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Fix incorrect fromDistinctAscList in PlutusTx.ErrorCodes (#6635)
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@zliu41
zliu41 authored Nov 5, 2024
1 parent cfcfe10 commit 0d22dad
Showing 1 changed file with 1 addition and 1 deletion.
2 changes: 1 addition & 1 deletion plutus-tx/src/PlutusTx/ErrorCodes.hs
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Expand Up @@ -35,7 +35,7 @@ When writing a new error description please follow existing patterns:

-- | All error codes used in the plutus prelude associated with a human-readable description.
plutusPreludeErrorCodes :: Map Builtins.BuiltinString String
plutusPreludeErrorCodes = Map.fromDistinctAscList
plutusPreludeErrorCodes = Map.fromList
[ ("PT1", "TH Generation of Indexed Data Error")
, ("PT2", "PlutusTx.IsData.Class.unsafeFromBuiltinData: Void is not supported")
, ("PT3", "PlutusTx.Ratio: zero denominator")
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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: 0d22dad Previous: cfcfe10 Ratio
validation-future-increase-margin-3 660.4 μs 542.8 μs 1.22
validation-future-increase-margin-4 692.9 μs 488.1 μs 1.42
validation-future-increase-margin-5 1151 μs 813.4 μs 1.42
validation-future-pay-out-1 354.9 μs 250.6 μs 1.42
validation-future-pay-out-2 762.6 μs 539.1 μs 1.41
validation-future-pay-out-3 761.5 μs 572.3 μs 1.33
validation-future-pay-out-4 1143 μs 810.2 μs 1.41
validation-future-settle-early-1 355.3 μs 251.2 μs 1.41
validation-future-settle-early-2 756.5 μs 543.4 μs 1.39
validation-future-settle-early-3 763.2 μs 539 μs 1.42
validation-future-settle-early-4 854.8 μs 606.2 μs 1.41
validation-game-sm-success_1-1 549.7 μs 413.9 μs 1.33
validation-game-sm-success_1-2 285.3 μs 203.9 μs 1.40
validation-prism-2 585.5 μs 414.3 μs 1.41
validation-decode-future-increase-margin-4 788 μs 668.6 μs 1.18
nofib-clausify/formula2 5738 μs 4377 μs 1.31
nofib-clausify/formula3 15650 μs 11340 μs 1.38
nofib-clausify/formula4 35750 μs 25970 μs 1.38
nofib-clausify/formula5 75870 μs 54830 μs 1.38
nofib-knights/4x4 25100 μs 17900 μs 1.40
nofib-knights/6x6 65660 μs 47200 μs 1.39
nofib-knights/8x8 115300 μs 86960 μs 1.33
nofib-primetest/05digits 14740 μs 12510 μs 1.18
nofib-primetest/10digits 28660 μs 24330 μs 1.18
nofib-queens4x4/bt 7553 μs 7106 μs 1.06
nofib-queens4x4/bm 9524 μs 6863 μs 1.39
nofib-queens4x4/bjbt1 9128 μs 6565 μs 1.39
nofib-queens4x4/bjbt2 8562 μs 6147 μs 1.39
nofib-queens4x4/fc 19270 μs 14700 μs 1.31
nofib-queens5x5/bt 102400 μs 73650 μs 1.39
nofib-queens5x5/bm 107300 μs 77510 μs 1.38
nofib-queens5x5/bjbt1 119600 μs 86320 μs 1.39
nofib-queens5x5/bjbt2 116200 μs 83770 μs 1.39
nofib-queens5x5/fc 246200 μs 177200 μs 1.39
