feat: tracing Random.jl functionality correctly

.github/workflows/CI.yml

@@ -50,6 +50,12 @@ jobs:
             version: '1.10'
             assertions: true
             test_group: neural_networks
+          - os: ubuntu-20.04
+            arch: x64
+            libReactant: packaged
+            version: '1.10'
+            assertions: true
+            test_group: integration
           - os: ubuntu-20.04
             arch: x86
             libReactant: packaged

Project.toml

@@ -14,6 +14,7 @@ Libdl = "8f399da3-3557-5675-b5ff-fb832c97cbdb"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 OrderedCollections = "bac558e1-5e72-5ebc-8fee-abe8a469f55d"
 Preferences = "21216c6a-2e73-6563-6e65-726566657250"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 ReactantCore = "a3311ec8-5e00-46d5-b541-4f83e724a433"
 Reactant_jll = "0192cb87-2b54-54ad-80e0-3be72ad8a3c0"
 Scratch = "6c6a2e73-6563-6170-7368-637461726353"
@@ -23,17 +24,19 @@ AbstractFFTs = "621f4979-c628-5d54-868e-fcf4e3e8185c"
 ArrayInterface = "4fba245c-0d91-5ea0-9b3e-6abc04ee57a9"
 CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
 NNlib = "872c559c-99b0-510c-b3b7-b6c96a88d5cd"
+Random123 = "74087812-796a-5b5d-8853-05524746bad3"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 YaoBlocks = "418bc28f-b43b-5e0b-a6e7-61bbc1a2c1df"
 
-[sources.ReactantCore]
-path = "lib/ReactantCore"
+[sources]
+ReactantCore = {path = "lib/ReactantCore"}
 
 [extensions]
 ReactantAbstractFFTsExt = "AbstractFFTs"
 ReactantArrayInterfaceExt = "ArrayInterface"
 ReactantCUDAExt = "CUDA"
 ReactantNNlibExt = "NNlib"
+ReactantRandom123Ext = "Random123"
 ReactantStatisticsExt = "Statistics"
 ReactantYaoBlocksExt = "YaoBlocks"
 
@@ -50,6 +53,8 @@ LinearAlgebra = "1.10"
 NNlib = "0.9.26"
 OrderedCollections = "1"
 Preferences = "1.4"
+Random = "1.10"
+Random123 = "1.7"
 ReactantCore = "0.1.3"
 Reactant_jll = "0.0.26"
 Scratch = "1.2"

docs/make.jl

@@ -43,6 +43,7 @@ pages = [
         ],
         "MLIR API" => "api/mlirc.md",
         "XLA" => "api/xla.md",
+        "Internal API" => "api/internal.md",
     ],
 ]
 

docs/src/.vitepress/config.mts

@@ -78,7 +78,8 @@ export default defineConfig({
               { text: "MLIR API", link: "/api/mlirc" },
               { text: "XLA", link: "/api/xla" },
             ],
-          }
+          },
+          { text: "Internal API", link: "/api/internal" },
         ],
       },
       {
@@ -132,6 +133,7 @@ export default defineConfig({
               { text: "XLA", link: "/api/xla" },
             ],
           },
+          { text: "Internal API", link: "/api/internal" },
         ],
       },
     },

docs/src/api/internal.md

@@ -0,0 +1,12 @@
+```@meta
+CollapsedDocStrings = true
+```
+
+# Internal API
+
+These functions are not part of the public API and are subject to change at any time.
+
+```@docs
+Reactant.REDUB_ARGUMENTS_NAME
+Reactant.within_reactant_interpreter
+```

ext/ReactantRandom123Ext.jl

@@ -0,0 +1,11 @@
+module ReactantRandom123Ext
+
+using Random123: Threefry4x, Threefry2x, Philox4x, Philox2x
+using Reactant: TracedRandom
+
+TracedRandom.rng_algorithm(::Threefry4x) = "THREE_FRY"
+TracedRandom.rng_algorithm(::Threefry2x) = "THREE_FRY"
+TracedRandom.rng_algorithm(::Philox4x) = "PHILOX"
+TracedRandom.rng_algorithm(::Philox2x) = "PHILOX"
+
+end

