Merge branch 'master' into dw/enzyme

test/mcmc/hmc.jl

@@ -1,6 +1,7 @@
 module HMCTests
 
 using ..Models: gdemo_default
+using ..ADUtils: ADTypeCheckContext
 #using ..Models: gdemo
 using ..NumericalTests: check_gdemo, check_numerical
 using Distributions: Bernoulli, Beta, Categorical, Dirichlet, Normal, Wishart, sample
@@ -328,6 +329,15 @@ Enzyme.API.runtimeActivity!(true)
         # KS will compare the empirical CDFs, which seems like a reasonable thing to do here.
         @test pvalue(ApproximateTwoSampleKSTest(vec(results), vec(results_prior))) > 0.001
     end
+
+    @testset "Check ADType" begin
+        alg = HMC(0.1, 10; adtype=adbackend)
+        m = DynamicPPL.contextualize(
+            gdemo_default, ADTypeCheckContext(adbackend, gdemo_default.context)
+        )
+        # These will error if the adbackend being used is not the one set.
+        sample(rng, m, alg, 10)
+    end
 end
 
 end

test/optimisation/Optimisation.jl

@@ -1,6 +1,7 @@
 module OptimisationTests
 
 using ..Models: gdemo, gdemo_default
+using ..ADUtils: ADTypeCheckContext
 using Distributions
 using Distributions.FillArrays: Zeros
 using DynamicPPL: DynamicPPL
@@ -140,7 +141,6 @@ using Turing
                 gdemo_default, OptimizationOptimJL.LBFGS(); initial_params=true_value
             )
             m3 = maximum_likelihood(gdemo_default, OptimizationOptimJL.Newton())
-            # TODO(mhauru) How can we check that the adtype is actually AutoReverseDiff?
             m4 = maximum_likelihood(
                 gdemo_default, OptimizationOptimJL.BFGS(); adtype=AutoReverseDiff()
             )
@@ -616,6 +616,18 @@ using Turing
         @assert vcat(get_a[:a], get_b[:b]) == result.values.array
         @assert get(result, :c) == (; :c => Array{Float64}[])
     end
+
+    @testset "ADType" begin
+        Random.seed!(222)
+        for adbackend in (AutoReverseDiff(), AutoForwardDiff(), AutoTracker())
+            m = DynamicPPL.contextualize(
+                gdemo_default, ADTypeCheckContext(adbackend, gdemo_default.context)
+            )
+            # These will error if the adbackend being used is not the one set.
+            maximum_likelihood(m; adtype=adbackend)
+            maximum_a_posteriori(m; adtype=adbackend)
+        end
+    end
 end
 
 end

test/runtests.jl

@@ -7,6 +7,7 @@ import Turing
 
 include(pkgdir(Turing) * "/test/test_utils/models.jl")
 include(pkgdir(Turing) * "/test/test_utils/numerical_tests.jl")
+include(pkgdir(Turing) * "/test/test_utils/ad_utils.jl")
 
 Turing.setprogress!(false)
 

