qtjddlZddlZddlZddlZddlmZmZddlmZddl m Z m Z m Z m Z ddlmZddlmZddlmZddlmZmZdd lmZmZmZmZmZmZmZm Z m!Z!m"Z"m#Z#m$Z$m%Z%m&Z&m'Z'm(Z(dd l)m*Z*dd l+m,Z,m-Z-m.Z.dd l+m/Z0dd l1m2Z2m3Z3m4Z4e5ej6Z7de7DZ8e8e'de&de$de$de$de$de$de%de%de%de%dg z Z8dZ9 ddZ:dZ;ej<=de8e9dZ>e#gd ej? ej?gfegd ej? ej?gfe'gd ej? ej?gfe&gd ej? ej?gfe!d!d"gej? d#d$ej?gfed!d"gej? d#d$dej?gfe$d#d!d"gej? ej?gfe$dd!d"gej? ej?gfe$d%d!d"gej? d#d$ej?gfe$dd!d"gej? d#d$dej?gfe$d&d!d"gej? d#d$dej?gfe%d#d!d"gej? ej?gfe%dgd'ej? ej?gfe%d%d!d"gej? d#d$ej?gfe%dd!d"gej? d#d$dej?gfe%d&d!d"gej? d#d$dej?gfegd(ej? d)dej?gfegej? d)d*ej?gfgZ@e!dggfe&dggfe$d#gd+gfe$dd,dggfe$d%dggfe%d#gd+gfe%dd,dggfe%d%dggfeddggfegd-gfg ZAe!gdgfe$d#ggd.fe$dggd.fe$d%gdgfe%d#ggd.fe%dgd.gfe%d%gdgfegddgfed!d/gddgfg ZBej<=d0e@eAzd1ZCej<=d2e@eBzd3ZDej<=d4ge#d5d6d7d8dfed5d6d9d5dfe'd/d5d6dd/dfe'dd5d6dddfe'dd6d5d5d:dfe&d/d&;d5d6dddfe%dd=d9ddejEdzz ddfe%dd=d9ejEdd/z ddfe%d&d=d9d?ddfedejEd8ejFd8dejEd8zz ddfed@dAdddfed5dAdBd)dfed@dCdddfed5dCdDd)dfed5dEdFd)dfed5dGdHdIdJfed@dGgdJgd&zRed5dKdLdIdMfed@dKgdMgd&zRed@dNdHdOdJfed5dNgdPgd&zRed@dFdFddQfed@dRdRddSfed5dBdddfed@dBdBddfed5dRddTdSfed5dUdddfed5dDdddfed@dDdDddfed&Vd@gdWegdWdXz ddfed&Vd5gdWegdWd/z ddfed&Vd=gdWegdWdYz ddfed&Vd=gdZegdZd[z ddfe9d\ZGej<=de7ej<=d]d^d_gej<=d`ejHejIgej<=daejHejIgej<=dbddgej<=dcddgej<=ddddgej<=deddgdfZJej<=de8e9ej<=dbddggdhZKej<=de8e9ej<=dbddggdiZLej<=de8e9ej<=dbdjdkgdlZMej<=de8e9dmZNej<=de8e9ej<=dbddggdnZOej<=de8e9ej<=dbddggdoZPej<=dpgdqe4drZQej<=de8e9ej<=dbddggdsZRej<=dte#ejSdufeejTdufe'ddvdufe!ejSdwfeejSdxfe$ejSdxfeejSdyfgdzZUd{ZVd|ZWd}ZXej<=d~ejYgdejYgdfej<=dejYgdejYgdfdZZej<=de8e9dZ[ej<=de7ej<=dbddggej<=dejHejIfej<=dddZ\ej<=de7ej<=ddej]idej]dfgdZ^ej<=de'ddie_dfe'ddie`dfe'dd*ie`dfe&ddie_dfe&ddie`dfe&dd*ie`dfgdZaej<=de8e9dZbej<=dgddZcej<=deefe efe"e!fggdej<=dgdej<=dd^d_gej<=de.dZdej<=de.dZedZfdS)N)assert_allcloseassert_array_equal)approx)LinearConstraintminimizeminimize_scalarnewton) logsumexp)config_context)_loss) IdentityLink_inclusive_low_high)_LOSSES AbsoluteErrorBaseLossHalfBinomialLossHalfBinomialLossArrayAPI HalfGammaLossHalfMultinomialLossHalfMultinomialLossArrayAPIHalfPoissonLossHalfPoissonLossArrayAPIHalfSquaredErrorHalfTweedieLossHalfTweedieLossIdentity HuberLoss PinballLoss _log1pexp)assert_all_finite)_atol_for_typemove_to)yield_namespace_device_dtype_combinationsdevice)_array_api_for_testscreate_memmap_backed_data skip_if_32bitc"g|] }| Sr)).0losss [/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/sklearn/_loss/tests/test_loss.py r-6s000T$$&&000g?)quantileg?power@crt|tr|}|jj}t|tr|d|jjdz }n[t|tr|d|jz }n8t|dr(t|jdr|d|jj dz }|St|S)Nz (quantile=)clossr2z(power=) isinstancer __class____name__rr8r/rhasattrr2str)paramr+names r,loss_instance_namer@Gs%"" ~& dK ( ( 2 7!4777 7DD i ( ( 2 000 0DD T7 # # 2 G(D(D 2 1dj.111 1D 5zzr.d*ctj|}|jrtj||jf}||d|d||jz|jdd<tj| t|jz}n:t|j trSt|j\}} tj||dg}tj| |dg} || f}||d|d|}t|j\}} t'||d}t)| |d} ||| |}|jjdkr|jjr d|dd|dz<|jjdkr|jjr d|dd|dz<||fS)z9Random generate y_true and raw_prediction in valid range.rr3)lowhighsizeNrK)nprandom RandomState is_multiclassempty n_classesuniformflatarangeastypefloatr9linkr rinterval_y_predamaxamininterval_y_truemaxminrI low_inclusiverJhigh_inclusive) r+ n_samplesy_bound raw_boundseedrngraw_predictiony_truerIrJs r,random_y_true_raw_predictionriVs )   % %C .9dn"=>>!