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Fix bug in regex in manual-benchmark.yml (#6664)
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@zeme-wana
zeme-wana authored Nov 14, 2024
1 parent c082e28 commit 01fdff8
Showing 1 changed file with 1 addition and 1 deletion.
2 changes: 1 addition & 1 deletion .github/workflows/manual-benchmark.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -43,7 +43,7 @@ jobs:
uses: actions/github-script@main
with:
script: |
const regex = /^\/benchmark\s*([^\s]*)\s*(cap=([0-9]+))?$/;
const regex = /^\/benchmark\s*([^\s]*)\s*(cap=([0-9]+))?\s*$/;
const comment = context.payload.comment.body;
const match = comment.match(regex)
if (match !== null && match.length == 4 && match[1] !== '') {
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⚠️ Performance Alert ⚠️

Possible performance regression was detected for benchmark 'Plutus Benchmarks'.
Benchmark result of this commit is worse than the previous benchmark result exceeding threshold 1.05.

Benchmark suite Current: 01fdff8 Previous: c082e28 Ratio
validation-multisig-sm-5 676 μs 556.6 μs 1.21
validation-multisig-sm-6 560.1 μs 395.8 μs 1.42
validation-multisig-sm-7 548.4 μs 388.5 μs 1.41
validation-multisig-sm-8 553.5 μs 389.7 μs 1.42
validation-multisig-sm-9 559.7 μs 396.8 μs 1.41
validation-multisig-sm-10 791.7 μs 560.3 μs 1.41
validation-ping-pong-1 463.9 μs 331.4 μs 1.40
validation-ping-pong-2 465.9 μs 331.3 μs 1.41
validation-ping-pong_2-1 286.1 μs 202.7 μs 1.41
validation-prism-1 187.8 μs 173 μs 1.09
validation-decode-auction_1-2 564.9 μs 533.2 μs 1.06
validation-decode-auction_2-2 772 μs 634 μs 1.22
validation-decode-future-increase-margin-1 297.7 μs 240.8 μs 1.24
validation-decode-future-increase-margin-2 450.5 μs 327.9 μs 1.37
validation-decode-future-increase-margin-3 409.2 μs 331.4 μs 1.23
validation-decode-game-sm-success_2-1 550 μs 515.5 μs 1.07
validation-decode-game-sm-success_2-2 173.6 μs 164.1 μs 1.06
validation-decode-game-sm-success_2-3 573.8 μs 531.7 μs 1.08
validation-decode-game-sm-success_2-4 232.4 μs 164.6 μs 1.41
validation-decode-game-sm-success_2-5 749.6 μs 530.4 μs 1.41
validation-decode-game-sm-success_2-6 232.5 μs 164.6 μs 1.41
validation-decode-multisig-sm-1 835.8 μs 576.3 μs 1.45
validation-decode-multisig-sm-2 834.2 μs 590.7 μs 1.41
validation-decode-multisig-sm-3 832.2 μs 589.7 μs 1.41
validation-decode-multisig-sm-4 834.7 μs 589.4 μs 1.42
validation-decode-multisig-sm-5 834.2 μs 674.7 μs 1.24
validation-decode-multisig-sm-10 833.6 μs 765.7 μs 1.09
validation-decode-ping-pong-1 693.1 μs 510.3 μs 1.36
validation-decode-stablecoin_2-1 899.9 μs 852.6 μs 1.06
validation-decode-uniswap-2 247.5 μs 234.6 μs 1.05
nofib-queens5x5/bjbt1 96550 μs 88210 μs 1.09
marlowe-semantics/0101020201010201010200010102000201000201010102000102010201010000 453.4 μs 374.8 μs 1.21
marlowe-semantics/0101080808040600020306010000000302050807010208060100070207080202 1139 μs 805.5 μs 1.41
marlowe-semantics/0104010200020000040103020102020004040300030304040400010301040303 1161 μs 819 μs 1.42
marlowe-semantics/04000f0b04051006000e060f09080d0b090d0104050a0b0f0506070f0a070008 1103 μs 783.2 μs 1.41
marlowe-semantics/0543a00ba1f63076c1db6bf94c6ff13ae7d266dd7544678743890b0e8e1add63 1563 μs 1104 μs 1.42
marlowe-semantics/0705030002040601010206030604080208020207000101060706050502040301 1522 μs 1080 μs 1.41
marlowe-semantics/07070c070510030509010e050d00040907050e0a0d06030f1006030701020607 1517 μs 1078 μs 1.41
marlowe-semantics/0bcfd9487614104ec48de2ea0b2c0979866a95115748c026f9ec129384c262c4 1473 μs 1194 μs 1.23
marlowe-semantics/0be82588e4e4bf2ef428d2f44b7687bbb703031d8de696d90ec789e70d6bc1d8 2021.9999999999998 μs 1432 μs 1.41
