Add Aqua tests (#395)

* Add Aqua tests

* Use ReTest

* Remove InplaceOps

* Fix ambiguities

* Fix format

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

---------

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

Author: devmotion

Project.toml

@@ -6,7 +6,6 @@ version = "0.6.4"
 AbstractMCMC = "80f14c24-f653-4e6a-9b94-39d6b0f70001"
 ArgCheck = "dce04be8-c92d-5529-be00-80e4d2c0e197"
 DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
-InplaceOps = "505f98c9-085e-5b2c-8e89-488be7bf1f34"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 LogDensityProblems = "6fdf6af0-433a-55f7-b3ed-c6c6e0b8df7c"
 LogDensityProblemsAD = "996a588d-648d-4e1f-a8f0-a84b347e47b1"
@@ -34,7 +33,6 @@ AbstractMCMC = "5.6"
 ArgCheck = "1, 2"
 CUDA = "3, 4, 5"
 DocStringExtensions = "0.8, 0.9"
-InplaceOps = "0.3"
 LogDensityProblems = "2"
 LogDensityProblemsAD = "1"
 MCMCChains = "5, 6"

README.md

@@ -5,6 +5,7 @@
 [![Coverage Status](https://coveralls.io/repos/github/TuringLang/AdvancedHMC.jl/badge.svg?branch=kx%2Fbug-fix)](https://coveralls.io/github/TuringLang/AdvancedHMC.jl?branch=kx%2Fbug-fix)
 [![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://turinglang.github.io/AdvancedHMC.jl/stable/)
 [![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://turinglang.github.io/AdvancedHMC.jl/dev/)
+[![Aqua QA](https://raw.githubusercontent.com/JuliaTesting/Aqua.jl/master/badge.svg)](https://github.com/JuliaTesting/Aqua.jl)
 
 AdvancedHMC.jl provides a robust, modular, and efficient implementation of advanced HMC algorithms. An illustrative example of AdvancedHMC's usage is given below. AdvancedHMC.jl is part of [Turing.jl](https://github.com/TuringLang/Turing.jl), a probabilistic programming library in Julia. 
 If you are interested in using AdvancedHMC.jl through a probabilistic programming language, please check it out!

src/AdvancedHMC.jl

@@ -163,17 +163,19 @@ function Hamiltonian(
 )
     return Hamiltonian(metric, ℓπ.logdensity, kind; kwargs...)
 end
-Hamiltonian(metric::AbstractMetric, ℓπ, m::Module; kwargs...) =
-    Hamiltonian(metric, ℓπ, Val(Symbol(m)); kwargs...)
-function Hamiltonian(metric::AbstractMetric, ℓπ, kind::Union{Symbol,Val}; kwargs...)
+function Hamiltonian(metric::AbstractMetric, ℓπ, kind::Union{Symbol,Val,Module}; kwargs...)
     if LogDensityProblems.capabilities(ℓπ) === nothing
         throw(
             ArgumentError(
                 "The log density function does not support the LogDensityProblems.jl interface",
             ),
         )
     end
-    ℓ = LogDensityProblemsAD.ADgradient(kind, ℓπ; kwargs...)
+    ℓ = LogDensityProblemsAD.ADgradient(
+        kind isa Val ? kind : Val(Symbol(kind)),
+        ℓπ;
+        kwargs...,
+    )
     return Hamiltonian(metric, ℓ)
 end
 

test/Project.toml

@@ -1,5 +1,6 @@
 [deps]
 AbstractMCMC = "80f14c24-f653-4e6a-9b94-39d6b0f70001"
+Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 Bijectors = "76274a88-744f-5084-9051-94815aaf08c4"
 CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
 Comonicon = "863f3e99-da2a-4334-8734-de3dacbe5542"

test/aqua.jl

@@ -0,0 +1,7 @@
+using AdvancedHMC
+using ReTest
+import Aqua
+
+@testset "Aqua" begin
+    Aqua.test_all(AdvancedHMC)
+end

test/runtests.jl

@@ -3,6 +3,8 @@ using FillArrays
 using AdvancedHMC: AdvancedHMC
 using LogDensityProblems: LogDensityProblems
 using LogDensityProblemsAD: LogDensityProblemsAD
+using MCMCChains
+using OrdinaryDiffEq
 using ReTest
 
 println("Environment variables for testing")
@@ -17,6 +19,7 @@ include("common.jl")
 if GROUP == "All" || GROUP == "AdvancedHMC"
     using ReTest, CUDA
 
+    include("aqua.jl")
     include("metric.jl")
     include("hamiltonian.jl")
     include("integrator.jl")