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optimizedeinsum.jl's Issues

`ssa_greedy_optimize` crashes for non-empty `output`

When !isempty(output), target_inds_histogram dictionary does not contain keys from output indices due to line

target_inds = setdiff(unique(Iterators.flatten(values(remaining))), output)
# histogram of ocurrences of target indices
# i.e. a index can only be contracted if it only appears in 2 tensors
# if it appears in 3+, then it cannot be contracted (but indirect Hadamard products can)
target_inds_histogram = histogram(Iterators.filter((target_inds), Iterators.flatten(values(remaining))))

This makes the following code to crash.

for ind [a..., b...]
target_inds_histogram[ind] -= 1
end
for ind c
target_inds_histogram[ind] += 1
end

If we can be sure that output indices are gonna be open indices (not open hyperindices), then it could be easily solved by filtering output indices in [a..., b...] and c.

Replace Requires with Package Extensions

In Julia 1.9, Weak Dependencies and Package Dependencies are introduced. Functionality is similar to the one provided by Requires.jl but has the advantage of support for precompilation.

Regression on 3D visualization

Currently, it is not possible to have 3D visualization with the following code,

julia> using Makie
julia> using OptimizedEinsum;
julia> using CairoMakie
julia> output, inputs, size_dict = rand_equation(25, 4)
(Symbol[], [[:u, :Q, :k, :g, :M], [:c, :W, :t, :r, :J, :L, :T], [:S, :d, :N, :V, :G, :D], [:b, :c, :d], [:v, :f, :g, :y, :N], [:o, :A], [:h, :i, :x, :t, :w], [:U, :f], [:x, :o], [:s, :i, :L, :q, :W]    [:u, :m, :G], [:A, :e, :a], [:l, :k, :I], [:K, :E, :B, :H], [:h, :C, :e, :B], [:C, :s, :a], [:m, :I, :v], [:w, :T, :j], [:n, :P, :H, :y, :F], [:U, :S, :D, :O]], Dict(:j => 3, :D => 8, :S => 2, :X => 9, :x => 9, :R => 8, :A => 6, :k => 6, :d => 7, :g => 6))
julia> path = contractpath(RandomGreedy, inputs, output, size_dict)
ContractionPath([(9, 7), (3, 25), (16, 22), (17, 6), (5, 8), (11, 14), (10, 21), (27, 4), (28, 18), (29, 20)    (24, 13), (37, 32), (41, 2), (42, 19), (39, 33), (44, 12), (45, 31), (46, 40), (47, 15), (43, 48)], [[:u, :Q, :k, :g, :M], [:c, :W, :t, :r, :J, :L, :T], [:S, :d, :N, :V, :G, :D], [:b, :c, :d], [:v, :f, :g, :y, :N], [:o, :A], [:h, :i, :x, :t, :w], [:U, :f], [:x, :o], [:s, :i, :L, :q, :W]    [:u, :m, :G], [:A, :e, :a], [:l, :k, :I], [:K, :E, :B, :H], [:h, :C, :e, :B], [:C, :s, :a], [:m, :I, :v], [:w, :T, :j], [:n, :P, :H, :y, :F], [:U, :S, :D, :O]], Symbol[], Dict(:j => 3, :D => 8, :S => 2, :X => 9, :x => 9, :R => 8, :A => 6, :k => 6, :d => 7, :g => 6))
julia> using NetworkLayout
julia> plot(path; layout=Spring(dim=3))

Instead, it produces a standard 2D plot. The problem seems that the kwargs are not correctly passed to plot.

Function `plot` produces inadequate results for large contraction paths

Summary

The visualization function plot creates inadequate results for large contraction paths. Ideally, we would want the edges between the nodes to be further separated if the nodes are bigger.