marlowe-semantics/0000020002010200020101020201000100010001020101020201010000020102 450.3 μs 382.1 μs 1.18
marlowe-semantics/0001000101000000010101000001000001010101010100000001000001010000 617.3 μs 433.5 μs 1.42
marlowe-semantics/0003040402030103010203030303000200000104030002040304020400000102 1457 μs 1024 μs 1.42
marlowe-semantics/004025fd712d6c325ffa12c16d157064192992faf62e0b991d7310a2f91666b8 1138 μs 800 μs 1.42
marlowe-semantics/0101010001010101010101000100010100000001010000010001000001000101 1303 μs 919.5 μs 1.42
marlowe-semantics/0101020201010201010200010102000201000201010102000102010201010000 423.6 μs 299.2 μs 1.42
marlowe-semantics/0101080808040600020306010000000302050807010208060100070207080202 1078 μs 756.1 μs 1.43
marlowe-semantics/0104010200020000040103020102020004040300030304040400010301040303 1087 μs 764.7 μs 1.42
marlowe-semantics/04000f0b04051006000e060f09080d0b090d0104050a0b0f0506070f0a070008 1028 μs 724.2 μs 1.42
marlowe-semantics/0543a00ba1f63076c1db6bf94c6ff13ae7d266dd7544678743890b0e8e1add63 1432 μs 999.6 μs 1.43
marlowe-semantics/0705030002040601010206030604080208020207000101060706050502040301 1391 μs 978.8 μs 1.42
marlowe-semantics/07070c070510030509010e050d00040907050e0a0d06030f1006030701020607 1437 μs 1012 μs 1.42
marlowe-semantics/0bcfd9487614104ec48de2ea0b2c0979866a95115748c026f9ec129384c262c4 1577 μs 1107 μs 1.42
marlowe-semantics/0be82588e4e4bf2ef428d2f44b7687bbb703031d8de696d90ec789e70d6bc1d8 1918 μs 1347 μs 1.42
marlowe-semantics/0f1d0110001b121d051e15140c0c05141d151c1f1d201c040f10091b020a0e1a 664.2 μs 466.8 μs 1.42
marlowe-semantics/119fbea4164e2bf21d2b53aa6c2c4e79414fe55e4096f5ce2e804735a7fbaf91 1066 μs 749.1 μs 1.42
marlowe-semantics/12910f24d994d451ff379b12c9d1ecdb9239c9b87e5d7bea570087ec506935d5 682.3 μs 483.6 μs 1.41
marlowe-semantics/18cefc240debc0fcab14efdd451adfd02793093efe7bc76d6322aed6ddb582ad 1059 μs 743.6 μs 1.42
marlowe-semantics/1a2f2540121f09321216090b2b1f211e3f020c2c133a1a3c3f3c232a26153a04 424.7 μs 298.6 μs 1.42
marlowe-semantics/1a573aed5c46d637919ccb5548dfc22a55c9fc38298d567d15ee9f2eea69d89e 1271 μs 894.7 μs 1.42
marlowe-semantics/26e24ee631a6d927ea4fb4fac530cfd82ff7636986014de2d2aaa460ddde0bc3 795 μs 559.8 μs 1.42
marlowe-semantics/2797d7ac77c1b6aff8e42cf9a47fa86b1e60f22719a996871ad412cbe4de78b5 2561 μs 1842 μs 1.39
marlowe-semantics/28fdce478e179db0e38fb5f3f4105e940ece450b9ce8a0f42a6e313b752e6f2c 1286 μs 905.4 μs 1.42
marlowe-semantics/2cb21612178a2d9336b59d06cbf80488577463d209a453048a66c6eee624a695 1105 μs 775.3 μs 1.43
marlowe-semantics/2f58c9d884813042bce9cf7c66048767dff166785e8b5183c8139db2aa7312d1 1073 μs 756.2 μs 1.42
marlowe-semantics/30aa34dfbe89e0c43f569929a96c0d2b74c321d13fec0375606325eee9a34a6a 1626 μs 1143 μs 1.42
marlowe-semantics/322acde099bc34a929182d5b894214fc87ec88446e2d10625119a9d17fa3ec3d 425.3 μs 298.7 μs 1.42
