Fix ndims for Broadcasted with no args.
#45477
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And some code clean.
New `_maxndims` is based on `tuple_type_tail`, thus improve the inference result.
N5N3
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May 27, 2022
vtjnash
reviewed
May 27, 2022
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| function _maxndims(Args::Type{<:Tuple{T,Vararg{Any}}}) where {T} | ||
| Argstail = Tuple{ntuple(i -> fieldtype(Args, i + 1), fieldcount(Args) - 1)...} | ||
| max(_maxndims(Tuple{T}), _maxndims(Argstail)) | ||
| end |
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This seems like generally a somewhat worse model for what Types can be present than the reduce it replaces
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This is just a type version of tuple’s fold.
Since it makes nested Broadcasted easier to inference, can I say our compiler “prefers” this style?😂
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The `N<:Integer` constraint was nonsensical, given that `(N === Any) || (N isa Int)`. N5N3 noticed this back in 2022: JuliaLang#44061 (comment) Follow up on JuliaLang#44061. Also xref JuliaLang#45477.
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The `N<:Integer` constraint was nonsensical, given that `(N === Any) || (N isa Int)`. N5N3 noticed this back in 2022: JuliaLang#44061 (comment) Follow up on JuliaLang#44061. Also xref JuliaLang#45477.
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The `N<:Integer` constraint was nonsensical, given that `(N === Any) || (N isa Int)`. N5N3 noticed this back in 2022: JuliaLang#44061 (comment) Follow up on JuliaLang#44061. Also xref JuliaLang#45477.
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The `N<:Integer` constraint was nonsensical, given that `(N === Any) || (N isa Int)`. N5N3 noticed this back in 2022: JuliaLang#44061 (comment) Follow up on JuliaLang#44061. Also xref JuliaLang#45477.
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The `N<:Integer` constraint was nonsensical, given that `(N === Any) || (N isa Int)`. N5N3 noticed this back in 2022: #44061 (comment) Follow up on #44061. Also xref #45477.
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The `N<:Integer` constraint was nonsensical, given that `(N === Any) || (N isa Int)`. N5N3 noticed this back in 2022: #44061 (comment) Follow up on #44061. Also xref #45477. (cherry picked from commit d3964b6)
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…aLang#56999) The `N<:Integer` constraint was nonsensical, given that `(N === Any) || (N isa Int)`. N5N3 noticed this back in 2022: JuliaLang#44061 (comment) Follow up on JuliaLang#44061. Also xref JuliaLang#45477. (cherry picked from commit d3964b6)
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Follow up #44061.
This PR makes
collect(Base.broadcast(randn))works correctly, and improve the inference result.Test added.