Merge branch 'master' into new-heuristics

Author: gbaraldi

Makefile

@@ -196,7 +196,7 @@ else ifeq ($(JULIA_BUILD_MODE),debug)
 JL_PRIVATE_LIBS-0 += libjulia-internal-debug libjulia-codegen-debug
 endif
 ifeq ($(USE_GPL_LIBS), 1)
-JL_PRIVATE_LIBS-$(USE_SYSTEM_LIBSUITESPARSE) += libamd libbtf libcamd libccolamd libcholmod libcolamd libklu libldl librbio libspqr libsuitesparseconfig libumfpack
+JL_PRIVATE_LIBS-$(USE_SYSTEM_LIBSUITESPARSE) += libamd libbtf libcamd libccolamd libcholmod libcholmod_cuda libcolamd libklu libldl librbio libspqr libspqr_cuda libsuitesparseconfig libumfpack
 endif
 JL_PRIVATE_LIBS-$(USE_SYSTEM_LIBBLASTRAMPOLINE) += libblastrampoline
 JL_PRIVATE_LIBS-$(USE_SYSTEM_PCRE) += libpcre2-8

NEWS.md

@@ -22,9 +22,12 @@ Build system changes
 
 New library functions
 ---------------------
+* `copyuntil(out, io, delim)` and `copyline(out, io)` copy data into an `out::IO` stream ([#48273]).
 
 New library features
 --------------------
+* `replace(string, pattern...)` now supports an optional `IO` argument to
+  write the output to a stream rather than returning a string ([#48625]).
 
 Standard library changes
 ------------------------

base/Makefile

@@ -269,9 +269,11 @@ $(eval $(call symlink_system_library,LIBSUITESPARSE,libamd))
 $(eval $(call symlink_system_library,LIBSUITESPARSE,libcamd))
 $(eval $(call symlink_system_library,LIBSUITESPARSE,libccolamd))
 $(eval $(call symlink_system_library,LIBSUITESPARSE,libcholmod))
+$(eval $(call symlink_system_library,LIBSUITESPARSE,libcholmod_cuda))
 $(eval $(call symlink_system_library,LIBSUITESPARSE,libcolamd))
 $(eval $(call symlink_system_library,LIBSUITESPARSE,libumfpack))
 $(eval $(call symlink_system_library,LIBSUITESPARSE,libspqr))
+$(eval $(call symlink_system_library,LIBSUITESPARSE,libspqr_cuda))
 $(eval $(call symlink_system_library,LIBSUITESPARSE,libsuitesparseconfig))
 # EXCLUDED LIBRARIES (installed/used, but not vendored for use with dlopen):
 # libunwind

base/abstractarray.jl

@@ -95,7 +95,7 @@ julia> axes(A)
 """
 function axes(A)
     @inline
-    map(oneto, size(A))
+    map(unchecked_oneto, size(A))
 end
 
 """
@@ -1651,7 +1651,7 @@ function _typed_hcat(::Type{T}, A::AbstractVecOrTuple{AbstractVecOrMat}) where T
     for j = 1:nargs
         Aj = A[j]
         if size(Aj, 1) != nrows
-            throw(ArgumentError("number of rows of each array must match (got $(map(x->size(x,1), A)))"))
+            throw(DimensionMismatch("number of rows of each array must match (got $(map(x->size(x,1), A)))"))
         end
         dense &= isa(Aj,Array)
         nd = ndims(Aj)
@@ -1686,7 +1686,7 @@ function _typed_vcat(::Type{T}, A::AbstractVecOrTuple{AbstractVecOrMat}) where T
     ncols = size(A[1], 2)
     for j = 2:nargs
         if size(A[j], 2) != ncols
-            throw(ArgumentError("number of columns of each array must match (got $(map(x->size(x,2), A)))"))
+            throw(DimensionMismatch("number of columns of each array must match (got $(map(x->size(x,2), A)))"))
         end
     end
     B = similar(A[1], T, nrows, ncols)
@@ -1984,16 +1984,14 @@ julia> cat(1, [2], [3;;]; dims=Val(2))
 
