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Simplify broadcastable a bit further and add docs (#26601)
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* Make LinAlg fess up to using Base._return_type

* Simplify broadcastable a bit further and add docs

Amazing what a great exercise writing documentation is. This is a followup to #26435, and more clearly lays out the requirements for defining a custom (non-AbstractArray) type that can participate in broadcasting.  The biggest functional change here is that types that define their own BroadcastStyle must now also implement `broadcastable` to be a no-op.

* Trailing comma, doc fixes from review; more tests
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mbauman committed Apr 4, 2018
1 parent b64a8e0 commit 416305c
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25 changes: 13 additions & 12 deletions base/broadcast.jl
Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@ using .Base: Indices, OneTo, linearindices, tail, to_shape,
_msk_end, unsafe_bitgetindex, bitcache_chunks, bitcache_size, dumpbitcache,
isoperator, promote_typejoin, unalias
import .Base: broadcast, broadcast!
export BroadcastStyle, broadcast_indices, broadcast_similar,
export BroadcastStyle, broadcast_indices, broadcast_similar, broadcastable,
broadcast_getindex, broadcast_setindex!, dotview, @__dot__

### Objects with customized broadcasting behavior should declare a BroadcastStyle
Expand Down Expand Up @@ -48,7 +48,6 @@ BroadcastStyle(::Type{<:Tuple}) = Style{Tuple}()

struct Unknown <: BroadcastStyle end
BroadcastStyle(::Type{Union{}}) = Unknown() # ambiguity resolution
BroadcastStyle(::Type) = Unknown()

"""
`Broadcast.AbstractArrayStyle{N} <: BroadcastStyle` is the abstract supertype for any style
Expand Down Expand Up @@ -101,7 +100,8 @@ struct DefaultArrayStyle{N} <: AbstractArrayStyle{N} end
const DefaultVectorStyle = DefaultArrayStyle{1}
const DefaultMatrixStyle = DefaultArrayStyle{2}
BroadcastStyle(::Type{<:AbstractArray{T,N}}) where {T,N} = DefaultArrayStyle{N}()
BroadcastStyle(::Type{<:Union{Ref,Number}}) = DefaultArrayStyle{0}()
BroadcastStyle(::Type{<:Ref}) = DefaultArrayStyle{0}()
BroadcastStyle(::Type{T}) where {T} = DefaultArrayStyle{ndims(T)}()