test/test_utils/ad_utils.jl

@@ -0,0 +1,273 @@
+module ADUtils
+
+using ForwardDiff: ForwardDiff
+using Random: Random
+using ReverseDiff: ReverseDiff
+using Test: Test
+using Tracker: Tracker
+using Turing: Turing
+using Turing: DynamicPPL
+using Zygote: Zygote
+
+export ADTypeCheckContext
+
+"""Element types that are always valid for a VarInfo regardless of ADType."""
+const always_valid_eltypes = (AbstractFloat, AbstractIrrational, Integer, Rational)
+
+"""A dictionary mapping ADTypes to the element types they use."""
+const eltypes_by_adtype = Dict(
+    Turing.AutoForwardDiff => (ForwardDiff.Dual,),
+    Turing.AutoReverseDiff => (
+        ReverseDiff.TrackedArray,
+        ReverseDiff.TrackedMatrix,
+        ReverseDiff.TrackedReal,
+        ReverseDiff.TrackedStyle,
+        ReverseDiff.TrackedType,
+        ReverseDiff.TrackedVecOrMat,
+        ReverseDiff.TrackedVector,
+    ),
+    # Zygote.Dual is actually the same as ForwardDiff.Dual, so can't distinguish between the
+    # two by element type. However, we have other checks for Zygote, see check_adtype.
+    Turing.AutoZygote => (Zygote.Dual,),
+    Turing.AutoTracker => (
+        Tracker.Tracked,
+        Tracker.TrackedArray,
+        Tracker.TrackedMatrix,
+        Tracker.TrackedReal,
+        Tracker.TrackedStyle,
+        Tracker.TrackedVecOrMat,
+        Tracker.TrackedVector,
+    ),
+)
+
+"""
+    AbstractWrongADBackendError
+
+An abstract error thrown when we seem to be using a different AD backend than expected.
+"""
+abstract type AbstractWrongADBackendError <: Exception end
+
+"""
+    WrongADBackendError
+
+An error thrown when we seem to be using a different AD backend than expected.
+"""
+struct WrongADBackendError <: AbstractWrongADBackendError
+    actual_adtype::Type
+    expected_adtype::Type
+end
+
+function Base.showerror(io::IO, e::WrongADBackendError)
+    return print(
+        io, "Expected to use $(e.expected_adtype), but using $(e.actual_adtype) instead."
+    )
+end
+
+"""
+    IncompatibleADTypeError
+
+An error thrown when an element type is encountered that is unexpected for the given ADType.
+"""
+struct IncompatibleADTypeError <: AbstractWrongADBackendError
+    valtype::Type
+    adtype::Type
+end
+
+function Base.showerror(io::IO, e::IncompatibleADTypeError)
+    return print(
+        io,
+        "Incompatible ADType: Did not expect element of type $(e.valtype) with $(e.adtype)",
+    )
+end
+
+"""
+    ADTypeCheckContext{ADType,ChildContext}
+
+A context for checking that the expected ADType is being used.
+
+Evaluating a model with this context will check that the types of values in a `VarInfo` are
+compatible with the ADType of the context. If the check fails, an `IncompatibleADTypeError`
+is thrown.
+
+For instance, evaluating a model with
+`ADTypeCheckContext(AutoForwardDiff(), child_context)`
+would throw an error if within the model a type associated with e.g. ReverseDiff was
+encountered.
+
+As a current short-coming, this context can not distinguish between ForwardDiff and Zygote.
+"""
+struct ADTypeCheckContext{ADType,ChildContext<:DynamicPPL.AbstractContext} <:
+       DynamicPPL.AbstractContext
+    child::ChildContext
+
+    function ADTypeCheckContext(adbackend, child)
+        adtype = adbackend isa Type ? adbackend : typeof(adbackend)
+        if !any(adtype <: k for k in keys(eltypes_by_adtype))
+            throw(ArgumentError("Unsupported ADType: $adtype"))
+        end
+        return new{adtype,typeof(child)}(child)
+    end
+end
+
+adtype(_::ADTypeCheckContext{ADType}) where {ADType} = ADType
+
+DynamicPPL.NodeTrait(::ADTypeCheckContext) = DynamicPPL.IsParent()
+DynamicPPL.childcontext(c::ADTypeCheckContext) = c.child
+function DynamicPPL.setchildcontext(c::ADTypeCheckContext, child)
+    return ADTypeCheckContext(adtype(c), child)
+end
+
+"""
+    valid_eltypes(context::ADTypeCheckContext)
+
+Return the element types that are valid for the ADType of `context` as a tuple.
+"""
+function valid_eltypes(context::ADTypeCheckContext)
+    context_at = adtype(context)
+    for at in keys(eltypes_by_adtype)
+        if context_at <: at
+            return (eltypes_by_adtype[at]..., always_valid_eltypes...)
+        end
+    end
+    # This should never be reached due to the check in the inner constructor.
+    throw(ArgumentError("Unsupported ADType: $(adtype(context))"))
+end
+
+"""
+    check_adtype(context::ADTypeCheckContext, vi::DynamicPPL.VarInfo)
+
+Check that the element types in `vi` are compatible with the ADType of `context`.
+
+When Zygote is being used, we also more explicitly check that `adtype(context)` is
+`AutoZygote`. This is because Zygote uses the same element type as ForwardDiff, so we can't
