 0) . probDensity)
     >-> P.map (MHResult False)

diff --git a/src/Control/Monad/Bayes/Inference/TUI.hs b/src/Control/Monad/Bayes/Inference/TUI.hs
@@ -19,9 +19,8 @@ import Control.Monad.Bayes.Enumerator (toEmpirical)
 import Control.Monad.Bayes.Inference.MCMC
 import Control.Monad.Bayes.Sampler.Strict (SamplerIO, sampleIO)
 import Control.Monad.Bayes.Traced (Traced)
-import Control.Monad.Bayes.Traced.Common
+import Control.Monad.Bayes.Traced.Common hiding (burnIn)
 import Control.Monad.Bayes.Weighted
-import Control.Monad.State.Class (put)
 import Data.Scientific (FPFormat (Exponent), formatScientific, fromFloatDigits)
 import Data.Text qualified as T
 import Data.Text.Lazy qualified as TL

diff --git a/src/Control/Monad/Bayes/Sampler/Lazy.hs b/src/Control/Monad/Bayes/Sampler/Lazy.hs
@@ -6,7 +6,7 @@
 -- | This is a port of the implementation of LazyPPL: https://lazyppl.bitbucket.io/
 module Control.Monad.Bayes.Sampler.Lazy where
 
-import Control.Monad (ap, liftM)
+import Control.Monad (ap)
 import Control.Monad.Bayes.Class (MonadDistribution (random))
 import Control.Monad.Bayes.Weighted (Weighted, weighted)
 import Numeric.Log (Log (..))

diff --git a/src/Control/Monad/Bayes/Sampler/Strict.hs b/src/Control/Monad/Bayes/Sampler/Strict.hs
@@ -77,7 +77,7 @@ instance StatefulGen g m => MonadDistribution (Sampler g m) where
 -- >>> import System.Random.Stateful hiding (random)
 -- >>> newIOGenM (mkStdGen 1729) >>= sampleWith random
 -- 4.690861245089605e-2
-sampleWith :: StatefulGen g m => Sampler g m a -> g -> m a
+sampleWith :: Sampler g m a -> g -> m a
 sampleWith (Sampler m) = runReaderT m
 
 -- | initialize random seed using system entropy, and sample

diff --git a/src/Math/Integrators/StormerVerlet.hs b/src/Math/Integrators/StormerVerlet.hs
@@ -25,7 +25,7 @@ type Integrator a =
 -- | Störmer-Verlet integration scheme for systems of the form
 -- \(\mathbb{H}(p,q) = T(p) + V(q)\)
 stormerVerlet2H ::
-  (Applicative f, Num (f a), Show (f a), Fractional a) =>
+  (Applicative f, Num (f a), Fractional a) =>
   -- | Step size
   a ->
   -- | \(\frac{\partial H}{\partial q}\)

diff --git a/test/TestAdvanced.hs b/test/TestAdvanced.hs
@@ -1,15 +1,7 @@
 module TestAdvanced where
 
-import ConjugatePriors
-  ( betaBernoulli',
-    betaBernoulliAnalytic,
-    gammaNormal',
-    gammaNormalAnalytic,
-    normalNormal',
-    normalNormalAnalytic,
-  )
 import Control.Arrow
-import Control.Monad (join, replicateM)
+import Control.Monad (join)
 import Control.Monad.Bayes.Class
 import Control.Monad.Bayes.Enumerator
 import Control.Monad.Bayes.Inference.MCMC
@@ -19,9 +11,6 @@ import Control.Monad.Bayes.Inference.SMC
 import Control.Monad.Bayes.Inference.SMC2
 import Control.Monad.Bayes.Population
 import Control.Monad.Bayes.Sampler.Strict
-import Control.Monad.Bayes.Traced
-import Control.Monad.Bayes.Weighted
-import Numeric.Log (Log)
 
 mcmcConfig :: MCMCConfig
 mcmcConfig = MCMCConfig {numMCMCSteps = 0, numBurnIn = 0, proposal = SingleSiteMH}

diff --git a/test/TestDistribution.hs b/test/TestDistribution.hs
@@ -9,13 +9,10 @@ module TestDistribution
 where
 
 import Control.Monad (replicateM)
-import Control.Monad.Bayes.Class (MonadDistribution, mvNormal)
+import Control.Monad.Bayes.Class (mvNormal)
 import Control.Monad.Bayes.Sampler.Strict
-import Control.Monad.Identity (runIdentity)
-import Control.Monad.State (evalStateT)
 import Data.Matrix (fromList)
 import Data.Vector qualified as V
-import System.Random.MWC (toSeed)
 
 -- Test the sampled covariance is approximately the same as the
 -- specified covariance.