src/Ops.jl

@@ -1016,19 +1016,150 @@ end
 end
 
 # random ops
+"""
+    rng_bit_generator(
+        ::Type{T},
+        seed::TracedRArray{UInt64,1},
+        shape;
+        algorithm::String="DEFAULT",
+        location=mlir_stacktrace("rand", @__FILE__, @__LINE__),
+    )
+
+Generate a random array of type `T` with the given shape and seed from a uniform random
+distribution between 0 and 1. Returns a NamedTuple with the following fields:
+
+- `output_state`: The state of the random number generator after the operation.
+- `output`: The generated array.
+
+# Arguments
+
+- `T`: The type of the generated array.
+- `seed`: The seed for the random number generator.
+- `shape`: The shape of the generated array.
+- `algorithm`: The algorithm to use for generating the random numbers. Defaults to
+  "DEFAULT". Other options include "PHILOX" and "THREE_FRY".
+"""
 @noinline function rng_bit_generator(
+    ::Type{T},
     seed::TracedRArray{UInt64,1},
     shape;
     algorithm::String="DEFAULT",
     location=mlir_stacktrace("rng_bit_generator", @__FILE__, @__LINE__),
-)
-    output = MLIR.IR.TensorType(TracedRArray{UInt64,1}, shape)
+) where {T<:Integer}
+    @assert algorithm in ("DEFAULT", "PHILOX", "THREE_FRY")
+    if algorithm == "PHILOX"
+        @assert length(seed) ∈ (2, 3)
+    elseif algorithm == "THREE_FRY"
+        @assert length(seed) == 2
+    end
+
+    output = MLIR.IR.TensorType(shape, MLIR.IR.Type(T))
+    output_state = MLIR.IR.TensorType(size(seed), MLIR.IR.Type(UInt64))
     rng_algorithm = MLIR.API.stablehloRngAlgorithmAttrGet(MLIR.IR.context(), algorithm)
-    op = stablehlo.rng_bit_generator(seed.mlir_data; output, rng_algorithm, location)
+    op = stablehlo.rng_bit_generator(
+        seed.mlir_data; output, output_state, rng_algorithm, location
+    )
     return (;
-        output_state=TracedRArray{UInt64,1}((), MLIR.IR.result(op, 1), MLIR.IR.size(seed)),
-        output=TracedRArray{T,length(shape)}((), MLIR.IR.result(op, 2), shape),
+        output_state=TracedRArray{UInt64,1}((), MLIR.IR.result(op, 1), size(seed)),
+        output=TracedRArray{T,length(shape)}((), MLIR.IR.result(op, 2), Tuple(shape)),
+    )
+end
+
+@noinline function rng_bit_generator(
+    ::Type{T},
+    seed::TracedRArray{UInt64,1},
+    shape;
+    algorithm::String="DEFAULT",
+    location=mlir_stacktrace("rng_bit_generator", @__FILE__, @__LINE__),
+) where {T<:AbstractFloat}
+    nbits = sizeof(T) * 8
+    uT = nbits == 16 ? UInt16 : (nbits == 32 ? UInt32 : UInt64)
+    (; output_state, output) = rng_bit_generator(uT, seed, shape; algorithm, location)
+    output = divide(
+        convert(TracedRArray{T,ndims(output)}, output),
+        constant(fill(T(typemax(uT)), Tuple(shape)); location),
+    )
+    return (; output_state, output)
+end
+
+"""
+    randn(
+        ::Type{T},
+        seed::TracedRArray{UInt64,1},
+        shape;
+        algorithm::String="DEFAULT",
+        location=mlir_stacktrace("rand", @__FILE__, @__LINE__),
     )
+
+Generate a random array of type `T` with the given shape and seed from a standard normal
+distribution of mean 0 and standard deviation 1. Returns a NamedTuple with the following
+fields:
+
+- `output_state`: The state of the random number generator after the operation.
+- `output`: The generated array.
+
+# Arguments
+
+- `T`: The type of the generated array.
+- `seed`: The seed for the random number generator.
+- `shape`: The shape of the generated array.
+- `algorithm`: The algorithm to use for generating the random numbers. Defaults to
+  "DEFAULT". Other options include "PHILOX" and "THREE_FRY".
+"""
+@noinline function randn(
+    ::Type{T},
+    seed::TracedRArray{UInt64,1},
+    shape;
+    algorithm::String="DEFAULT",
+    location=mlir_stacktrace("rand", @__FILE__, @__LINE__),
+) where {T}
+    res = rng_bit_generator(T, seed, shape; algorithm, location)
+    rand_uniform = res.output
+    seed = res.output_state
+    scaled_uniform = subtract(
+        multiply(rand_uniform, constant(fill(T(2), size(rand_uniform)))),
+        constant(fill(T(1), size(rand_uniform))),
+    )
+    probit = erf_inv(scaled_uniform)
+    rand_normal = multiply(probit, constant(fill(Base.sqrt(T(2)), size(rand_uniform))))
+    return (; output_state=seed, output=rand_normal)
+end
+
+"""
+    randexp(
+        ::Type{T},
+        seed::TracedRArray{UInt64,1},
+        shape;
+        algorithm::String="DEFAULT",
+        location=mlir_stacktrace("rand", @__FILE__, @__LINE__),
+    )
+
+Generate a random array of type `T` with the given shape and seed from an exponential
+distribution with rate 1. Returns a NamedTuple with the following fields:
+
+- `output_state`: The state of the random number generator after the operation.
+- `output`: The generated array.
+
+# Arguments
+
+- `T`: The type of the generated array.
+- `seed`: The seed for the random number generator.
+- `shape`: The shape of the generated array.
+- `algorithm`: The algorithm to use for generating the random numbers. Defaults to
+  "DEFAULT". Other options include "PHILOX" and "THREE_FRY".
+"""
+@noinline function randexp(
+    ::Type{T},
+    seed::TracedRArray{UInt64,1},
+    shape;
+    algorithm::String="DEFAULT",
+    location=mlir_stacktrace("rand", @__FILE__, @__LINE__),
+) where {T}
+    res = rng_bit_generator(T, seed, shape; algorithm, location)
+    rand_uniform = res.output
+    seed = res.output_state
+    rand_exp = negate(log_plus_one(negate(rand_uniform)))
+    return (; output_state=seed, output=rand_exp)
 end
 
 # functional ops

src/Overlay.jl

@@ -3,14 +3,23 @@
 #       correctly. Once that (https://github.com/timholy/Revise.jl/issues/646) is resolved
 #       we should move all the reactant_overrides to relevant files.
 
