Switch to texthighlighter to unbreak profile

[kshyatt]

Hopefully this works

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diff --git a/src/profile.jl b/src/profile.jl
index a276fff90..a82ba7c66 100644
--- a/src/profile.jl
+++ b/src/profile.jl
@@ -660,15 +660,21 @@ function Base.show(io::IO, results::ProfileResults)
         p75 = quantile(relevant_times, 0.75)
         p95 = quantile(relevant_times, 0.95)
 
-        highlight_p95 = TextHighlighter((data, i, j) -> (names(data)[j] == "time") &&
-                                                        (data[i,j] >= p95),
-                                        crayon"red")
-        highlight_p75 = TextHighlighter((data, i, j) -> (names(data)[j] == "time") &&
-                                                        (data[i,j] >= p75),
-                                        crayon"yellow")
-        highlight_bold = TextHighlighter((data, i, j) -> (names(data)[j] == "name") &&
-                                                         (data[!, :time][i] >= p75),
-                                         crayon"bold")
+            highlight_p95 = TextHighlighter(
+                (data, i, j) -> (names(data)[j] == "time") &&
+                    (data[i, j] >= p95),
+                crayon"red"
+            )
+            highlight_p75 = TextHighlighter(
+                (data, i, j) -> (names(data)[j] == "time") &&
+                    (data[i, j] >= p75),
+                crayon"yellow"
+            )
+            highlight_bold = TextHighlighter(
+                (data, i, j) -> (names(data)[j] == "name") &&
+                    (data[!, :time][i] >= p75),
+                crayon"bold"
+            )
 
         (highlight_p95, highlight_p75, highlight_bold)
     end
@@ -829,9 +835,9 @@ function Base.show(io::IO, results::ProfileResults)
                 end
             end
             highlighters = time_highlighters(df)
-            highlighters = isempty(highlighters) ? PrettyTables.TextHighlighter[] : collect(highlighters)
-            pretty_table(io, df; column_labels=header, alignment, formatters=[formatters], highlighters)#,
-                                 #body_hlines=trace_divisions)
+                highlighters = isempty(highlighters) ? PrettyTables.TextHighlighter[] : collect(highlighters)
+                pretty_table(io, df; column_labels = header, alignment, formatters = [formatters], highlighters) #,
+                #body_hlines=trace_divisions)
         else
             df = summarize_trace(df)
 
@@ -845,7 +851,7 @@ function Base.show(io::IO, results::ProfileResults)
             header = [summary_column_names[name] for name in names(df)]
             alignment = [name in ["name", "time_dist"] ? :l : :r for name in names(df)]
             highlighters = time_highlighters(df)
-            pretty_table(io, df; column_labels=header, alignment, formatters=[summary_formatter(df)], highlighters=collect(highlighters))
+                pretty_table(io, df; column_labels = header, alignment, formatters = [summary_formatter(df)], highlighters = collect(highlighters))
         end
     end
 
@@ -930,8 +936,8 @@ function Base.show(io::IO, results::ProfileResults)
                 end
             end
             highlighters = time_highlighters(df)
-            pretty_table(io, df; column_labels=header, alignment, formatters=[formatters], highlighters=collect(highlighters),)
-                                 #body_hlines=trace_divisions)
+                pretty_table(io, df; column_labels = header, alignment, formatters = [formatters], highlighters = collect(highlighters))
+                #body_hlines=trace_divisions)
         else
             df = summarize_trace(results.device)
 
@@ -945,7 +951,7 @@ function Base.show(io::IO, results::ProfileResults)
             header = [summary_column_names[name] for name in names(df)]
             alignment = [name in ["name", "time_dist"] ? :l : :r for name in names(df)]
             highlighters = time_highlighters(df)
-            pretty_table(io, df; column_labels=header, alignment, formatters=[summary_formatter(df)], highlighters=collect(highlighters))
+                pretty_table(io, df; column_labels = header, alignment, formatters = [summary_formatter(df)], highlighters = collect(highlighters))
         end
     end
 
@@ -982,7 +988,7 @@ function Base.show(io::IO, results::ProfileResults)
             for color in unique(df.color)
                 if color !== nothing
                     ids = df[df.color .== color, :id]
-                    highlighter = TextHighlighter(Crayon(; foreground=color)) do data, i, j
+                        highlighter = TextHighlighter(Crayon(; foreground = color)) do data, i, j
                         names(data)[j] in ["name", "domain"] && data[!, :id][i] in ids
                     end
                     push!(color_highlighters, highlighter)
@@ -1003,7 +1009,7 @@ function Base.show(io::IO, results::ProfileResults)
                 end
             end
             highlighters = tuple(color_highlighters..., time_highlighters(df)...)
-            pretty_table(io, df; column_labels=header, alignment, formatters=[formatters], highlighters=collect(highlighters))
+                pretty_table(io, df; column_labels = header, alignment, formatters = [formatters], highlighters = collect(highlighters))
         else
             # merge the domain and name into a single column
             nvtx_ranges.name = map(nvtx_ranges.name, nvtx_ranges.domain) do name, domain
@@ -1026,7 +1032,7 @@ function Base.show(io::IO, results::ProfileResults)
             header = [summary_column_names[name] for name in names(df)]
             alignment = [name in ["name", "time_dist"] ? :l : :r for name in names(df)]
             highlighters = time_highlighters(df)
-            pretty_table(io, df; column_labels=header, alignment, formatters=[summary_formatter(df)], highlighters=collect(highlighters))
+                pretty_table(io, df; column_labels = header, alignment, formatters = [summary_formatter(df)], highlighters = collect(highlighters))
         end
     end
 
