Merge pull request #23912 from JuliaLang/jn/infer-norecur-more

inference: revise recursion detection algorithm

Author: vtjnash

base/array.jl

@@ -628,18 +628,28 @@ function _collect_indices(indsA, A)
     copy!(B, CartesianRange(indices(B)), A, CartesianRange(indsA))
 end
 
+# define this as a macro so that the call to Inference
+# gets inlined into the caller before recursion detection
+# gets a chance to see it, so that recursive calls to the caller
+# don't trigger the inference limiter
 if isdefined(Core, :Inference)
-    _default_eltype(@nospecialize itrt) = Core.Inference.return_type(first, Tuple{itrt})
+    macro default_eltype(itrt)
+        return quote
+            Core.Inference.return_type(first, Tuple{$(esc(itrt))})
+        end
+    end
 else
-    _default_eltype(@nospecialize itr) = Any
+    macro default_eltype(itrt)
+        return :(Any)
+    end
 end
 
 _array_for(::Type{T}, itr, ::HasLength) where {T} = Array{T,1}(Int(length(itr)::Integer))
 _array_for(::Type{T}, itr, ::HasShape) where {T} = similar(Array{T}, indices(itr))
 
 function collect(itr::Generator)
     isz = iteratorsize(itr.iter)
-    et = _default_eltype(typeof(itr))
+    et = @default_eltype(typeof(itr))
     if isa(isz, SizeUnknown)
         return grow_to!(Array{et,1}(0), itr)
     else
@@ -653,12 +663,12 @@ function collect(itr::Generator)
 end
 
 _collect(c, itr, ::EltypeUnknown, isz::SizeUnknown) =
-    grow_to!(_similar_for(c, _default_eltype(typeof(itr)), itr, isz), itr)
+    grow_to!(_similar_for(c, @default_eltype(typeof(itr)), itr, isz), itr)
 
 function _collect(c, itr, ::EltypeUnknown, isz::Union{HasLength,HasShape})
     st = start(itr)
     if done(itr,st)
-        return _similar_for(c, _default_eltype(typeof(itr)), itr, isz)
+        return _similar_for(c, @default_eltype(typeof(itr)), itr, isz)
     end
     v1, st = next(itr, st)
     collect_to_with_first!(_similar_for(c, typeof(v1), itr, isz), v1, itr, st)

base/dict.jl

@@ -158,9 +158,9 @@ associative_with_eltype(DT_apply, kv, ::TP{K,V}) where {K,V} = DT_apply(K, V)(kv
 associative_with_eltype(DT_apply, kv::Generator, ::TP{K,V}) where {K,V} = DT_apply(K, V)(kv)
 associative_with_eltype(DT_apply, ::Type{Pair{K,V}}) where {K,V} = DT_apply(K, V)()
 associative_with_eltype(DT_apply, ::Type) = DT_apply(Any, Any)()
-associative_with_eltype(DT_apply::F, kv, t) where {F} = grow_to!(associative_with_eltype(DT_apply, _default_eltype(typeof(kv))), kv)
+associative_with_eltype(DT_apply::F, kv, t) where {F} = grow_to!(associative_with_eltype(DT_apply, @default_eltype(typeof(kv))), kv)
 function associative_with_eltype(DT_apply::F, kv::Generator, t) where F
-    T = _default_eltype(typeof(kv))
+    T = @default_eltype(typeof(kv))
     if T <: Union{Pair, Tuple{Any, Any}} && _isleaftype(T)
         return associative_with_eltype(DT_apply, kv, T)
     end

base/inference.jl

@@ -376,7 +376,7 @@ Returns the sum of all elements of `A`, using the Kahan-Babuska-Neumaier compens
 summation algorithm for additional accuracy.
 """
 function sum_kbn(A)
-    T = _default_eltype(typeof(A))
+    T = @default_eltype(typeof(A))
     c = r_promote(+, zero(T)::T)
     i = start(A)
     if done(A, i)