# `ArrayConflict` is an internal type signaling that two or more different `AbstractArrayStyle`
# objects were supplied as arguments, and that no rule was defined for resolving the
Expand Down Expand Up @@ -385,9 +385,15 @@ end
"""
broadcastable(x)
Return either `x` or an object like `x` such that it supports `axes` and indexing.
Return either `x` or an object like `x` such that it supports `axes`, indexing, and its type supports `ndims`.
If `x` supports iteration, the returned value should have the same `axes` and indexing behaviors as [`collect(x)`](@ref).
If `x` supports iteration, the returned value should have the same `axes` and indexing
behaviors as [`collect(x)`](@ref).
If `x` is not an `AbstractArray` but it supports `axes`, indexing, and its type supports
`ndims`, then `broadcastable(::typeof(x))` may be implemented to just return itself.
Further, if `x` defines its own [`BroadcastStyle`](@ref), then it must define its
`broadcastable` method to return itself for the custom style to have any effect.
# Examples
```jldoctest
Expand All @@ -407,9 +413,9 @@ Base.RefValue{String}("hello")
broadcastable(x::Union{Symbol,AbstractString,Function,UndefInitializer,Nothing,RoundingMode,Missing}) = Ref(x)
broadcastable(x::Ptr) = Ref{Ptr}(x) # Cannot use Ref(::Ptr) until ambiguous deprecation goes through
broadcastable(::Type{T}) where {T} = Ref{Type{T}}(T)
broadcastable(x::AbstractArray) = x
broadcastable(x::Union{AbstractArray,Number,Ref,Tuple}) = x
# In the future, default to collecting arguments. TODO: uncomment once deprecations are removed
# broadcastable(x) = BroadcastStyle(typeof(x)) isa Unknown ? collect(x) : x
# broadcastable(x) = collect(x)
# broadcastable(::Union{AbstractDict, NamedTuple}) = error("intentionally unimplemented to allow development in 1.x")

"""
Expand Down Expand Up @@ -590,11 +596,6 @@ julia> abs.((1, -2))
julia> broadcast(+, 1.0, (0, -2.0))
(1.0, -1.0)
julia> broadcast(+, 1.0, (0, -2.0), Ref(1))
2-element Array{Float64,1}:
2.0
0.0
julia> (+).([[0,2], [1,3]], Ref{Vector{Int}}([1,-1]))
2-element Array{Array{Int64,1},1}:
[1, 1]
Expand Down
14 changes: 5 additions & 9 deletions base/deprecated.jl
Original file line number Diff line number Diff line change
Expand Up @@ -689,15 +689,11 @@ end

# Broadcast no longer defaults to treating its arguments as scalar (#)
@noinline function Broadcast.broadcastable(x)
if Base.Broadcast.BroadcastStyle(typeof(x)) isa Broadcast.Unknown
depwarn("""
broadcast will default to iterating over its arguments in the future. Wrap arguments of
type `x::$(typeof(x))` with `Ref(x)` to ensure they broadcast as "scalar" elements.
""", (:broadcast, :broadcast!))
return Ref{typeof(x)}(x)
else
return x
end
depwarn("""
broadcast will default to iterating over its arguments in the future. Wrap arguments of
type `x::$(typeof(x))` with `Ref(x)` to ensure they broadcast as "scalar" elements.
""", (:broadcast, :broadcast!))
return Ref{typeof(x)}(x)
end
@eval Base.Broadcast Base.@deprecate_binding Scalar DefaultArrayStyle{0} false
# After deprecation is removed, enable the fallback broadcastable definitions in base/broadcast.jl
Expand Down
2 changes: 1 addition & 1 deletion doc/src/base/arrays.md
Original file line number Diff line number Diff line change
Expand Up @@ -70,10 +70,10 @@ For specializing broadcast on custom types, see
Base.BroadcastStyle
Base.broadcast_similar
Base.broadcast_indices
Base.Broadcast.Scalar
Base.Broadcast.AbstractArrayStyle
Base.Broadcast.ArrayStyle
Base.Broadcast.DefaultArrayStyle
Base.Broadcast.broadcastable
```

## Indexing and assignment
Expand Down
124 changes: 75 additions & 49 deletions doc/src/manual/interfaces.md
Original file line number Diff line number Diff line change
Expand Up @@ -443,7 +443,8 @@ V = view(A, [1,2,4], :) # is not strided, as the spacing between rows is not f
| `Base.broadcast_similar(f, ::DestStyle, ::Type{ElType}, inds, As...)` | Allocation of output container |
| **Optional methods** | | |
| `Base.BroadcastStyle(::Style1, ::Style2) = Style12()` | Precedence rules for mixing styles |
| `Base.broadcast_indices(::StyleA, A)` | Declaration of the indices of `A` for broadcasting purposes (for AbstractArrays, defaults to `axes(A)`) |
| `Base.broadcast_indices(::StyleA, A)` | Declaration of the indices of `A` for broadcasting purposes (defaults to [`axes(A)`](@ref)) |
| `Base.broadcastable(x)` | Convert `x` to an object that has `axes` and supports indexing |
| **Bypassing default machinery** | |
| `broadcast(f, As...)` | Complete bypass of broadcasting machinery |
| `broadcast(f, ::DestStyle, ::Nothing, ::Nothing, As...)` | Bypass after container type is computed |
Expand All @@ -452,21 +453,43 @@ V = view(A, [1,2,4], :) # is not strided, as the spacing between rows is not f
| `broadcast!(f, dest, ::BroadcastStyle, As...)` | Bypass in-place broadcast, specialization on `BroadcastStyle` |

[Broadcasting](@ref) is triggered by an explicit call to `broadcast` or `broadcast!`, or implicitly by
"dot" operations like `A .+ b`. Any `AbstractArray` type supports broadcasting,
but the default result (output) type is `Array`. To specialize the result for specific input type(s),
the main task is the allocation of an appropriate result object.
(This is not an issue for `broadcast!`, where
the result object is passed as an argument.) This process is split into two stages: computation
of the behavior and type from the arguments ([`Base.BroadcastStyle`](@ref)), and allocation of the object
given the resulting type with [`Base.broadcast_similar`](@ref).