diff --git a/test/core/profile.jl b/test/core/profile.jl
index 84b22e96c..f0dfd8e93 100644
--- a/test/core/profile.jl
+++ b/test/core/profile.jl
@@ -53,25 +53,25 @@ end
 let
     str = string(CUDA.@profile trace=true raw=true @cuda identity(nothing))
 
-    @test_broken occursin("cuLaunchKernel", str)
-    @test_broken occursin("identity()", str)
+                @test_broken occursin("cuLaunchKernel", str)
+                @test_broken occursin("identity()", str)
 
     @test occursin("ID", str)
 
-    @test_broken occursin("cuCtxSynchronize", str)
+                @test_broken occursin("cuCtxSynchronize", str)
 end
 
 # benchmarked profile
 let
     str = string(CUDA.@bprofile @cuda identity(nothing))
-    @test_broken occursin("cuLaunchKernel", str)
-    @test_broken occursin("identity()", str)
+                @test_broken occursin("cuLaunchKernel", str)
+                @test_broken occursin("identity()", str)
     @test !occursin("cuCtxGetCurrent", str)
 
     str = string(CUDA.@bprofile raw=true @cuda identity(nothing))
-    @test_broken occursin("cuLaunchKernel", str)
-    @test_broken occursin("identity()", str)
-    @test_broken occursin("cuCtxGetCurrent", str)
+                @test_broken occursin("cuLaunchKernel", str)
+                @test_broken occursin("identity()", str)
+                @test_broken occursin("cuCtxGetCurrent", str)
 end
 
 if CUPTI.version() != v"13.0.0" # NVIDIA/NVTX#125

[maleadt]

I've done #2892 first. Let's bump the compat in here then?

[github-actions]

