Auto compile Lux models to reactant

Project.toml

@@ -1,7 +1,7 @@
 name = "Lux"
 uuid = "b2108857-7c20-44ae-9111-449ecde12c47"
 authors = ["Avik Pal <[email protected]> and contributors"]
-version = "0.5.51"
+version = "0.5.52"
 
 [deps]
 ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
@@ -40,6 +40,7 @@ MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
 MPI = "da04e1cc-30fd-572f-bb4f-1f8673147195"
 NCCL = "3fe64909-d7a1-4096-9b7d-7a0f12cf0f6b"
 Optimisers = "3bd65402-5787-11e9-1adc-39752487f4e2"
+Reactant = "3c362404-f566-11ee-1572-e11a4b42c853"
 ReverseDiff = "37e2e3b7-166d-5795-8a7a-e32c996b4267"
 SimpleChains = "de6bee2f-e2f4-4ec7-b6ed-219cc6f6e9e5"
 Tracker = "9f7883ad-71c0-57eb-9f7f-b5c9e6d3789c"
@@ -57,6 +58,7 @@ LuxMLUtilsExt = "MLUtils"
 LuxMPIExt = "MPI"
 LuxMPINCCLExt = ["CUDA", "MPI", "NCCL"]
 LuxOptimisersExt = "Optimisers"
+LuxReactantExt = "Reactant"
 LuxReverseDiffExt = "ReverseDiff"
 LuxSimpleChainsExt = "SimpleChains"
 LuxTrackerExt = "Tracker"
@@ -102,6 +104,7 @@ Pkg = "1.10"
 PrecompileTools = "1.2"
 Preferences = "1.4.3"
 Random = "1.10"
+Reactant = "0.1.1"
 ReTestItems = "1.23.1"
 Reexport = "1.2.2"
 ReverseDiff = "1.15"

ext/LuxReactantExt.jl

@@ -0,0 +1,48 @@
+module LuxReactantExt
+
+using ArgCheck: @argcheck
+using Random: AbstractRNG, Xoshiro
+using Reactant: Reactant
+using Lux: Lux
+using LuxCore: LuxCore, AbstractExplicitLayer
+
+@inline __make_concrete_array(x::Reactant.ConcreteRArray) = x
+@inline __make_concrete_array(x::AbstractArray) = Reactant.ConcreteRArray(x)
+@inline function __make_concrete_array(x)
+    return Reactant.make_tracer(IdDict(), x, (), Reactant.ArrayToConcrete, nothing)
+end
+
+# FIXME: currently only `stateless_apply` is supported: https://github.com/EnzymeAD/Reactant.jl/issues/8
+function Lux.__to_reactant_adaptor(model::AbstractExplicitLayer, input_prototype)
+    concrete_input = __make_concrete_array(input_prototype)
+    cmodel = __make_concrete_array(model)
+    # We generate fake parameters and states to compile the model
+    ps = LuxCore.initialparameters(Xoshiro(123), model)
+    cps = __make_concrete_array(ps)
+
+    st = LuxCore.initialstates(Xoshiro(123), model)
+    @argcheck st==LuxCore._getemptystate(model) "Currently only stateless models are supported."
+
+    fwd = Reactant.compile(
+        (m, x, ps) -> LuxCore.stateless_apply(m, x, ps), (cmodel, concrete_input, cps))
+
+    # TODO: conditionally compile the backward pass
+
+    return Lux.ReactantLayer(model, cmodel, fwd, nothing)
+end
+
+function LuxCore.initialparameters(rng::AbstractRNG, layer::Lux.ReactantLayer)
+    return __make_concrete_array(LuxCore.initialparameters(rng, layer.layer))
+end
+
+# FIXME: Change once https://github.com/EnzymeAD/Reactant.jl/pull/8 is fixed
+function LuxCore.initialstates(::AbstractRNG, layer::Lux.ReactantLayer)
+    return NamedTuple() # __make_concrete_array(LuxCore.initialstates(rng, layer.layer))
+end
+
+# TODO: Add a type assert here to make it type stable
+function (l::Lux.ReactantLayer)(x, ps, ::NamedTuple{()})
+    return LuxCore.stateless_apply(l.clayer, __make_concrete_array(x), ps), NamedTuple()
+end
+
+end

src/Lux.jl

@@ -76,6 +76,7 @@ include("helpers/nested_ad.jl")
 include("transform/types.jl")
 include("transform/flux.jl")
 include("transform/simplechains.jl")
+include("transform/reactant.jl")
 
 # Distributed Training
 include("distributed/backend.jl")
@@ -110,6 +111,7 @@ export f16, f32, f64
 export transform
 export FromFluxAdaptor, FluxLayer
 export ToSimpleChainsAdaptor, SimpleChainsLayer
+export ToReactantAdaptor
 export DynamicExpressionsLayer
 
 export MPIBackend, NCCLBackend, DistributedUtils

src/layers/extension.jl

@@ -242,3 +242,12 @@ function CRC.rrule(::typeof(__apply_simple_chain), layer, x, ps, ::LuxCPUDevice)
     end
     return res, __∇apply_simple_chain
 end
+
+# TODO: Add a ChainRules rrule that calls the `bwd` function, i.e. uses Enzyme for the
+#       gradient computation
+@concrete struct ReactantLayer{F, B, L <: AbstractExplicitLayer} <: AbstractExplicitLayer
+    layer::L
+    clayer
+    fwd::F
+    bwd::B
+end

src/transform/reactant.jl

@@ -0,0 +1,13 @@
+# TODO: Add options to compile the gradients directly using Enzyme.jl
+@concrete struct ToReactantAdaptor <: AbstractFromLuxAdaptor
+    input_prototype
+end
+
+function Adapt.adapt(to::ToReactantAdaptor, model::AbstractExplicitLayer)
+    if Base.get_extension(@__MODULE__, :LuxReactantExt) === nothing
+        error("`ToReactantAdaptor` requires `LuxReactantExt.jl` to be loaded.")
+    end
+    return __to_reactant_adaptor(model, to.input_prototype)
+end
+
+function __to_reactant_adaptor end