Example

julia> using OptimizedEinsum; using Makie; using CairoMakie
[ Info: Precompiling OptimizedEinsum [c9cfed12-e746-47c4-860d-affc68c43467]
julia> output = Symbol[]
inSymbol[]
julia> inputs = [[:ą, :p, :ċ, :é, :ñ, :ž, :ƶ], [:Ǟ, :ś, :Ɖ, :x, :Ş, :Ě, :õ, :ǩ, :j], [:ǟ, :Ņ, :H], [:ų, :ě, :S, :ƒ, :ǁ, :Ƅ, :Ŀ], [:ĸ, :ŀ, :Š, :Č, :ħ, :V, :ť, :ń], [:Þ, :Ū, :ą, :Ƨ, :i, :B], [:ũ, :U, :ĝ, :R, :ǖ, :í], [:ċ, :Ǩ, :Ĵ, :ƪ, :Ɛ, :ƍ, :n, :Ŗ], [:c, :W, :Á, :ƙ, :ƭ, :Ǒ], [:ǔ, :ư, :d, :C, :o, :Nj, :ł], [:Ç, :t, :Đ, :Ə, :ī, :Ǝ, :Ő, :nj], [:Ǔ, :ƃ, :J, :r, :ƅ, :ú, :ž, :û, :Ē], [:U, :Û, :Ń, :ţ, :Y, :ƣ, :à, :Ĩ, :Ţ], [:ǣ, :Ć, :ś, :ƚ], [:Ǚ, :ĩ, :ǀ], [:Ǜ, :ă, :ņ, :ë, :è], [:ð, :â, :ǒ, :ħ, :ď], [:ƅ, :ǖ, :Ƥ, :ĕ, :k, :ƒ], [:Ö, :Ð, :À, :ǟ, :ƨ, :Ł, :Ƨ, :ƿ], [:Ĥ, :S, :ģ, :ƿ, :Ę], [:Ƭ, :t, :L, :Ú, :ã, :Ķ, :Ɓ, :đ, :ǥ, :ǝ, :d, :f, :ŵ], [:Ŀ, :ſ, :ƈ, :Ą, :ř, :Ľ], [:ē, :I, :z, :ó, :ǂ, :İ], [:IJ, :Ƶ, :Ǥ], [:x, :LJ, :æ, :ƭ, :Q, :Ő, :Ƽ, :ŀ, :ó, :e, :ƕ], [:Ƭ, :ǐ, :Ŧ, :ƫ, :ǣ, :ƀ, :ǩ, :E], [:Ŕ, :Ø, :Ư, :Ʈ, :ƹ, :Ǔ, :Ō, :Ɯ, :ă], [:ű, :ė, :Ǡ, :o, :ƥ, :ƞ, :æ], [:Ğ, :Â, :Ʈ, :Ĺ, :Ž], [:Ñ, :Ť, :é, :Ð, :P], [:V, :ŗ, :nj, :ż, :Ė, :Ġ, :ø, :y], [:ŏ, :Ż, :ǚ, :ŧ, :Ƽ, :ê, :Ă, :ū], [:Ë, :ġ, :ğ, :Ɩ, :s, :v, :DŽ], [:Ʋ, :Ɵ, :q, :ǡ, :ţ, :Ɖ, :ĥ, :A, :ù, :â], [:ǁ, :Ɔ, :Ʋ, :ŗ, :ķ], [:Į, :ğ, :ǃ, :Ñ, :Ŝ, :ò, :ń, :î], [:ć, :ǎ, :Ê], [:Ž, :÷, :Ƌ, :ŕ, :Ɣ, :ĺ, :b, :f], [:n, :È, :Ř, :ş, :ƨ, :Ǧ, :ô, :ĵ], [:Ŏ, :å, :Õ, :Ć, :ǘ, :M, :Ĭ, :Ǣ], [:y, :ď, :ü, :Ń, :Dž, :Æ], [:Å, :Ħ, :ł, :ŕ, :ő, :ġ], [:Ę, :Ã, :ǀ, :ű, :ƈ, :Ô, :ƻ, :Ū], [:×, :G, :Ǖ, :ŭ, :Ǧ, :Ů], [:Ĺ, :u, :ĕ, :ƥ, :Ā, :Ċ], [:u, :w, :ā, :Ġ, :Ɠ, :ı, :à], [:Ģ, :ë, :Ŕ, :Ś, :Ɯ, :Œ, :Ô, :a], [:ŏ, :dž, :í, :Ţ, :ƕ, :Č, :ģ, :l, :Ļ], [:Ʀ, :C, :ļ, :ĸ, :ƺ, :ĝ], [:Ě, :ƛ, :Â, :r, :M, :Ɨ, :Ũ, :ƣ], [:Ŏ, :Ĝ, :ʼn, :ƻ, :Ƃ, :Þ], [:ę, :ÿ, :Ɠ, :þ, :ö], [:dž, :ß, :X, :ì, :ĭ, :z, :č], [:Ğ, :ŭ, :h, :Ó, :Ŭ, :į, :Ĉ, :Ù], [:Ʊ, :ƽ, :Ɗ, :ï, :ķ], [:ĭ, :÷, :Ö, :č, :ŷ, :ê, :ĩ], [:Ý, :Ǐ, :Q, :Ă, :Ó, :ǘ, :Ƙ], [:ľ, :×, :Ň, :Ŵ, :ż], [:Ī, :N, :Ù, :Ň, :ò, :Ů, :G, :ij], [:ī, :ü, :B, :Ǐ, :ı, :ū, :Ƈ, :š, :Ĉ], [:Ď, :e, :Ò, :ö, :Ɩ, :l, :þ, :D, :Ʀ, :Į, :Ä, :Ǖ, :X], [:ý, :Ƒ, :Ŗ, :Ŷ, :Ƶ, :ā], [:Ɲ, :ä, :ş, :Ų, :Ǎ, :Ƈ], [:w, :ň, :ǚ, :Ơ, :ř, :Ï, :Ź], [:ƞ, :g, :ļ, :NJ, :ŋ, :Ï, :œ], [:Ɣ, :ť, :Ō, :Ĝ, :Ǒ, :Œ, :ň, :j], [:Ĕ, :Ķ, :g, :ě, :Ƃ, :Ŭ, :ƍ, :õ, :m], [:ç, :Ė, :DŽ, :ĥ, :ƌ, :š, :v, :Ë, :Nj], [:Ƣ, :å, :ź, :Ű, :À, :Ş, :IJ, :H, :Á, :Ĭ], [:Í, :Ÿ, :ĺ, :ē, :Ƣ], [:Ǫ, :î, :F, :ù, :Å, :ŧ], [:ĵ, :œ, :ƪ, :ć, :Ģ, :Ǝ, :Ǩ], [:ƴ, :Ê, :Ǣ, :ő, :F, :ÿ, :Ɔ, :Ü, :Ǡ, :Ʃ], [:ơ, :c, :Ã, :ņ, :É, :Í, :Ĵ], [:ƫ, :ơ, :Ŋ, :ǒ, :ǡ, :Î, :LJ, :Đ], [:ė, :Ź, :Ƙ, :Ɵ, :ƀ], [:k, :ľ, :Æ, :Ǫ, :Ś], [:ƺ, :ō, :Ý, :Ʒ, :K, :Ā, :Ú, :Ť], [:Ʃ, :L, :ƚ, :T], [:ę, :Ì, :ƾ, :ǜ], [:T, :Ɓ, :Ƴ, :Ü, :Ə, :h, :Ʊ], [:ǧ, :ǔ, :Ƒ, :NJ, :ij], [:ũ, :ß, :ǝ, :O], [:ǥ, :ä, :D, :Ŵ, :Ř, :ƾ], [:Ą, :R, :ŝ, :Ǎ, :ø, :ǧ], [:Ħ, :Ǟ, :A, :ĉ, :Ĩ, :ƽ, :ư, :Ɗ, :Ɨ], [:Ŋ, :ƴ, :Ƥ, :Ÿ, :ǜ, :ō], [:I, :K, :Ĥ, :Î, :ð, :s, :ô], [:Lj, :P, :ñ, :Ɛ, :ŵ, :Ø, :a], [:J, :è, :Ƴ, :ƛ, :Ű, :Ǚ, :b, :ź, :đ, :Ä, :Ǘ], [:Õ, :û, :Ŧ, :Ŝ, :Lj, :ï], [:Ď, :ſ, :Ɲ], [:Ŷ, :ŷ, :E, :İ, :Ƹ, :É, :ƙ, :Ļ, :Ē, :lj, :ƃ], [:Û, :ǐ, :ǎ, :Ľ, :ʼn, :W, :Ư], [:ì, :ú, :i, :Ơ, :q, :ǃ, :Ĕ, :Ƹ], [:ŝ, :Ż, :ĉ, :á, :m, :Š, :ƶ], [:lj, :N, :ã, :ç, :Dž], [:Ƅ, :O, :Ʒ, :Ì, :Ƌ, :ý], [:Ç, :È, :Ł, :Ǜ, :Ǘ, :Ī, :Ų, :Ǥ, :ǂ, :Y, :ų, :ů], [:Ņ, :á, :ƹ, :Ũ, :p, :į, :ŋ, :ƌ, :ů, :Ċ, :Ò]]
100-element Vector{Vector{Symbol}}:
 [, :p, , , , , ]
 [, , , :x, , , , , :j]
 [, , :H]
 [, , :S, , , , :Ŀ]
 [, , , , , :V, , ]
 [, , , , :i, :B]
 [, :U, , :R, , ]
 [, , , , , , :n, ]
 [:c, :W, , , , ]
 
