i"tSSKJrJr SSKJrJr SSKJrJrJ r SSK J r SSK J r Jr SSKJr "SS5rg ) )int_from_bytes int_to_bytes)ChoiceTchoice_permitted)ConjectureResultStatus_Overrun)ConjectureRunner) bits_to_bytes find_integer)NO_SCOREc \rSrSrSrSS\S\S\S\SS4 S jjr SS jr S\S\ 4S jr \ S\ 4S j5rS\\-S\4S jrSSjrSrg) OptimiseruA fairly basic optimiser designed to increase the value of scores for targeted property-based testing. This implements a fairly naive hill climbing algorithm based on randomly regenerating parts of the test case to attempt to improve the result. It is not expected to produce amazing results, because it is designed to be run in a fairly small testing budget, so it prioritises finding easy wins and bailing out quickly if that doesn't work. For more information about targeted property-based testing, see Löscher, Andreas, and Konstantinos Sagonas. "Targeted property-based testing." Proceedings of the 26th ACM SIGSOFT International Symposium on Software Testing and Analysis. ACM, 2017. enginedatatargetmax_improvementsreturnNcBXlX lX0lX@lSUlg)a Optimise ``target`` starting from ``data``. Will stop either when we seem to have found a local maximum or when the target score has been improved ``max_improvements`` times. This limit is in place to deal with the fact that the target score may not be bounded above.rN)r current_datarr improvements)selfrrrrs g/var/www/html/ai-image-ml/venv/lib/python3.13/site-packages/hypothesis/internal/conjecture/optimiser.py__init__Optimiser.__init__#s"   0c$UR5 gN) hill_climbrs rrun Optimiser.run4s  rcVURRUR[5$r)target_observationsgetrr )rrs rscore_functionOptimiser.score_function7s''++DKKBBrc8URUR5$r)r'rr!s r current_scoreOptimiser.current_score:s""4#4#455rcUR[R:ag[U[5(deUR U5nX R :agX R :aU=RS- slXlgX R :Xde[UR5[URR5::aXlgg)zdConsider a new data object as a candidate target. If it is better than the current one, return True.FT) statusrVALID isinstancerr'r*rrlennodes)rrscores rconsider_new_dataOptimiser.consider_new_data>s ;; %$ 01111##D) %% % %% %    "  $ ***** tzz?c$"3"3"9"9: : $ rc^^^[5nSn[TRR5S- mTS:GaTRTR ::aUTRLa.[TRR5S- mTRnTU;aTS-mMkUR T5 TRRTnURceURS;aMS[S[4UU4Sjjm[U4Sj5 [U4S j5 TS:aTRTR ::aMgggg) zThe main hill climbing loop where we actually do the work: Take data, and attempt to improve its score for target. select_example takes a data object and returns an index to an example where we should focus our efforts.Nr-r>bytesfloatbooleanintegerkrc d>[U5S:agTRRT nURceUR(agUR S;a7[ UR[[45(deURU-nOUR S:XaT[ UR[5(de[U5S:agUS:XaSnUS:XaSnUS :Xa URnOUR S :Xde[ UR[5(de[UR5nX0-S :agX0- n[[UR5[UR!555n[#X45n[%WUR&5(dg[)S 5GHnTRR*nUSURU4-XaRS-S-nTR,R/US S 9nTR1U5(a gUR2[4R6La g[ U[85(de[UR5[TRR5:Xa g[;TRR<5HupU R>URS-:a GM$U R@UR::aMBUR<U n U RBU RB:XaMmUR*U R>U R@n TR1TR,R/USURU -TRR*U R@S-55(dM g GM g)aW Try replacing the current node in the current best test case with a value which is "k times larger", where the exact notion of "larger" depends on the choice_type. Note that we use the *current* best and not the one we started with. This helps ensure that if we luck into a good draw when making random choices we get to keep the good bits. iFN>r8r:r9r-Trr7full)extend)"absrr2index was_forcedtyper0valueintr8boolr7rmaxr1r bit_lengthrr constraintsrangechoicesrcached_test_functionr4r.rOVERRUNr enumeratespansstartend choice_count)r;node new_choicevsize_rLattempt_choicesattemptjex ex_attempt replacementirs rattempt_replace-Optimiser.hill_climb..attempt_replacepsq6E> ((..q1zz---?? 99 44%djj3,????!%aJYY)+%djj$77771vz$Bw%* Av%) Av%)ZZ 99///%djj%8888&tzz2Auqy$FAs4:: alln0MND!-a!6J' D4D4DEE qA"//77G $**-%-(!**q."234$ #kk>>'?G--g66#~~7$%g/?@@@@7==)S1B1B1H1H-II$!*4+<+<+B+B!C88tzzA~5!66TZZ/$%,]]1%5 ??j.E.EE$&-ooj6F6F&X 11 KK<< ' $** 5"-!."&"3"3";";BFFH"E!F$(!"D+"Lrc>T"U5$rr;r`s r&Optimiser.hill_climb..s ?1#5rc>T"U*5$rrcrds rrerfs ?A2#6r) setr1rr2rraddrBrDrFrGr )rnodes_examinedprevrTr`r_s` @@rr Optimiser.hill_climbTs) (, !!'' (1 ,1f**d.C.CC4,,,))//014((N"Q   q !$$**1-D::) ))yy HHW 3W 4W W v 5 6 6 7]1f**d.C.CCfCfr)rrrrr)d)rN)__name__ __module__ __qualname____firstlineno____doc__r rstrrFrr"r8r'propertyr*r rGr4r __static_attributes__rcrrrrs (!$       "C#3CC6u66&6&Ad,x8rrN)hypothesis.internal.compatrr%hypothesis.internal.conjecture.choicerr#hypothesis.internal.conjecture.datarrr %hypothesis.internal.conjecture.enginer )hypothesis.internal.conjecture.junkdrawerr r %hypothesis.internal.conjecture.paretor rrcrrr|s)DKRRBQ:y8y8r