CUDA.jl Benchmarks

Benchmark suite	Current: 1a584e5	Previous: 6c6977f	Ratio
latency/precompile	57159963125.5 ns	43775122238.5 ns	1.31
latency/ttfp	7935287212.5 ns	7276778491 ns	1.09
latency/import	4442786891 ns	3836255124 ns	1.16
integration/volumerhs	9625884 ns	9623790.5 ns	1.00
integration/byval/slices=1	147010 ns	146826 ns	1.00
integration/byval/slices=3	425844 ns	426011 ns	1.00
integration/byval/reference	145015 ns	145073 ns	1.00
integration/byval/slices=2	286522 ns	286240 ns	1.00
integration/cudadevrt	103581 ns	103460 ns	1.00
kernel/indexing	14168 ns	14196 ns	1.00
kernel/indexing_checked	14990 ns	15033 ns	1.00
kernel/occupancy	688.9271523178808 ns	670.506329113924 ns	1.03
kernel/launch	2204 ns	2162.5555555555557 ns	1.02
kernel/rand	14862 ns	16555 ns	0.90
array/reverse/1d	19807 ns	19646 ns	1.01
array/reverse/2dL_inplace	66861 ns	66804 ns	1.00
array/reverse/1dL	69952 ns	69923 ns	1.00
array/reverse/2d	21989.5 ns	21677 ns	1.01
array/reverse/1d_inplace	9652 ns	9658 ns	1.00
array/reverse/2d_inplace	13355 ns	13323 ns	1.00
array/reverse/2dL	73988.5 ns	73803 ns	1.00
array/reverse/1dL_inplace	66823 ns	66812 ns	1.00
array/copy	20216 ns	20306 ns	1.00
array/iteration/findall/int	156845.5 ns	157164 ns	1.00
array/iteration/findall/bool	139096 ns	139633 ns	1.00
array/iteration/findfirst/int	160778.5 ns	160554.5 ns	1.00
array/iteration/findfirst/bool	161828 ns	160957 ns	1.01
array/iteration/scalar	71596 ns	72124 ns	0.99
array/iteration/logical	214030 ns	215036.5 ns	1.00
array/iteration/findmin/1d	49953 ns	49445 ns	1.01
array/iteration/findmin/2d	96065 ns	96493.5 ns	1.00
array/reductions/reduce/Int64/1d	42860 ns	42960 ns	1.00
array/reductions/reduce/Int64/dims=1	46518 ns	44742.5 ns	1.04
array/reductions/reduce/Int64/dims=2	61329 ns	61453 ns	1.00
array/reductions/reduce/Int64/dims=1L	89026 ns	88951 ns	1.00
array/reductions/reduce/Int64/dims=2L	87704 ns	88014.5 ns	1.00
array/reductions/reduce/Float32/1d	36194 ns	35769 ns	1.01
array/reductions/reduce/Float32/dims=1	41670 ns	51586 ns	0.81
array/reductions/reduce/Float32/dims=2	59747 ns	59511 ns	1.00
array/reductions/reduce/Float32/dims=1L	52356 ns	52474 ns	1.00
array/reductions/reduce/Float32/dims=2L	71675 ns	71419 ns	1.00
array/reductions/mapreduce/Int64/1d	42980 ns	43189 ns	1.00
array/reductions/mapreduce/Int64/dims=1	53350 ns	46540.5 ns	1.15
array/reductions/mapreduce/Int64/dims=2	61617 ns	61279.5 ns	1.01
array/reductions/mapreduce/Int64/dims=1L	88923 ns	88854 ns	1.00
array/reductions/mapreduce/Int64/dims=2L	88079 ns	88014 ns	1.00
array/reductions/mapreduce/Float32/1d	35901 ns	36287 ns	0.99
array/reductions/mapreduce/Float32/dims=1	41785 ns	41466 ns	1.01
array/reductions/mapreduce/Float32/dims=2	60179 ns	59744 ns	1.01
array/reductions/mapreduce/Float32/dims=1L	52687 ns	52550 ns	1.00
array/reductions/mapreduce/Float32/dims=2L	72062.5 ns	71985 ns	1.00
array/broadcast	20288 ns	20047 ns	1.01
array/copyto!/gpu_to_gpu	12774 ns	11191 ns	1.14
array/copyto!/cpu_to_gpu	214743 ns	213964 ns	1.00
array/copyto!/gpu_to_cpu	284572 ns	284661.5 ns	1.00
array/accumulate/Int64/1d	125238 ns	124888 ns	1.00
array/accumulate/Int64/dims=1	83053 ns	83130 ns	1.00
array/accumulate/Int64/dims=2	157577 ns	157680 ns	1.00
array/accumulate/Int64/dims=1L	1708697 ns	1709578 ns	1.00
array/accumulate/Int64/dims=2L	965843 ns	966045 ns	1.00
array/accumulate/Float32/1d	109037 ns	108910 ns	1.00
array/accumulate/Float32/dims=1	80484 ns	80564 ns	1.00
array/accumulate/Float32/dims=2	147354 ns	147715 ns	1.00
array/accumulate/Float32/dims=1L	1618546 ns	1618612 ns	1.00
array/accumulate/Float32/dims=2L	698010 ns	698318 ns	1.00
array/construct	1261.4 ns	1287.5 ns	0.98
array/random/randn/Float32	44046 ns	43976 ns	1.00
array/random/randn!/Float32	24739 ns	24816 ns	1.00
array/random/rand!/Int64	27457 ns	27267 ns	1.01
array/random/rand!/Float32	8699 ns	8653.333333333334 ns	1.01
array/random/rand/Int64	31362 ns	38285 ns	0.82
array/random/rand/Float32	12953 ns	13026 ns	0.99
array/permutedims/4d	59865 ns	60152.5 ns	1.00
array/permutedims/2d	54251 ns	53934 ns	1.01
array/permutedims/3d	54850 ns	54649.5 ns	1.00
array/sorting/1d	2755637 ns	2757180 ns	1.00
array/sorting/by	3367795.5 ns	3343619 ns	1.01
array/sorting/2d	1084536 ns	1080730 ns	1.00
cuda/synchronization/stream/auto	1015.6 ns	1029.6 ns	0.99
cuda/synchronization/stream/nonblocking	8508.7 ns	7270.700000000001 ns	1.17
cuda/synchronization/stream/blocking	815.3333333333334 ns	850.7415730337078 ns	0.96
cuda/synchronization/context/auto	1156.9 ns	1157 ns	1.00
cuda/synchronization/context/nonblocking	7177.700000000001 ns	6964 ns	1.03
cuda/synchronization/context/blocking	900.1730769230769 ns	888.5208333333334 ns	1.01

This comment was automatically generated by workflow using github-action-benchmark.

[maleadt]

Why?

[kshyatt]

I was marking things broken to figure out what just doesn't work with the new PT 3.0. Let me mark this PR draft.

[kshyatt]

cc @ronisbr, could you help us out transitioning to PrettyTables.jl 3.0 here? There have been a bunch of API changes I'm unsure how to work with so some expert advice would be very welcome :)

[ronisbr]

Hi @kshyatt!

Yes, sure! I can submit a PR to adapt the old API to the new one. I am in the middle of a trip outside my country, but I will do this in a spare time.