 [, :ſ, ]
 [, , :E, , , , , , , , ]
 [, , , , , :W, ]
 [, , :i, , :q, , , ]
 [, , , , :m, , ]
 [, :N, , , ]
 [, :O, , , , ]
 [, , , , , , , , , :Y, , ]
 [, , , , :p, , , , , , ]
julia> size_dict = Dict(:Á => 7, :Ű => 3, :Ɔ => 7, :ʼn => 9, :ǚ => 3, :Š => 6, :ƃ => 9, :Ǟ => 7, :Ė => 4, :ĝ => 3, :Ľ => 7, :Ŷ => 7, :m => 5, :ű => 4, :Ĉ => 5, :Ŏ => 5, :ś => 8, :Ƨ => 4, :æ => 6, :e => 9, :Ô => 8, :Ü => 3, :Ð => 4, :Ǔ => 7, :Ɣ => 8, :Ĺ => 8, :à => 3, :Ƈ => 9, :ō => 4, :þ => 3, :Ə => 3, :ƅ => 9, :ħ => 6, :Ħ => 7, :È => 6, :ŋ => 9, :Õ => 8, :ď => 6, :Ǝ => 5, :ŧ => 8, :ť => 2, :ĉ => 9, :lj => 4, :Ǐ => 7, :Ɵ => 3, :ï => 8, :Ɨ => 2, :X => 5, :Ò => 2, :ĺ => 4, :Ǎ => 4, :x => 2, :ñ => 9, :ŗ => 5, :ă => 3, :A => 2, :ų => 4, :Ư => 3, :í => 7, :Ǒ => 8, :ą => 9, :œ => 9, :à => 9, :Ŀ => 2, :b => 9, :ż => 3, :ň => 9, :n => 2, :Ÿ => 9, :l => 7, :w => 9, :ì => 3, :Ƭ => 8, :ã => 9, :ģ => 2, :Ɗ => 3, :ł => 2, :Ñ => 2, :ĥ => 5, :ƫ => 3, :ž => 8, :Ĕ => 4, :f => 7, :ě => 8, :P => 5, :H => 8, :Ń => 6, :Ć => 3, :ĸ => 2, :ǥ => 3, :õ => 2, :ó => 2, :Dž => 9, :Ŭ => 6, :Ʃ => 7, :ī => 7, :ô => 2, :š => 7, :Ý => 8, :ƶ => 4, :d => 5, :ċ => 6, :Ņ => 5, :Ź => 5, :ƿ => 2, :Ě => 9, :y => 7, :ŝ => 6, :LJ => 9, :Œ => 3, :ƣ => 6, :Ē => 2, :ÿ => 3, :F => 6, :ŏ => 5, :ǟ => 8, :c => 2, :ū => 7, :Ä => 7, :ā => 3, :Ğ => 5, :Ƙ => 3, :Ǫ => 6, :Ċ => 7, :Æ => 3, :č => 3, :ŕ => 3, :M => 3, :Ă => 3, :s => 6, :Ɠ => 5, :Q => 3, :Ŧ => 8, :z => 6, :Ŗ => 6, :Å => 3, :Ĵ => 6, :Ƣ => 9, :ƥ => 6, :ğ => 9, :ƺ => 3, :ƛ => 8, :C => 6, :Ǖ => 3, :ı => 9, :j => 6, :û => 7, :Û => 8, :ơ => 6, :á => 6, :Ķ => 7, :ƒ => 7, :Ú => 2, :ƀ => 8, :Ŕ => 5, :ļ => 7, :ġ => 6, :Ɛ => 5, :Ő => 6, :Ʋ => 3, :r => 2, :Ų => 6, :ƍ => 3, :Ĩ => 7, :ư => 7, :Ƽ => 2, :ņ => 3, :Nj => 7, :Ʊ => 4, :Ƥ => 3, :h => 5, :Ø => 7, :× => 8, :K => 7, :ij => 6, : => 6, :ö => 7, :Ģ => 9, :ø => 7, :Ç => 4, :â => 7, :IJ => 2, :ƹ => 8, :Ĝ => 6, :ǝ => 5, :Ł => 9, :ź => 3, :À => 8, :ǜ => 3, :ù => 8, :dž => 5, :ƽ => 3, :É => 3, :Ƹ => 3, :Ļ => 5, :÷ => 7, :ǡ => 3, :ǒ => 3, :S => 3, :Ǜ => 2, :ƻ => 5, :R => 3, :Ĥ => 6, :ǘ => 8, :k => 6, :ŵ => 5, :Ƃ => 3, :ƪ => 5, :Í => 5, :Þ => 9, :Ĭ => 5, :W => 5, :Ġ => 8, :Ž => 9, :O => 6, :ē => 8, :ǁ => 9, :Į => 8, :ƨ => 7, :N => 5, :ð => 6, :ê => 2, :Ŵ => 3, :ę => 4, :Y => 2, :ƾ => 2, :å => 7, :ǔ => 3, :Ū => 2, :ǧ => 8, :Ą => 3, :ŷ => 3, :ő => 7, :ƚ => 9, :Ň => 2, :Ǧ => 3, :Ơ => 8, :nj => 9, :ä => 2, :Ɩ => 2, :T => 3, :Ʒ => 8, :a => 5, :ǣ => 7, :Ù => 4, :Ā => 9, :ç => 8, :Ţ => 2, :Lj => 3, :Ʈ => 7, :B => 4, :Ǘ => 5, :Ƅ => 2, :Ō => 6, :E => 9, :ƙ => 5, :q => 8, :ė => 3, :Ö => 8, :ǂ => 3, :Ď => 7, :Ɖ => 7, :t => 7, :ř => 2, :D => 7, :Ī => 9, :Ƴ => 9, :ĵ => 5, :Ƶ => 6, :ƭ => 5, :ũ => 3, :ú => 9, :Ů => 4, :Ǥ => 6, :Î => 5, :ý => 9, :ķ => 4, :Ť => 3, :ſ => 2, :o => 4, :p => 3, :ò => 5, :Ó => 4, :ƌ => 8, :Ś => 8, :é => 3, :ƕ => 5, :ń => 9, :Ê => 5, :Ǣ => 9, :ĩ => 8, :ë => 9, :Ƌ => 8, :è => 3, :v => 6, :İ => 9, :î => 9, :I => 5, :ü => 9, :G => 3, :Ǡ => 3, :ŭ => 8, :Ż => 2, :L => 5, :ŀ => 9, :ß => 6, :ǩ => 3, :ƴ => 2, :Ř => 2, :Ë => 9, :Ì => 9, :đ => 9, :ǖ => 9, :ľ => 7, :ǎ => 9, :ǀ => 7, :į => 9, :DŽ => 2, :Ŝ => 8, :Ɓ => 7, :Ŋ => 4, :g => 9, :u => 5, :Ɲ => 2, :Ş => 8, :U => 5, :ş => 6, :J => 3, :Č => 9, :i => 6, :ĕ => 9, :ţ => 3, :ƞ => 6, :V => 5, :ĭ => 6, :Ɯ => 8, :ǃ => 6, :Đ => 9, :ǐ => 8, :ů => 2, :Ũ => 8, :Ƒ => 5, :ƈ => 9, :Ʀ => 4, :Ï => 6, :ć => 7, :NJ => 7, :Ǚ => 4, :Ę => 6, :Ǩ => 5)
Dict{Symbol, Int64} with 350 entries:
   => 7
   => 3
   => 7
   => 9
   => 3
   => 6
   => 9
   => 7
   => 4
   => 3
   => 7
   => 7
  :m => 5
   => 4
   => 5
   => 5
   => 8
   => 4
    => 
julia> path_greedy = contractpath(Greedy, inputs, output, size_dict)
ContractionPath(o[(92, 61), (79, 14), (52, 80), (62, 24), (58, 84), (56, 15), (35, 55), (87, 70), (7, 83), (16, 74)  …  (189, 65), (190, 113), (191, 115), (192, 47), (193, 54), (194, 31), (116, 26), (196, 195), (197, 13), (67, 198)], [[:ą, :p, :ċ, :é, :ñ, :ž, :ƶ], [:Ǟ, :ś, :Ɖ, :x, :Ş, :Ě, :õ, :ǩ, :j], [:ǟ, :Ņ, :H], [:ų, :ě, :S, :ƒ, :ǁ, :Ƅ, :Ŀ], [:ĸ, :ŀ, :Š, :Č, :ħ, :V, :ť, :ń], [:Þ, :Ū, :ą, :Ƨ, :i, :B], [:ũ, :U, :ĝ, :R, :ǖ, :í], [:ċ, :Ǩ, :Ĵ, :ƪ, :Ɛ, :ƍ, :n, :Ŗ], [:c, :W, :Á, :ƙ, :ƭ, :Ǒ], [:ǔ, :ư, :d, :C, :o, :Nj, :ł]  …  [:Õ, :û, :Ŧ, :Ŝ, :Lj, :ï], [:Ď, :ſ, :Ɲ], [:Ŷ, :ŷ, :E, :İ, :Ƹ, :É, :ƙ, :Ļ, :Ē, :lj, :ƃ], [:Û, :ǐ, :ǎ, :Ľ, :ʼn, :W, :Ư], [:ì, :ú, :i, :Ơ, :q, :ǃ, :Ĕ, :Ƹ], [:ŝ, :Ż, :ĉ, :á, :m, :Š, :ƶ], [:lj, :N, :ã, :ç, :Dž], [:Ƅ, :O, :Ʒ, :Ì, :Ƌ, :ý], [:Ç, :È, :Ł, :Ǜ, :Ǘ, :Ī, :Ų, :Ǥ, :ǂ, :Y, :ų, :ů], [:Ņ, :á, :ƹ, :Ũ, :p, :į, :ŋ, :ƌ, :ů, :Ċ, :Ò]], Symbol[], Dict(:Á => 7, :Ű => 3, :Ɔ => 7, :ʼn => 9, :ǚ => 3, :Š => 6, :ƃ => 9, :Ǟ => 7, :Ė => 4, :ĝ => 3…))
julia> plot(path_greedy)