 # The specializations for 1 and 2 inputs are important
 # especially when running with --inline=no, see #11158
-# The specializations for Union{AbstractVecOrMat,Number} are necessary
-# to have more specialized methods here than in LinearAlgebra/uniformscaling.jl
 vcat(A::AbstractArray) = cat(A; dims=Val(1))
 vcat(A::AbstractArray, B::AbstractArray) = cat(A, B; dims=Val(1))
 vcat(A::AbstractArray...) = cat(A...; dims=Val(1))
-vcat(A::Union{AbstractVecOrMat,Number}...) = cat(A...; dims=Val(1))
+vcat(A::Union{AbstractArray,Number}...) = cat(A...; dims=Val(1))
 hcat(A::AbstractArray) = cat(A; dims=Val(2))
 hcat(A::AbstractArray, B::AbstractArray) = cat(A, B; dims=Val(2))
 hcat(A::AbstractArray...) = cat(A...; dims=Val(2))
-hcat(A::Union{AbstractVecOrMat,Number}...) = cat(A...; dims=Val(2))
+hcat(A::Union{AbstractArray,Number}...) = cat(A...; dims=Val(2))
 
 typed_vcat(T::Type, A::AbstractArray) = _cat_t(Val(1), T, A)
 typed_vcat(T::Type, A::AbstractArray, B::AbstractArray) = _cat_t(Val(1), T, A, B)
@@ -2055,8 +2053,8 @@ julia> hvcat((2,2,2), a,b,c,d,e,f) == hvcat(2, a,b,c,d,e,f)
 true
 ```
 """
-hvcat(rows::Tuple{Vararg{Int}}, xs::AbstractVecOrMat...) = typed_hvcat(promote_eltype(xs...), rows, xs...)
-hvcat(rows::Tuple{Vararg{Int}}, xs::AbstractVecOrMat{T}...) where {T} = typed_hvcat(T, rows, xs...)
+hvcat(rows::Tuple{Vararg{Int}}, xs::AbstractArray...) = typed_hvcat(promote_eltype(xs...), rows, xs...)
+hvcat(rows::Tuple{Vararg{Int}}, xs::AbstractArray{T}...) where {T} = typed_hvcat(T, rows, xs...)
 
 function typed_hvcat(::Type{T}, rows::Tuple{Vararg{Int}}, as::AbstractVecOrMat...) where T
     nbr = length(rows)  # number of block rows
@@ -2084,16 +2082,16 @@ function typed_hvcat(::Type{T}, rows::Tuple{Vararg{Int}}, as::AbstractVecOrMat..
             Aj = as[a+j-1]
             szj = size(Aj,2)
             if size(Aj,1) != szi
-                throw(ArgumentError("mismatched height in block row $(i) (expected $szi, got $(size(Aj,1)))"))
+                throw(DimensionMismatch("mismatched height in block row $(i) (expected $szi, got $(size(Aj,1)))"))
             end
             if c-1+szj > nc
-                throw(ArgumentError("block row $(i) has mismatched number of columns (expected $nc, got $(c-1+szj))"))
+                throw(DimensionMismatch("block row $(i) has mismatched number of columns (expected $nc, got $(c-1+szj))"))
             end
             out[r:r-1+szi, c:c-1+szj] = Aj
             c += szj
         end
         if c != nc+1
-            throw(ArgumentError("block row $(i) has mismatched number of columns (expected $nc, got $(c-1))"))
+            throw(DimensionMismatch("block row $(i) has mismatched number of columns (expected $nc, got $(c-1))"))
         end
         r += szi
         a += rows[i]
@@ -2115,7 +2113,7 @@ function hvcat(rows::Tuple{Vararg{Int}}, xs::T...) where T<:Number
     k = 1
     @inbounds for i=1:nr
         if nc != rows[i]
-            throw(ArgumentError("row $(i) has mismatched number of columns (expected $nc, got $(rows[i]))"))
+            throw(DimensionMismatch("row $(i) has mismatched number of columns (expected $nc, got $(rows[i]))"))
         end
         for j=1:nc
             a[i,j] = xs[k]
@@ -2144,14 +2142,14 @@ end
 hvcat(rows::Tuple{Vararg{Int}}, xs::Number...) = typed_hvcat(promote_typeof(xs...), rows, xs...)
 hvcat(rows::Tuple{Vararg{Int}}, xs...) = typed_hvcat(promote_eltypeof(xs...), rows, xs...)
 # the following method is needed to provide a more specific one compared to LinearAlgebra/uniformscaling.jl
-hvcat(rows::Tuple{Vararg{Int}}, xs::Union{AbstractVecOrMat,Number}...) = typed_hvcat(promote_eltypeof(xs...), rows, xs...)