base/reduce.jl

@@ -17,7 +17,7 @@ for sets of arbitrary objects.
 """
 Set(itr) = Set{eltype(itr)}(itr)
 function Set(g::Generator)
-    T = _default_eltype(typeof(g))
+    T = @default_eltype(typeof(g))
     (_isleaftype(T) || T === Union{}) || return grow_to!(Set{T}(), g)
     return Set{T}(g)
 end
@@ -258,7 +258,7 @@ julia> unique(Real[1, 1.0, 2])
 ```
 """
 function unique(itr)
-    T = _default_eltype(typeof(itr))
+    T = @default_eltype(typeof(itr))
     out = Vector{T}()
     seen = Set{T}()
     i = start(itr)

base/set.jl

@@ -926,37 +926,34 @@ end
 # vectors/matrices in mixedargs in their orginal order, and such that the result of
 # broadcast(parevalf, passedargstup...) is broadcast(f, mixedargs...)
 @inline function capturescalars(f, mixedargs)
-    let makeargs = _capturescalars(mixedargs...),
-        parevalf = (passed...) -> f(makeargs(passed...)...),
-        passedsrcargstup = _capturenonscalars(mixedargs...)
+    let (passedsrcargstup, makeargs) = _capturescalars(mixedargs...)
+        parevalf = (passed...) -> f(makeargs(passed...)...)
         return (parevalf, passedsrcargstup)
     end
 end
 
-@inline _capturenonscalars(nonscalararg::SparseVecOrMat, mixedargs...) =
-    (nonscalararg, _capturenonscalars(mixedargs...)...)
-@inline _capturenonscalars(scalararg, mixedargs...) =
-    _capturenonscalars(mixedargs...)
-@inline _capturenonscalars() = ()
+nonscalararg(::SparseVecOrMat) = true
+nonscalararg(::Any) = false
 
-@inline _capturescalars(nonscalararg::SparseVecOrMat, mixedargs...) =
-    let f = _capturescalars(mixedargs...)
-        (head, tail...) -> (head, f(tail...)...) # pass-through
+@inline function _capturescalars()
+    return (), () -> ()
+end
+@inline function _capturescalars(arg, mixedargs...)
+    let (rest, f) = _capturescalars(mixedargs...)
+        if nonscalararg(arg)
+            return (arg, rest...), (head, tail...) -> (head, f(tail...)...) # pass-through to broadcast
+        else
+            return rest, (tail...) -> (arg, f(tail...)...) # add back scalararg after (in makeargs)
+        end
     end
-@inline _capturescalars(scalararg, mixedargs...) =
-    let f = _capturescalars(mixedargs...)
-        (tail...) -> (scalararg, f(tail...)...) # add scalararg
+end
+@inline function _capturescalars(arg) # this definition is just an optimization (to bottom out the recursion slightly sooner)
+    if nonscalararg(arg)
+        return (arg,), (head,) -> (head,) # pass-through
+    else
+        return (), () -> (arg,) # add scalararg
     end
-# TODO: use the implicit version once inference can handle it
-# handle too-many-arguments explicitly
-@inline function _capturescalars()
-    too_many_arguments() = ()
-    too_many_arguments(tail...) = throw(ArgumentError("too many"))
 end
-#@inline _capturescalars(nonscalararg::SparseVecOrMat) =
-#    (head,) -> (head,) # pass-through
-#@inline _capturescalars(scalararg) =
-#    () -> (scalararg,) # add scalararg
 
 # NOTE: The following two method definitions work around #19096.
 broadcast(f::Tf, ::Type{T}, A::SparseMatrixCSC) where {Tf,T} = broadcast(y -> f(T, y), A)

base/sparse/higherorderfns.jl

@@ -538,14 +538,12 @@ static size_t jl_static_show_x_(JL_STREAM *out, jl_value_t *v, jl_datatype_t *vt
     else if (vt == jl_method_instance_type) {
         jl_method_instance_t *li = (jl_method_instance_t*)v;
         if (jl_is_method(li->def.method)) {
-            jl_method_t *m = li->def.method;
-            n += jl_static_show_x(out, (jl_value_t*)m->module, depth);
             if (li->specTypes) {
-                n += jl_printf(out, ".");
-                n += jl_show_svec(out, ((jl_datatype_t*)jl_unwrap_unionall(li->specTypes))->parameters,
-                                  jl_symbol_name(m->name), "(", ")");
+                n += jl_static_show_func_sig(out, li->specTypes);
             }
             else {
+                jl_method_t *m = li->def.method;
+                n += jl_static_show_x(out, (jl_value_t*)m->module, depth);
                 n += jl_printf(out, ".%s(?)", jl_symbol_name(m->name));
             }
         }
@@ -949,15 +947,15 @@ JL_DLLEXPORT size_t jl_static_show_func_sig(JL_STREAM *s, jl_value_t *type)
     if (ftype == NULL)
         return jl_static_show(s, type);
     size_t n = 0;
-    if (jl_nparams(ftype)==0 || ftype == ((jl_datatype_t*)ftype)->name->wrapper) {
+    if (jl_nparams(ftype) == 0 || ftype == ((jl_datatype_t*)ftype)->name->wrapper) {
         n += jl_printf(s, "%s", jl_symbol_name(((jl_datatype_t*)ftype)->name->mt->name));
     }
     else {
         n += jl_printf(s, "(::");
         n += jl_static_show(s, ftype);