`Base.BroadcastStyle` is an abstract type from which all styles are
"dot" operations like `A .+ b` or `f.(x, y)`. Any object that has [`axes`](@ref) and supports
indexing can participate as an argument in broadcasting, and by default the result is stored
in an `Array`. This basic framework is extensible in three major ways:

* Ensuring that all arguments support broadcast
* Selecting an appropriate output array for the given set of arguments
* Selecting an efficient implementation for the given set of arguments

Not all types support `axes` and indexing, but many are convenient to allow in broadcast.
The [`Base.broadcastable`](@ref) function is called on each argument to broadcast, allowing
it to return something different that supports `axes` and indexing if it does not. By
default, this is the identity function for all `AbstractArray`s and `Number`s — they already
support `axes` and indexing. For a handful of other types (including but not limited to
types themselves, functions, special singletons like `missing` and `nothing`, and dates),
`Base.broadcastable` returns the argument wrapped in a `Ref` to act as a 0-dimensional
"scalar" for the purposes of broadcasting. Custom types can similarly specialize
`Base.broadcastable` to define their shape, but they should follow the convention that
`collect(Base.broadcastable(x)) == collect(x)`. A notable exception are `AbstractString`s;
they are special-cased to behave as scalars for the purposes of broadcast even though they
are iterable collections of their characters.

The next two steps (selecting the output array and implementation) are dependent upon
determining a single answer for a given set of arguments. Broadcast must take all the varied
types of its arguments and collapse them down to just one output array and one
implementation. Broadcast calls this single answer a "style." Every broadcastable object
each has its own preferred style, and a promotion-like system is used to combine these
styles into a single answer — the "destination style".

### Broadcast Styles

`Base.BroadcastStyle` is the abstract type from which all styles are
derived. When used as a function it has two possible forms,
unary (single-argument) and binary.
The unary variant states that you intend to
implement specific broadcasting behavior and/or output type,
and do not wish to rely on the default fallback ([`Broadcast.Scalar`](@ref) or [`Broadcast.DefaultArrayStyle`](@ref)).
To achieve this, you can define a custom `BroadcastStyle` for your object:
and do not wish to rely on the default fallback ([`Broadcast.DefaultArrayStyle`](@ref)).
To override these defaults, you can define a custom `BroadcastStyle` for your object:

```julia
struct MyStyle <: Broadcast.BroadcastStyle end
Expand All @@ -486,6 +509,8 @@ When your broadcast operation involves several arguments, individual argument st
combined to determine a single `DestStyle` that controls the type of the output container.
For more detail, see [below](@ref writing-binary-broadcasting-rules).

### Selecting an appropriate output array

The actual allocation of the result array is handled by `Base.broadcast_similar`:

```julia
Expand Down Expand Up @@ -562,6 +587,8 @@ julia> a .+ [5,10]
13 14
```

### [Extending broadcast with custom implementations](@id extending-in-place-broadcast)

Finally, it's worth noting that sometimes it's easier simply to bypass the machinery for
computing result types and container sizes, and just do everything manually. For example,
you can convert a `UnitRange{Int}` `r` to a `UnitRange{BigInt}` with `big.(r)`; the definition
Expand All @@ -580,7 +607,40 @@ the internal machinery to compute the container type, element type, and indices
Broadcast.broadcast(::typeof(somefunction), ::MyStyle, ::Type{ElType}, inds, As...)
```

### [Writing binary broadcasting rules](@id writing-binary-broadcasting-rules)
Extending `broadcast!` (in-place broadcast) should be done with care, as it is easy to introduce
ambiguities between packages. To avoid these ambiguities, we adhere to the following conventions.

First, if you want to specialize on the destination type, say `DestType`, then you should
define a method with the following signature:

```julia
broadcast!(f, dest::DestType, ::Nothing, As...)
```

Note that no bounds should be placed on the types of `f` and `As...`.

Second, if specialized `broadcast!` behavior is desired depending on the input types,
you should write [binary broadcasting rules](@ref writing-binary-broadcasting-rules) to
determine a custom `BroadcastStyle` given the input types, say `MyBroadcastStyle`, and you should define a method with the following
signature:

```julia
broadcast!(f, dest, ::MyBroadcastStyle, As...)
```

Note the lack of bounds on `f`, `dest`, and `As...`.