+hvcat(rows::Tuple{Vararg{Int}}, xs::Union{AbstractArray,Number}...) = typed_hvcat(promote_eltypeof(xs...), rows, xs...)
 
 function typed_hvcat(::Type{T}, rows::Tuple{Vararg{Int}}, xs::Number...) where T
     nr = length(rows)
     nc = rows[1]
     for i = 2:nr
         if nc != rows[i]
-            throw(ArgumentError("row $(i) has mismatched number of columns (expected $nc, got $(rows[i]))"))
+            throw(DimensionMismatch("row $(i) has mismatched number of columns (expected $nc, got $(rows[i]))"))
         end
     end
     hvcat_fill!(Matrix{T}(undef, nr, nc), xs)
@@ -2319,7 +2317,7 @@ function _typed_hvncat(::Type{T}, ::Val{N}, as::AbstractArray...) where {T, N}
         Ndim += cat_size(as[i], N)
         nd = max(nd, cat_ndims(as[i]))
         for d ∈ 1:N - 1
-            cat_size(as[1], d) == cat_size(as[i], d) || throw(ArgumentError("mismatched size along axis $d in element $i"))
+            cat_size(as[1], d) == cat_size(as[i], d) || throw(DimensionMismatch("mismatched size along axis $d in element $i"))
         end
     end
 
@@ -2346,7 +2344,7 @@ function _typed_hvncat(::Type{T}, ::Val{N}, as...) where {T, N}
         nd = max(nd, cat_ndims(as[i]))
         for d ∈ 1:N-1
             cat_size(as[i], d) == 1 ||
-                throw(ArgumentError("all dimensions of element $i other than $N must be of length 1"))
+                throw(DimensionMismatch("all dimensions of element $i other than $N must be of length 1"))
         end
     end
 
@@ -2463,7 +2461,7 @@ function _typed_hvncat_dims(::Type{T}, dims::NTuple{N, Int}, row_first::Bool, as
                 for dd ∈ 1:N
                     dd == d && continue
                     if cat_size(as[startelementi], dd) != cat_size(as[i], dd)
-                        throw(ArgumentError("incompatible shape in element $i"))
+                        throw(DimensionMismatch("incompatible shape in element $i"))
                     end
                 end
             end
@@ -2500,18 +2498,18 @@ function _typed_hvncat_dims(::Type{T}, dims::NTuple{N, Int}, row_first::Bool, as
                     elseif currentdims[d] < outdims[d] # dimension in progress
                         break
                     else # exceeded dimension
-                        throw(ArgumentError("argument $i has too many elements along axis $d"))
+                        throw(DimensionMismatch("argument $i has too many elements along axis $d"))
                     end
                 end
             end
         elseif currentdims[d1] > outdims[d1] # exceeded dimension
-            throw(ArgumentError("argument $i has too many elements along axis $d1"))
+            throw(DimensionMismatch("argument $i has too many elements along axis $d1"))
         end
     end
 
     outlen = prod(outdims)
     elementcount == outlen ||
-        throw(ArgumentError("mismatched number of elements; expected $(outlen), got $(elementcount)"))
+        throw(DimensionMismatch("mismatched number of elements; expected $(outlen), got $(elementcount)"))
 
     # copy into final array
     A = cat_similar(as[1], T, outdims)
@@ -2572,8 +2570,8 @@ function _typed_hvncat_shape(::Type{T}, shape::NTuple{N, Tuple}, row_first, as::
             if d == 1 || i == 1 || wasstartblock
                 currentdims[d] += dsize
             elseif dsize != cat_size(as[i - 1], ad)
-                throw(ArgumentError("argument $i has a mismatched number of elements along axis $ad; \