         n += jl_printf(s, ")");
     }
-    // TODO: better way to show method parameters
+    jl_unionall_t *tvars = (jl_unionall_t*)type;
     type = jl_unwrap_unionall(type);
     if (!jl_is_datatype(type)) {
         n += jl_printf(s, " ");
@@ -984,6 +982,19 @@ JL_DLLEXPORT size_t jl_static_show_func_sig(JL_STREAM *s, jl_value_t *type)
         }
     }
     n += jl_printf(s, ")");
+    if (jl_is_unionall(tvars)) {
+        int first = 1;
+        n += jl_printf(s, " where {");
+        while (jl_is_unionall(tvars)) {
+            if (first)
+                first = 0;
+            else
+                n += jl_printf(s, ", ");
+            n += jl_static_show(s, (jl_value_t*)tvars->var);
+            tvars = (jl_unionall_t*)tvars->body;
+        }
+        n += jl_printf(s, "}");
+    }
     return n;
 }
 

src/rtutils.c

@@ -3353,10 +3353,6 @@ end
 @test EmptyIIOtherField13175(EmptyImmutable13175(), 1.0) == EmptyIIOtherField13175(EmptyImmutable13175(), 1.0)
 @test EmptyIIOtherField13175(EmptyImmutable13175(), 1.0) != EmptyIIOtherField13175(EmptyImmutable13175(), 2.0)
 
-# issue #13183
-gg13183(x::X...) where {X} = 1==0 ? gg13183(x, x) : 0
-@test gg13183(5) == 0
-
 # issue 8932 (llvm return type legalizer error)
 struct Vec3_8932
     x::Float32
@@ -5331,7 +5327,8 @@ module UnionOptimizations
 using Test
 
 const boxedunions = [Union{}, Union{String, Void}]
-const unboxedunions = [Union{Int8, Void}, Union{Int8, Float16, Void},
+const unboxedunions = [Union{Int8, Void},
+                       Union{Int8, Float16, Void},
                        Union{Int8, UInt8, Int16, UInt16, Int32, UInt32, Int64, UInt64, Int128, UInt128},
                        Union{Char, Date, Int}]
 
@@ -5457,6 +5454,7 @@ t4 = vcat(A23567, t2, t3)
 @test t4[11:15] == A23567
 
 for U in unboxedunions
+    Base.unionlen(U) > 5 && continue # larger values cause subtyping to crash
     local U
     for N in (1, 2, 3, 4)
         A = Array{U}(ntuple(x->0, N)...)

test/core.jl

@@ -2,6 +2,20 @@
 
 # tests for Core.Inference correctness and precision
 import Core.Inference: Const, Conditional, ⊑
+const isleaftype = Core.Inference._isleaftype
+
+# demonstrate some of the type-size limits
+@test Core.Inference.limit_type_size(Ref{Complex{T} where T}, Ref, Ref, 0) == Ref
+@test Core.Inference.limit_type_size(Ref{Complex{T} where T}, Ref{Complex{T} where T}, Ref, 0) == Ref{Complex{T} where T}
+let comparison = Tuple{X, X} where X<:Tuple
+    sig = Tuple{X, X} where X<:comparison
+    ref = Tuple{X, X} where X
+    @test Core.Inference.limit_type_size(sig, comparison, comparison, 10) == comparison
+    @test Core.Inference.limit_type_size(sig, ref, comparison,  10) == comparison
+    @test Core.Inference.limit_type_size(Tuple{sig}, Tuple{ref}, comparison,  10) == Tuple{comparison}
+    @test Core.Inference.limit_type_size(sig, ref, Tuple{comparison},  10) == sig
+end
+
 
 # issue 9770
 @noinline x9770() = false
@@ -186,7 +200,6 @@ function find_tvar10930(arg)
 end
 @test find_tvar10930(Vararg{Int}) === 1
 
-const isleaftype = Base._isleaftype
 
 # issue #12474
 @generated function f12474(::Any)
@@ -980,13 +993,13 @@ copy_dims_out(out) = ()
 copy_dims_out(out, dim::Int, tail...) =  copy_dims_out((out..., dim), tail...)
 copy_dims_out(out, dim::Colon, tail...) = copy_dims_out((out..., dim), tail...)
 @test Base.return_types(copy_dims_out, (Tuple{}, Vararg{Union{Int,Colon}})) == Any[Tuple{}, Tuple{}, Tuple{}]
-@test all(m -> 2 < count_specializations(m) < 15, methods(copy_dims_out))
+@test all(m -> 10 < count_specializations(m) < 25, methods(copy_dims_out))
 
 copy_dims_pair(out) = ()
-copy_dims_pair(out, dim::Int, tail...) =  copy_dims_out(out => dim, tail...)
-copy_dims_pair(out, dim::Colon, tail...) = copy_dims_out(out => dim, tail...)
+copy_dims_pair(out, dim::Int, tail...) =  copy_dims_pair(out => dim, tail...)
+copy_dims_pair(out, dim::Colon, tail...) = copy_dims_pair(out => dim, tail...)
 @test Base.return_types(copy_dims_pair, (Tuple{}, Vararg{Union{Int,Colon}})) == Any[Tuple{}, Tuple{}, Tuple{}]
-@test all(m -> 5 < count_specializations(m) < 25, methods(copy_dims_out))
+@test all(m -> 5 < count_specializations(m) < 25, methods(copy_dims_pair))
 
 # splatting an ::Any should still allow inference to use types of parameters preceding it
 f22364(::Int, ::Any...) = 0
@@ -1225,3 +1238,8 @@ end
 let t = Tuple{Type{T23786{D, N} where N where D<:Tuple{Vararg{Array{T, 1} where T, N} where N}}}
     @test Core.Inference.limit_type_depth(t, 4) >: t
 end
+
+# issue #13183
+_false13183 = false
+gg13183(x::X...) where {X} = (_false13183 ? gg13183(x, x) : 0)
+@test gg13183(5) == 0