diff --git a/test/TestInference.hs b/test/TestInference.hs
@@ -20,15 +20,14 @@ import Control.Monad.Bayes.Inference.SMC
 import Control.Monad.Bayes.Integrator (normalize)
 import Control.Monad.Bayes.Integrator qualified as Integrator
 import Control.Monad.Bayes.Population
-import Control.Monad.Bayes.Population (collapse, runPopulation)
 import Control.Monad.Bayes.Sampler.Strict (Sampler, sampleIOfixed)
 import Control.Monad.Bayes.Sampler.Strict qualified as Sampler
 import Control.Monad.Bayes.Weighted (Weighted)
 import Control.Monad.Bayes.Weighted qualified as Weighted
 import Data.AEq (AEq ((~==)))
 import Numeric.Log (Log)
 import Sprinkler (soft)
-import System.Random.Stateful (IOGenM, StdGen, mkStdGen, newIOGenM)
+import System.Random.Stateful (IOGenM, StdGen)
 
 sprinkler :: MonadMeasure m => m Bool
 sprinkler = Sprinkler.soft

diff --git a/test/TestIntegrator.hs b/test/TestIntegrator.hs
@@ -14,7 +14,7 @@ import Control.Monad.Bayes.Class
 import Control.Monad.Bayes.Integrator
 import Control.Monad.Bayes.Sampler.Strict
 import Control.Monad.Bayes.Weighted (weighted)
-import Control.Monad.ST (ST, runST)
+import Control.Monad.ST (runST)
 import Data.AEq (AEq ((~==)))
 import Data.List (sortOn)
 import Data.Set (fromList)

diff --git a/test/TestPipes.hs b/test/TestPipes.hs
@@ -7,9 +7,7 @@ import Control.Monad.Bayes.Class ()
 import Control.Monad.Bayes.Enumerator (enumerator)
 import Data.AEq (AEq ((~==)))
 import HMM (hmm, hmmPosterior)
-import Pipes ((>->))
 import Pipes.Prelude (toListM)
-import qualified Pipes.Prelude as Pipes
 
 urns :: Int -> Bool
 urns n = enumerator (urn n) ~== enumerator (urnP n)

diff --git a/test/TestPopulation.hs b/test/TestPopulation.hs
@@ -14,7 +14,6 @@ import Control.Monad.Bayes.Population as Population
 import Control.Monad.Bayes.Sampler.Strict (sampleIOfixed)
 import Data.AEq (AEq ((~==)))
 import Sprinkler (soft)
-import System.Random.Stateful (mkStdGen, newIOGenM)
 
 weightedSampleSize :: MonadDistribution m => Population m a -> m Int
 weightedSampleSize = fmap length . population

diff --git a/test/TestSampler.hs b/test/TestSampler.hs
@@ -4,7 +4,7 @@ import qualified Control.Foldl as Fold
 import Control.Monad (replicateM)
 import Control.Monad.Bayes.Class (MonadDistribution (normal))
 import Control.Monad.Bayes.Sampler.Strict (sampleSTfixed)
-import Control.Monad.ST (ST, runST)
+import Control.Monad.ST (runST)
 
 testMeanAndVariance :: Bool
 testMeanAndVariance = isDiff

diff --git a/test/TestStormerVerlet.hs b/test/TestStormerVerlet.hs
@@ -10,6 +10,7 @@ import qualified Data.Vector as V
 import qualified Linear as L
 import Linear.V
 import Math.Integrators.StormerVerlet
+import Statistics.Function (square)
 
 gConst :: Double
 gConst = 6.67384e-11
@@ -81,8 +82,8 @@ energy x = keJ + keS + peJ + peS
     qS = qs ^. _2
     pJ = ps ^. _1
     pS = ps ^. _2
-    keJ = (* 0.5) $ (/ jupiterMass) $ sum $ fmap (^ 2) pJ
-    keS = (* 0.5) $ (/ sunMass) $ sum $ fmap (^ 2) pS
+    keJ = (* 0.5) $ (/ jupiterMass) $ sum $ fmap square pJ
+    keS = (* 0.5) $ (/ sunMass) $ sum $ fmap square pS
     r = qJ L.^-^ qS
     ri = r `L.dot` r
     peJ = 0.5 * gConst * sunMass * jupiterMass / (sqrt ri)

diff --git a/test/TestWeighted.hs b/test/TestWeighted.hs
@@ -13,7 +13,6 @@ import Control.Monad.State (unless, when)
 import Data.AEq (AEq ((~==)))
 import Data.Bifunctor (second)
 import Numeric.Log (Log (Exp, ln))
-import System.Random.Stateful (mkStdGen, newIOGenM)
 
 model :: MonadMeasure m => m (Int, Double)
 model = do
-Original file line number
+Diff line change
@@ Expand Up / @@ -85,7 +85,7 @@ @@
                 };
               };
-              cabal2nixOptions = "--benchmark";
+              cabal2nixOptions = "--benchmark -fdev";
             };
             jupyterEnvironment = mkJupyterlabFromPath ./kernels {inherit pkgs monad-bayes;};
@@ Expand Down @@