-                                    expected $(cat_size(as[i - 1], ad)), got $dsize"))
+                throw(DimensionMismatch("argument $i has a mismatched number of elements along axis $ad; \
+                                         expected $(cat_size(as[i - 1], ad)), got $dsize"))
             end
 
             wasstartblock = blockcounts[d] == 1 # remember for next dimension
@@ -2583,15 +2581,15 @@ function _typed_hvncat_shape(::Type{T}, shape::NTuple{N, Tuple}, row_first, as::
                 if outdims[d] == -1
                     outdims[d] = currentdims[d]
                 elseif outdims[d] != currentdims[d]
-                    throw(ArgumentError("argument $i has a mismatched number of elements along axis $ad; \
-                                        expected $(abs(outdims[d] - (currentdims[d] - dsize))), got $dsize"))
+                    throw(DimensionMismatch("argument $i has a mismatched number of elements along axis $ad; \
+                                             expected $(abs(outdims[d] - (currentdims[d] - dsize))), got $dsize"))
                 end
                 currentdims[d] = 0
                 blockcounts[d] = 0
                 shapepos[d] += 1
                 d > 1 && (blockcounts[d - 1] == 0 ||
-                    throw(ArgumentError("shape in level $d is inconsistent; level counts must nest \
-                                        evenly into each other")))
+                    throw(DimensionMismatch("shape in level $d is inconsistent; level counts must nest \
+                                             evenly into each other")))
             end
         end
     end

base/array.jl

@@ -1757,7 +1757,7 @@ function splice!(a::Vector, i::Integer, ins=_default_splice)
     if m == 0
         _deleteat!(a, i, 1)
     elseif m == 1
-        a[i] = ins[1]
+        a[i] = only(ins)
     else
         _growat!(a, i, m-1)
         k = 1
@@ -2041,18 +2041,6 @@ function vcat(arrays::Vector{T}...) where T
 end
 vcat(A::Vector...) = cat(A...; dims=Val(1)) # more special than SparseArrays's vcat
 
-# disambiguation with LinAlg/special.jl
-# Union{Number,Vector,Matrix} is for LinearAlgebra._DenseConcatGroup
-# VecOrMat{T} is for LinearAlgebra._TypedDenseConcatGroup
-hcat(A::Union{Number,Vector,Matrix}...) = cat(A...; dims=Val(2))
-hcat(A::VecOrMat{T}...) where {T} = typed_hcat(T, A...)
-vcat(A::Union{Number,Vector,Matrix}...) = cat(A...; dims=Val(1))
-vcat(A::VecOrMat{T}...) where {T} = typed_vcat(T, A...)
-hvcat(rows::Tuple{Vararg{Int}}, xs::Union{Number,Vector,Matrix}...) =
-    typed_hvcat(promote_eltypeof(xs...), rows, xs...)
-hvcat(rows::Tuple{Vararg{Int}}, xs::VecOrMat{T}...) where {T} =
-    typed_hvcat(T, rows, xs...)
-
 _cat(n::Integer, x::Integer...) = reshape([x...], (ntuple(Returns(1), n-1)..., length(x)))
 
 ## find ##
@@ -2445,9 +2433,8 @@ julia> findall(x -> x >= 0, d)
 ```
 """
 function findall(testf::Function, A)
-    T = eltype(keys(A))
     gen = (first(p) for p in pairs(A) if testf(last(p)))
-    isconcretetype(T) ? collect(T, gen) : collect(gen)
+    @default_eltype(gen) === Union{} ? collect(@default_eltype(keys(A)), gen) : collect(gen)
 end
 
 # Broadcasting is much faster for small testf, and computing

base/asyncevent.jl

@@ -272,8 +272,8 @@ julia> begin
 3
 ```
 """
-function Timer(cb::Function, timeout::Real; interval::Real=0.0)
-    timer = Timer(timeout, interval=interval)
+function Timer(cb::Function, timeout; kwargs...)
+    timer = Timer(timeout; kwargs...)
     t = @task begin
         unpreserve_handle(timer)
         while _trywait(timer)