marlowe-semantics/33c3efd79d9234a78262b52bc6bbf8124cb321a467dedb278328215167eca455 876.5 μs 616.9 μs 1.42
marlowe-semantics/383683bfcecdab0f4df507f59631c702bd11a81ca3841f47f37633e8aacbb5de 1068 μs 752.2 μs 1.42
marlowe-semantics/3bb75b2e53eb13f718eacd3263ab4535f9137fabffc9de499a0de7cabb335479 358.9 μs 299.9 μs 1.20
marlowe-semantics/44a9e339fa25948b48637fe7e10dcfc6d1256319a7b5ce4202cb54dfef8e37e7 424.4 μs 298.5 μs 1.42
marlowe-semantics/4c3efd13b6c69112a8a888372d56c86e60c232125976f29b1c3e21d9f537845c 1448 μs 1016 μs 1.43
marlowe-semantics/4d7adf91bfc93cebe95a7e054ec17cfbb912b32bd8aecb48a228b50e02b055c8 976.3 μs 687.7 μs 1.42
marlowe-semantics/4f9e8d361b85e62db2350dd3ae77463540e7af0d28e1eb68faeecc45f4655f57 511.1 μs 395.8 μs 1.29
marlowe-semantics/52df7c8dfaa5f801cd837faa65f2fd333665fff00a555ce8c55e36ddc003007a 502.7 μs 352.9 μs 1.42
marlowe-semantics/53ed4db7ab33d6f907eec91a861d1188269be5ae1892d07ee71161bfb55a7cb7 511.9 μs 358.3 μs 1.43
marlowe-semantics/55dfe42688ad683b638df1fa7700219f00f53b335a85a2825502ab1e0687197e 425 μs 298.8 μs 1.42
marlowe-semantics/56333d4e413dbf1a665463bf68067f63c118f38f7539b7ba7167d577c0c8b8ce 1094 μs 770.1 μs 1.42
marlowe-semantics/57728d8b19b0e06412786f3dfed9e1894cd0ad1d2bc2bd497ec0ecb68f989d2b 425.5 μs 298.5 μs 1.43
marlowe-semantics/5abae75af26f45658beccbe48f7c88e74efdfc0b8409ba1e98f95fa5b6caf999 681.5 μs 479.9 μs 1.42
marlowe-semantics/5d0a88250f13c49c20e146819357a808911c878a0e0a7d6f7fe1d4a619e06112 1451 μs 1016 μs 1.43
marlowe-semantics/5e274e0f593511543d41570a4b03646c1d7539062b5728182e073e5760561a66 1423 μs 999.1 μs 1.42
marlowe-semantics/5e2c68ac9f62580d626636679679b97109109df7ac1a8ce86d3e43dfb5e4f6bc 731.8 μs 515.2 μs 1.42
marlowe-semantics/5f130d19918807b60eab4c03119d67878fb6c6712c28c54f5a25792049294acc 425.6 μs 299.2 μs 1.42
marlowe-semantics/5f306b4b24ff2b39dab6cdc9ac6ca9bb442c1dc6f4e7e412eeb5a3ced42fb642 1067 μs 747.6 μs 1.43
marlowe-semantics/5f3d46c57a56cef6764f96c9de9677ac6e494dd7a4e368d1c8dd9c1f7a4309a5 682.9 μs 480.4 μs 1.42
marlowe-semantics/64c3d5b43f005855ffc4d0950a02fd159aa1575294ea39061b81a194ebb9eaae 931.3 μs 650.9 μs 1.43
marlowe-semantics/7529b206a78becb793da74b78c04d9d33a2540a1abd79718e681228f4057403a 1108 μs 784.1 μs 1.41
marlowe-semantics/75a8bb183688bce447e00f435a144c835435e40a5defc6f3b9be68b70b4a3db6 974.4 μs 685.8 μs 1.42
marlowe-semantics/7a758e17486d1a30462c32a5d5309bd1e98322a9dcbe277c143ed3aede9d265f 714.2 μs 503.6 μs 1.42
marlowe-semantics/7cbc5644b745f4ea635aca42cce5e4a4b9d2e61afdb3ac18128e1688c07071ba 671.4 μs 471.6 μs 1.42
marlowe-semantics/82213dfdb6a812b40446438767c61a388d2c0cfd0cbf7fd4a372b0dc59fa17e1 1795 μs 1259 μs 1.43

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

CC: @IntersectMBO/plutus-core

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