Merge pull request #42 from tpapp/dw/error_hints

Add error hints

Author: tpapp

Project.toml

@@ -1,7 +1,7 @@
 name = "LogDensityProblemsAD"
 uuid = "996a588d-648d-4e1f-a8f0-a84b347e47b1"
 authors = ["Tamás K. Papp <[email protected]>"]
-version = "1.12.0"
+version = "1.13.0"
 
 [deps]
 DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"

ext/LogDensityProblemsADADTypesExt.jl

@@ -68,4 +68,15 @@ function LogDensityProblemsAD.ADgradient(::ADTypes.AutoZygote, ℓ; x::Union{Not
     return LogDensityProblemsAD.ADgradient(Val(:Zygote), ℓ)
 end
 
+# Better error message if users forget to load DifferentiationInterface
+if isdefined(Base.Experimental, :register_error_hint)
+    function __init__()
+        Base.Experimental.register_error_hint(MethodError) do io, exc, argtypes, _
+            if exc.f === LogDensityProblemsAD.ADgradient && length(argtypes) == 2 && first(argtypes) <: ADTypes.AbstractADType
+                print(io, "\nDon't know how to AD with $(nameof(first(argtypes))). Did you forget to load DifferentiationInterface?")
+            end
+        end
+    end
+end
+
 end # module

src/LogDensityProblemsAD.jl

@@ -63,9 +63,17 @@ The function `parent` can be used to retrieve the original argument.
 """
 ADgradient(kind::Symbol, P; kwargs...) = ADgradient(Val{kind}(), P; kwargs...)
 
-function ADgradient(v::Val{kind}, P; kwargs...) where kind
-    @info "Don't know how to AD with $(kind), consider `import $(kind)` if there is such a package."
-    throw(MethodError(ADgradient, (v, P)))
+# Better error message if users forget to load the AD package
+if isdefined(Base.Experimental, :register_error_hint)
+    _unval(::Type{Val{T}}) where {T} = T
+    function __init__()
+        Base.Experimental.register_error_hint(MethodError) do io, exc, argtypes, _
+            if exc.f === ADgradient && length(argtypes) == 2 && first(argtypes) <: Val
+                kind = _unval(first(argtypes))
+                print(io, "\nDon't know how to AD with $(kind), consider `import $(kind)` if there is such a package.")
+            end
+        end
+    end
 end
 
 #####

test/runtests.jl

@@ -6,7 +6,6 @@ import FiniteDifferences, ForwardDiff, Enzyme, Tracker, Zygote, ReverseDiff # ba
 import ADTypes # load support for AD types with options
 import BenchmarkTools                            # load the heuristic chunks code
 using ComponentArrays: ComponentVector           # test with other vector types
-import DifferentiationInterface
 
 struct EnzymeTestMode <: Enzyme.Mode{Enzyme.DefaultABI, false, false} end
 
@@ -71,6 +70,15 @@ struct TestTag end
 # Allow tag type in gradient etc. calls of the log density function
 ForwardDiff.checktag(::Type{ForwardDiff.Tag{TestTag, V}}, ::Base.Fix1{typeof(logdensity),typeof(TestLogDensity())}, ::AbstractArray{V}) where {V} = true
 
+@testset "Missing DI for unsupported ADType" begin
+    msg = "Don't know how to AD with AutoFiniteDifferences. Did you forget to load DifferentiationInterface?"
+    adtype = ADTypes.AutoFiniteDifferences(; fdm=FiniteDifferences.central_fdm(5, 1))
+    @test_throws msg ADgradient(adtype, TestLogDensity2())
+    @test_throws msg ADgradient(adtype, TestLogDensity2(); x=zeros(20))
+end
+
+import DifferentiationInterface
+
 @testset "AD via ReverseDiff" begin
     ℓ = TestLogDensity()
 
@@ -296,7 +304,10 @@ end
 
 @testset "ADgradient missing method" begin
     msg = "Don't know how to AD with Foo, consider `import Foo` if there is such a package."
-    @test_logs((:info, msg), @test_throws(MethodError, ADgradient(:Foo, TestLogDensity2())))
+    @test_throws msg ADgradient(:Foo, TestLogDensity2())
+    @test_throws msg ADgradient(:Foo, TestLogDensity2(); x=zeros(20))
+    @test_throws msg ADgradient(Val(:Foo), TestLogDensity2())
+    @test_throws msg ADgradient(Val(:Foo), TestLogDensity2(); x=zeros(20))
 end
 
 @testset "benchmark ForwardDiff chunk size" begin