Output:
image

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Interactive plots

Makie (and GraphMakie) allow registering interactive callbacks to plots such that nodes or edges are highlighted, a popup with more info gets displayed, ...

For this you need an interactive backend (i.e. GLMakie or WGLMakie).

I have been unsuccessful.

Lazy load plotting support

Wait for Package extensions on Julia 1.9

We can also use Requires.jl if we need to support Julia <=1.8

Improve plot design

Plots of ContractionPath would look more awesome if we could get rid of the grid and the axis lines (do not apply to our plots), and add a color bar.

@jofrevalles could you take a look at this? We might want to do the same later in Tenet.

Random crashes on `ssa_greedy_optimize`

Sometimes, randomly, when I create a random tensor network (with rand_equation) and find a contraction path using the Greedy solver, it crashes.

Example

using OptimizedEinsum
output, inputs, size_dict = rand_equation(100, 3)
path = contractpath(Greedy, inputs, output, size_dict)

Stacktrace

path = optimize(Greedy, inputs, output, size_dict)
ERROR: MethodError: Cannot `convert` an object of type Int64 to an object of type Set{Symbol}
Closest candidates are:
  convert(::Type{T}, ::T) where T<:AbstractSet at set.jl:475
  convert(::Type{T}, ::AbstractSet) where T<:AbstractSet at set.jl:476
  convert(::Type, ::GeoInterface.AbstractGeometryTrait, ::Any) at ~/.julia/packages/GeoInterface/J298z/src/fallbacks.jl:112
  ...
Stacktrace:
  [1] setindex!(h::Dict{Int64, Set{Symbol}}, v0::Int64, key::Int64)
    @ Base ./dict.jl:382
  [2] (::OptimizedEinsum.Optimizers.var"#4#10"{Dict{Int64, Set{Symbol}}, Vector{Tuple{Int64, Int64}}})(::Tuple{Int64, Set{Symbol}}, ::Tuple{Int64, Set{Symbol}})
    @ OptimizedEinsum.Optimizers ~/Workspace/OptimizedEinsum.jl/src/Optimizers/Greedy.jl:70
  [3] BottomRF
    @ ./reduce.jl:81 [inlined]
  [4] FilteringRF
    @ ./reduce.jl:107 [inlined]
  [5] _foldl_impl(op::Base.FilteringRF{ComposedFunction{Base.Fix2{typeof(isequal), Set{Symbol}}, typeof(last)}, Base.BottomRF{OptimizedEinsum.Optimizers.var"#4#10"{Dict{Int64, Set{Symbol}}, Vector{Tuple{Int64, Int64}}}}}, init::Base._InitialValue, itr::Base.Iterators.Enumerate{Vector{Set{Symbol}}})
    @ Base ./reduce.jl:62
  [6] foldl_impl
    @ ./reduce.jl:48 [inlined]
  [7] mapfoldl_impl(f::typeof(identity), op::OptimizedEinsum.Optimizers.var"#4#10"{Dict{Int64, Set{Symbol}}, Vector{Tuple{Int64, Int64}}}, nt::Base._InitialValue, itr::Base.Iterators.Filter{ComposedFunction{Base.Fix2{typeof(isequal), Set{Symbol}}, typeof(last)}, Base.Iterators.Enumerate{Vector{Set{Symbol}}}})
    @ Base ./reduce.jl:44
  [8] mapfoldl(f::Function, op::Function, itr::Base.Iterators.Filter{ComposedFunction{Base.Fix2{typeof(isequal), Set{Symbol}}, typeof(last)}, Base.Iterators.Enumerate{Vector{Set{Symbol}}}}; init::Base._InitialValue)
    @ Base ./reduce.jl:170
  [9] mapfoldl
    @ ./reduce.jl:170 [inlined]
 [10] #mapreduce#263
    @ ./reduce.jl:302 [inlined]
 [11] mapreduce
    @ ./reduce.jl:302 [inlined]
 [12] #reduce#265
    @ ./reduce.jl:483 [inlined]
 [13] reduce(op::Function, itr::Base.Iterators.Filter{ComposedFunction{Base.Fix2{typeof(isequal), Set{Symbol}}, typeof(last)}, Base.Iterators.Enumerate{Vector{Set{Symbol}}}})
    @ Base ./reduce.jl:483
 [14] ssa_greedy_optimize(inputs::Vector{Vector{Symbol}}, output::Vector{Symbol}, size::Dict{Symbol, Int64}, choose_fn::typeof(OptimizedEinsum.Optimizers.greedy_choose_simple!), cost_fn::typeof(removedsize))
    @ OptimizedEinsum.Optimizers ~/Workspace/OptimizedEinsum.jl/src/Optimizers/Greedy.jl:65
 [15] optimize(config::Greedy, inputs::Vector{Vector{Symbol}}, output::Vector{Symbol}, size::Dict{Symbol, Int64})
    @ OptimizedEinsum.Optimizers ~/Workspace/OptimizedEinsum.jl/src/Optimizers/Greedy.jl:25
 [16] optimize(::Type{Greedy}, ::Vector{Vector{Symbol}}, ::Vector{Symbol}, ::Dict{Symbol, Int64})
    @ OptimizedEinsum.Optimizers ~/Workspace/OptimizedEinsum.jl/src/Optimizers/Greedy.jl:20
 [17] top-level scope
    @ REPL[3]:1

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