+# Helper Function to determine if we are inside the ReactantInterpreter
+"""
+    within_reactant_interpreter()
+
+Returns `true` if we are currently inside the ReactantInterpreter.
+"""
+@noinline within_reactant_interpreter() = false
+@reactant_overlay @noinline within_reactant_interpreter() = true
+
 # Compiling within a compile should return simply the original function
 @reactant_overlay function Compiler.compile(
     f, args; client=nothing, optimize=true, sync=false
 )
     return f
 end
 
-# Enzyme overrides
+# Enzyme.jl overlays
 @reactant_overlay @noinline function Enzyme.autodiff_deferred(
     rmode::Enzyme.Mode, f::FA, rt::Type{A}, args::Vararg{Annotation,Nargs}
 ) where {FA<:Annotation,A<:Annotation,Nargs}
@@ -22,3 +31,60 @@ end
 ) where {FA<:Annotation,A<:Annotation,Nargs}
     return overload_autodiff(rmode, f, rt, args...)
 end
+
+# Random.jl overlays
+@reactant_overlay @noinline function Random.default_rng()
+    return call_with_reactant(TracedRandom.default_rng)
+end
+
+## Only problematic edge case here is the direct `<randfun!>(rng, A::AbstractArray)` call
+## We can't directly overlay that call without breaking the semantics of inplace update
+for randfun in (:rand, :randn, :randexp)
+    randfun! = Symbol(randfun, :!)
+    overload_randfun = Symbol(:overload_, randfun)
+    overload_randfun! = Symbol(:overload_, randfun!)
+
+    @eval begin
+        @reactant_overlay @noinline function Random.$(randfun)(
+            rng::AbstractRNG, ::Type{T}, dims::Dims
+        ) where {T <: ReactantPrimitive}
+            return TracedRandom.$(overload_randfun)(rng, T, dims)
+        end
+
+        @reactant_overlay @noinline function Random.$(randfun)(
+            rng::AbstractRNG, dim1::Integer, dims::Integer...
+        )
+            return TracedRandom.$(overload_randfun)(rng, dim1, dims...)
+        end
+
+        @reactant_overlay @noinline function Random.$(randfun)(
+            rng::AbstractRNG, ::Type{T}, dim1::Integer, dims::Integer...
+        ) where {T <: ReactantPrimitive}
+            return TracedRandom.$(overload_randfun)(rng, T, dim1, dims...)
+        end
+
+        # scalars
+        @reactant_overlay @noinline function Random.$(randfun)(
+            rng::AbstractRNG, ::Type{T}=Float64
+        ) where {T <: ReactantPrimitive}
+            return TracedRandom.$(overload_randfun)(rng, T)
+        end
+
+        # inplace
+        @reactant_overlay @noinline function Random.$(randfun!)(
+            rng::AbstractRNG, A::AnyTracedRArray
+        )
+            return TracedRandom.$(overload_randfun!)(rng, A)
+        end
+
+        # warn about direct writing to arrays
+        @reactant_overlay @noinline function Random.$(randfun!)(
+            rng::AbstractRNG, A::AbstractArray
+        )
+            @warn "Directly writing to an array using Random.jl functions inside \
+                   ReactantInterpreter will generate a constant array in the IR. Use with \
+                   caution." maxlog = 1
+            return Random.$(randfun!)(rng, A)
+        end
+    end
+end

src/Reactant.jl

@@ -3,6 +3,8 @@ module Reactant
 using ReactantCore: ReactantCore, @trace, MissingTracedValue
 
 using LinearAlgebra: LinearAlgebra
+using Random: Random, AbstractRNG
+
 using Adapt: Adapt, WrappedArray
 using GPUArraysCore: GPUArraysCore, @allowscalar, allowscalar # keep this import to allow users to do `Reactant.allowscalar(false)`
 
@@ -122,7 +124,14 @@ include("TracedRArray.jl")
 
 include("ConcreteRArray.jl")
 
-include("linear_algebra.jl")
+mutable struct TracedRNG <: Random.AbstractRNG
+    seed::Union{ConcreteRArray{UInt64,1},TracedRArray{UInt64,1}}
+    const algorithm::String
+end
+
+# StdLib Overloads
+include("stdlibs/LinearAlgebra.jl")
+include("stdlibs/Random.jl")
 
 const TracedType = Union{TracedRArray,TracedRNumber,MissingTracedValue}