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refine svmpredict #77
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Codecov Report
@@ Coverage Diff @@
## master #77 +/- ##
==========================================
+ Coverage 82.88% 84.09% +1.20%
==========================================
Files 5 5
Lines 222 220 -2
==========================================
+ Hits 184 185 +1
+ Misses 38 35 -3
Continue to review full report at Codecov.
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It would be great if we managed to make |
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I added Before: julia> A = rand(2, 2_000_000);
julia> @benchmark svmpredict($model, $A)
BenchmarkTools.Trial:
memory estimate: 152.59 MiB
allocs estimate: 15
--------------
minimum time: 1.185 s (0.10% GC)
median time: 1.207 s (1.83% GC)
mean time: 1.236 s (3.57% GC)
maximum time: 1.305 s (7.68% GC)
--------------
samples: 5
evals/sample: 1 After: julia> @benchmark svmpredict($model, $A)
BenchmarkTools.Trial:
memory estimate: 152.59 MiB
allocs estimate: 16
--------------
minimum time: 1.062 s (0.11% GC)
median time: 1.092 s (2.34% GC)
mean time: 1.113 s (4.13% GC)
maximum time: 1.195 s (8.72% GC)
--------------
samples: 5
evals/sample: 1 |
Given that there are some CI failures popped out randomly, I suspect that there are some GC safety issues e.g. |
@barucden good to go? |
I am trying to replicate the issue caught by one of the tests. So far I did not succeed. |
I cannot reproduce that on my machine either. I can add some |
Alright 👍 |
Ref: #76 (comment)
I imported the functionRebased.libsvm_predict_probability
andlibsvm_predict_values
for temporary and discussion needs.They should be relocated later in #76.