+discriminate between the two based on element type alone. This function will still fail to
+catch cases where Zygote is supposed to be used, but ForwardDiff is used instead.
+
+Throw an `IncompatibleADTypeError` if an incompatible element type is encountered, or
+`WrongADBackendError` if Zygote is used unexpectedly.
+"""
+function check_adtype(context::ADTypeCheckContext, vi::DynamicPPL.AbstractVarInfo)
+    Zygote.hook(vi) do _
+        if !(adtype(context) <: Turing.AutoZygote)
+            throw(WrongADBackendError(Turing.AutoZygote, adtype(context)))
+        end
+    end
+
+    valids = valid_eltypes(context)
+    for val in vi[:]
+        valtype = typeof(val)
+        if !any(valtype .<: valids)
+            throw(IncompatibleADTypeError(valtype, adtype(context)))
+        end
+    end
+    return nothing
+end
+
+# A bunch of tilde_assume/tilde_observe methods that just call the same method on the child
+# context, and then call check_adtype on the result before returning the results from the
+# child context.
+
+function DynamicPPL.tilde_assume(context::ADTypeCheckContext, right, vn, vi)
+    value, logp, vi = DynamicPPL.tilde_assume(
+        DynamicPPL.childcontext(context), right, vn, vi
+    )
+    check_adtype(context, vi)
+    return value, logp, vi
+end
+
+function DynamicPPL.tilde_assume(
+    rng::Random.AbstractRNG, context::ADTypeCheckContext, sampler, right, vn, vi
+)
+    value, logp, vi = DynamicPPL.tilde_assume(
+        rng, DynamicPPL.childcontext(context), sampler, right, vn, vi
+    )
+    check_adtype(context, vi)
+    return value, logp, vi
+end
+
+function DynamicPPL.tilde_observe(context::ADTypeCheckContext, right, left, vi)
+    logp, vi = DynamicPPL.tilde_observe(DynamicPPL.childcontext(context), right, left, vi)
+    check_adtype(context, vi)
+    return logp, vi
+end
+
+function DynamicPPL.tilde_observe(context::ADTypeCheckContext, sampler, right, left, vi)
+    logp, vi = DynamicPPL.tilde_observe(
+        DynamicPPL.childcontext(context), sampler, right, left, vi
+    )
+    check_adtype(context, vi)
+    return logp, vi
+end
+
+function DynamicPPL.dot_tilde_assume(context::ADTypeCheckContext, right, left, vn, vi)
+    value, logp, vi = DynamicPPL.dot_tilde_assume(
+        DynamicPPL.childcontext(context), right, left, vn, vi
+    )
+    check_adtype(context, vi)
+    return value, logp, vi
+end
+
+function DynamicPPL.dot_tilde_assume(
+    rng::Random.AbstractRNG, context::ADTypeCheckContext, sampler, right, left, vn, vi
+)
+    value, logp, vi = DynamicPPL.dot_tilde_assume(
+        rng, DynamicPPL.childcontext(context), sampler, right, left, vn, vi
+    )
+    check_adtype(context, vi)
+    return value, logp, vi
+end
+
+function DynamicPPL.dot_tilde_observe(context::ADTypeCheckContext, right, left, vi)
+    logp, vi = DynamicPPL.dot_tilde_observe(
+        DynamicPPL.childcontext(context), right, left, vi
+    )
+    check_adtype(context, vi)
+    return logp, vi
+end
+
+function DynamicPPL.dot_tilde_observe(context::ADTypeCheckContext, sampler, right, left, vi)
+    logp, vi = DynamicPPL.dot_tilde_observe(
+        DynamicPPL.childcontext(context), sampler, right, left, vi
+    )
+    check_adtype(context, vi)
+    return logp, vi
+end
+
+# Check that the ADTypeCheckContext works as expected.
+Test.@testset "ADTypeCheckContext" begin
+    Turing.@model test_model() = x ~ Turing.Normal(0, 1)
+    tm = test_model()
+    adtypes = (
+        Turing.AutoForwardDiff(),
+        Turing.AutoReverseDiff(),
+        Turing.AutoZygote(),
+        Turing.AutoTracker(),
+    )
+    for actual_adtype in adtypes
+        sampler = Turing.HMC(0.1, 5; adtype=actual_adtype)
+        for expected_adtype in adtypes
+            if (
+                actual_adtype == Turing.AutoForwardDiff() &&
+                expected_adtype == Turing.AutoZygote()
+            )
+                # TODO(mhauru) We are currently unable to check this case.
+                continue
+            end
+            contextualised_tm = DynamicPPL.contextualize(
+                tm, ADTypeCheckContext(expected_adtype, tm.context)
+            )
+            Test.@testset "Expected: $expected_adtype, Actual: $actual_adtype" begin
+                if actual_adtype == expected_adtype
+                    # Check that this does not throw an error.
+                    Turing.sample(contextualised_tm, sampler, 2)
+                else
+                    Test.@test_throws AbstractWrongADBackendError Turing.sample(
+                        contextualised_tm, sampler, 2
+                    )
+                end
+            end
+        end
+    end
+end
+
+end