marlowe-semantics/0f1d0110001b121d051e15140c0c05141d151c1f1d201c040f10091b020a0e1a 704.4 μs 498 μs 1.41
marlowe-semantics/119fbea4164e2bf21d2b53aa6c2c4e79414fe55e4096f5ce2e804735a7fbaf91 1132 μs 802.4 μs 1.41
marlowe-semantics/12910f24d994d451ff379b12c9d1ecdb9239c9b87e5d7bea570087ec506935d5 739.6 μs 529.9 μs 1.40
marlowe-semantics/18cefc240debc0fcab14efdd451adfd02793093efe7bc76d6322aed6ddb582ad 1122 μs 793.2 μs 1.41
marlowe-semantics/1a2f2540121f09321216090b2b1f211e3f020c2c133a1a3c3f3c232a26153a04 349.8 μs 319.5 μs 1.09
marlowe-semantics/21953bf8798b28df60cb459db24843fb46782b19ba72dc4951941fb4c20d2263 531.6 μs 390.6 μs 1.36
marlowe-semantics/238b21364ab5bdae3ddb514d7001c8feba128b4ddcf426852b441f9a9d02c882 454.7 μs 333 μs 1.37
marlowe-semantics/26e24ee631a6d927ea4fb4fac530cfd82ff7636986014de2d2aaa460ddde0bc3 830 μs 610.6 μs 1.36
marlowe-semantics/2797d7ac77c1b6aff8e42cf9a47fa86b1e60f22719a996871ad412cbe4de78b5 2616 μs 1922 μs 1.36
marlowe-semantics/28fdce478e179db0e38fb5f3f4105e940ece450b9ce8a0f42a6e313b752e6f2c 1378 μs 1012 μs 1.36
marlowe-semantics/2cb21612178a2d9336b59d06cbf80488577463d209a453048a66c6eee624a695 1168 μs 855.7 μs 1.36
marlowe-semantics/2f58c9d884813042bce9cf7c66048767dff166785e8b5183c8139db2aa7312d1 1134 μs 833.4 μs 1.36
marlowe-semantics/30aa34dfbe89e0c43f569929a96c0d2b74c321d13fec0375606325eee9a34a6a 1710 μs 1249 μs 1.37
marlowe-semantics/322acde099bc34a929182d5b894214fc87ec88446e2d10625119a9d17fa3ec3d 423.8 μs 333.4 μs 1.27
marlowe-semantics/cf542b7df466b228ca2197c2aaa89238a8122f3330fe5b77b3222f570395d9f5 701.6 μs 540.1 μs 1.30
marlowe-semantics/d1ab832dfab25688f8845bec9387e46ee3f00ba5822197ade7dd540489ec5e95 48130 μs 37650 μs 1.28
marlowe-semantics/d1c03759810747b7cab38c4296593b38567e11195d161b5bb0a2b58f89b2c65a 1523 μs 1115 μs 1.37
marlowe-semantics/e26c1cddba16e05fd10c34cbdb16ea6acdbac7c8323256c31c90c520ee6a1080 548.4 μs 403 μs 1.36
marlowe-semantics/e34b48f80d49360e88c612f4016f7d68cb5678dd8cd5ddb981375a028b3a40a5 585.2 μs 430.9 μs 1.36
marlowe-semantics/e3afd22d01ff12f381cf915fd32358634e6c413f979f2492cf3339319d8cc079 454.1 μs 332.7 μs 1.36
marlowe-semantics/e9234d2671760874f3f660aae5d3416d18ce6dfd7af4231bdd41b9ec268bc7e1 1399 μs 1027 μs 1.36
marlowe-semantics/eb4a605ed3a64961e9e66ad9631c2813dadf7131740212762ae4483ec749fe1d 452 μs 332.7 μs 1.36
marlowe-semantics/ecb5e8308b57724e0f8533921693f111eba942123cf8660aac2b5bac21ec28f0 984.9 μs 726.8 μs 1.36
marlowe-semantics/f2a8fd2014922f0d8e01541205d47e9bb2d4e54333bdd408cbe7c47c55e73ae4 1116 μs 819.1 μs 1.36
marlowe-semantics/f339f59bdf92495ed2b14e2e4d3705972b4dda59aa929cffe0f1ff5355db8d79 6421 μs 4750 μs 1.35
marlowe-semantics/ffdd68a33afd86f8844c9f5e45b2bda5b035aa02274161b23d57709c0f8b8de6 1420 μs 1038 μs 1.37
marlowe-role-payout/0004000402010401030101030100040000010104020201030001000204020401 285.2 μs 208.8 μs 1.37
marlowe-role-payout/0100000100010000000001000100010101000101000001000000010000010000 391.7 μs 288 μs 1.36
marlowe-role-payout/0101000100000101010000010101000100010101000001000001000000010101 304.3 μs 222.1 μs 1.37
marlowe-role-payout/01dcc372ea619cb9f23c45b17b9a0a8a16b7ca0e04093ef8ecce291667a99a4c 250.2 μs 184 μs 1.36
marlowe-role-payout/0e72f62b0f922e31a2340baccc768104025400cf7fdd7dae62fbba5fc770936d 270.9 μs 223.4 μs 1.21
marlowe-role-payout/5d4c62a0671c65a14f6a15093e3efc4f1816d95a5a58fd92486bedaae8d9526b 284.8 μs 211.3 μs 1.35
marlowe-role-payout/5efe992e306e31cc857c64a62436ad2f9325acc5b4a74a8cebccdfd853ce63d2 268.1 μs 189.9 μs 1.41

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

CC: @IntersectMBO/plutus-core

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