Third, simultaneously specializing on both the type of `dest` and the `BroadcastStyle` is fine. In this case,
it is also allowed to specialize on the types of the source arguments (`As...`). For example, these method signatures are OK:

```julia
broadcast!(f, dest::DestType, ::MyBroadcastStyle, As...)
broadcast!(f, dest::DestType, ::MyBroadcastStyle, As::AbstractArray...)
broadcast!(f, dest::DestType, ::Broadcast.DefaultArrayStyle{0}, As::Number...)
```


#### [Writing binary broadcasting rules](@id writing-binary-broadcasting-rules)

The precedence rules are defined by binary `BroadcastStyle` calls:

Expand All @@ -592,10 +652,10 @@ where `Style12` is the `BroadcastStyle` you want to choose for outputs involving
arguments of `Style1` and `Style2`. For example,

```julia
Base.BroadcastStyle(::Broadcast.Style{Tuple}, ::Broadcast.Scalar) = Broadcast.Style{Tuple}()
Base.BroadcastStyle(::Broadcast.Style{Tuple}, ::Broadcast.AbstractArrayStyle{0}) = Broadcast.Style{Tuple}()
```

indicates that `Tuple` "wins" over scalars (the output container will be a tuple).
indicates that `Tuple` "wins" over zero-dimensional arrays (the output container will be a tuple).
It is worth noting that you do not need to (and should not) define both argument orders
of this call; defining one is sufficient no matter what order the user supplies the arguments in.

Expand Down Expand Up @@ -643,37 +703,3 @@ yields another `SparseVecStyle`, that its combination with a 2-dimensional array
yields a `SparseMatStyle`, and anything of higher dimensionality falls back to the dense arbitrary-dimensional framework.
These rules allow broadcasting to keep the sparse representation for operations that result
in one or two dimensional outputs, but produce an `Array` for any other dimensionality.

### [Extending `broadcast!`](@id extending-in-place-broadcast)

Extending `broadcast!` (in-place broadcast) should be done with care, as it is easy to introduce
ambiguities between packages. To avoid these ambiguities, we adhere to the following conventions.

First, if you want to specialize on the destination type, say `DestType`, then you should
define a method with the following signature:

```julia
broadcast!(f, dest::DestType, ::Nothing, As...)
```

Note that no bounds should be placed on the types of `f` and `As...`.

Second, if specialized `broadcast!` behavior is desired depending on the input types,
you should write [binary broadcasting rules](@ref writing-binary-broadcasting-rules) to
determine a custom `BroadcastStyle` given the input types, say `MyBroadcastStyle`, and you should define a method with the following
signature:

```julia
broadcast!(f, dest, ::MyBroadcastStyle, As...)
```

Note the lack of bounds on `f`, `dest`, and `As...`.

Third, simultaneously specializing on both the type of `dest` and the `BroadcastStyle` is fine. In this case,
it is also allowed to specialize on the types of the source arguments (`As...`). For example, these method signatures are OK:

```julia
broadcast!(f, dest::DestType, ::MyBroadcastStyle, As...)
broadcast!(f, dest::DestType, ::MyBroadcastStyle, As::AbstractArray...)
broadcast!(f, dest::DestType, ::Broadcast.Scalar, As::Number...)
```
12 changes: 6 additions & 6 deletions stdlib/LinearAlgebra/src/uniformscaling.jl
Original file line number Diff line number Diff line change
Expand Up @@ -102,7 +102,7 @@ for (t1, t2) in ((:UnitUpperTriangular, :UpperTriangular),
($op)(UL::$t2, J::UniformScaling) = ($t2)(($op)(UL.data, J))

function ($op)(UL::$t1, J::UniformScaling)
ULnew = copy_oftype(UL.data, Broadcast.combine_eltypes($op, UL, J))
ULnew = copy_oftype(UL.data, Base._return_type($op, Tuple{eltype(UL), typeof(J.λ)}))
for i = 1:size(ULnew, 1)
ULnew[i,i] = ($op)(1, J.λ)
end
Expand All @@ -113,7 +113,7 @@ for (t1, t2) in ((:UnitUpperTriangular, :UpperTriangular),
end

function (-)(J::UniformScaling, UL::Union{UpperTriangular,UnitUpperTriangular})
ULnew = similar(parent(UL), Broadcast.combine_eltypes(-, J, UL))
ULnew = similar(parent(UL), Base._return_type(-, Tuple{typeof(J.λ), eltype(UL)}))
n = size(ULnew, 1)
ULold = UL.data
for j = 1:n
Expand All @@ -129,7 +129,7 @@ function (-)(J::UniformScaling, UL::Union{UpperTriangular,UnitUpperTriangular})
return UpperTriangular(ULnew)
end
function (-)(J::UniformScaling, UL::Union{LowerTriangular,UnitLowerTriangular})
ULnew = similar(parent(UL), Broadcast.combine_eltypes(-, J, UL))
ULnew = similar(parent(UL), Base._return_type(-, Tuple{typeof(J.λ), eltype(UL)}))
n = size(ULnew, 1)
ULold = UL.data
for j = 1:n
Expand All @@ -147,7 +147,7 @@ end

function (+)(A::AbstractMatrix, J::UniformScaling)
n = checksquare(A)
B = similar(A, Broadcast.combine_eltypes(+, A, J))
B = similar(A, Base._return_type(+, Tuple{eltype(A), typeof(J.λ)}))
copyto!(B,A)
@inbounds for i = 1:n
B[i,i] += J.λ
Expand All @@ -157,7 +157,7 @@ end

function (-)(A::AbstractMatrix, J::UniformScaling)
n = checksquare(A)
B = similar(A, Broadcast.combine_eltypes(-, A, J))
B = similar(A, Base._return_type(-, Tuple{eltype(A), typeof(J.λ)}))
copyto!(B, A)
@inbounds for i = 1:n
B[i,i] -= J.λ
Expand All @@ -166,7 +166,7 @@ function (-)(A::AbstractMatrix, J::UniformScaling)
end
function (-)(J::UniformScaling, A::AbstractMatrix)
n = checksquare(A)
B = convert(AbstractMatrix{Broadcast.combine_eltypes(-, J, A)}, -A)
B = convert(AbstractMatrix{Base._return_type(-, Tuple{typeof(J.λ), eltype(A)})}, -A)
@inbounds for j = 1:n
B[j,j] += J.λ
end
Expand Down
21 changes: 20 additions & 1 deletion test/broadcast.jl
Original file line number Diff line number Diff line change
Expand Up @@ -545,7 +545,7 @@ end
# Test that broadcast treats type arguments as scalars, i.e. containertype yields Any,
# even for subtypes of abstract array. (https://github.com/JuliaStats/DataArrays.jl/issues/229)
@testset "treat type arguments as scalars, DataArrays issue 229" begin
@test Broadcast.combine_styles(AbstractArray) == Broadcast.Unknown()
@test Broadcast.combine_styles(Broadcast.broadcastable(AbstractArray)) == Base.Broadcast.DefaultArrayStyle{0}()
@test broadcast(==, [1], AbstractArray) == BitArray([false])
@test broadcast(==, 1, AbstractArray) == false
end
Expand Down Expand Up @@ -578,6 +578,25 @@ end
[Set([1, 3]), Set([2, 3])])
end

# A bare bones custom type that supports broadcast
struct Foo26601{T}
data::T
end
Base.axes(f::Foo26601) = axes(f.data)
Base.getindex(f::Foo26601, i...) = getindex(f.data, i...)
Base.ndims(::Type{Foo26601{T}}) where {T} = ndims(T)
Base.Broadcast.broadcastable(f::Foo26601) = f
@testset "barebones custom object broadcasting" begin
for d in (rand(Float64, ()), rand(5), rand(5,5), rand(5,5,5))
f = Foo26601(d)
@test f .* 2 == d .* 2
@test f .* (1:5) == d .* (1:5)
@test f .* reshape(1:25,5,5) == d .* reshape(1:25,5,5)
@test sqrt.(f) == sqrt.(d)
@test f .* (1,2,3,4,5) == d .* (1,2,3,4,5)
end
end

@testset "broadcast resulting in tuples" begin
# Issue #21291
let t = (0, 1, 2)
Expand Down

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