$! 1T^+"-" " AAA 9%%,,U33dnD di . . $+D,@AAIC'3 ! -..C7D)A,/00Dd I! 9Q !!r.ctj||}||d|zz }|||z }|||z}||d|zz}| d|zzd|zz |zd|zz S)z2Helper function for numerical (first) derivatives.) fill_valuer4(@)rN full_like)funcxepsh f_minus_2h f_minus_1h f_plus_1h f_plus_2hs r,numerical_derivativerw{s Q3'''Aa!a%iJa!eJQU IQQYI JY &Z 7* DPS TTr.r+)idsc|jr0d}tjtjd|dz |d}n.t |j\}}tj||d}|jjrtj||jjf}|jj rtj||jj f}| |sJ|j d}t |j \}}|jrgtj||f}tj||||dddf<dd|dddfz z|dddf<dd|dddfz z|dddf<ntj|||}||sJ|j|}||| dS) z4Test interval ranges of y_true and y_pred in losses.rMrr3num N?r4rhrg)rQrNtilelinspacerr]r`r_rIrarJin_y_true_rangeshaperZrRin_y_pred_rangerYr+)r+rSrhrIrJny_predrgs r,test_loss_boundaryrs 0 Q A 9EEEqII'(<== TS$B/// )9vt3778 *:vt3889    ' ''' ' QA#D$899IC /1i.)){3!444qqq!t a&A,./qqq!t a&A,./qqq!t S$A...    ' ''' 'Y^^F++NIIVNI;;;;;r.)rBr皙?rCrrC皙?rM)rrrrrC)rr}?g?)rBrrrB)?r4)rrrr}z!loss, y_true_success, y_true_failc|D],}|tj|gsJ-|D],}|tj|grJ-dS)z-Test boundaries of y_true for loss functions.N)rrNarray)r+y_true_success y_true_failys r,test_loss_boundary_y_truerz 33##BHaSMM222222 77''! 66666677r.z!loss, y_pred_success, y_pred_failc|D],}|tj|gsJ-|D],}|tj|grJ-dS)z-Test boundaries of y_pred for loss functions.N)rrNr)r+y_pred_success y_pred_failrs r,test_loss_boundary_y_predrrr.zDloss, y_true, raw_prediction, loss_true, gradient_true, hessian_truerg@rlg@gп)r/deltag@@gȿg?rg@xg@xDg@g@@gBgB@gB%ggT`Grc|tj|gtj|g}|tj|gtj|g}|tj|gtj|g\}} |tj|gtj|g\} } |t |ddksJ|t |ddksJ|H|t |ddksJ| t |ddksJ| t |ddksJ|| t |ddksJdSdS)z7Test losses, gradients and hessians at specific values.r~V瞯<relabsN)rNrgradient loss_gradientgradient_hessianr) r+rhrg loss_true gradient_true hessian_trueloss1grad1loss2grad2grad3hesss r,test_loss_on_specific_valuesrsx D&**28^DT;U;U V V VE MMx!!"(N;K2L2L   E%%x!!"(N;K2L2L&LE5''x!!"(N;K2L2L(KE4 F9%U;;; ; ; ; ; F9%U;;; ; ; ; ; }%UCCCCCCC}%UCCCCCCC}%UCCCCCCCvl5AAAAAAA AAr.readonly_memmapFTdtype_in dtype_out sample_weightout1out2 n_threadsc~|}d}t||ddd\} } | |} | |} |tjdg|z|}|tj| |}|tj| |}|r/t | } t | } |t |}|| | ||| } || |usnnJ|| | ||| } || |usnnJ|| | |||| \} } || |usnnJ|| |usnnJ||j rtj| |}| | | |||| \} } || |usnnJ|| |usnnJ|| | || | || | |t|dr|| t|dr3|| | ||||\} }|| |usnnJ|||usndSJdSdS)a0Test acceptance of dtypes, readonly and writeable arrays in loss functions. Check that loss accepts if all input arrays are either all float32 or all float64, and all output arrays are either all float32 or all float64. Also check that input arrays can be readonly, e.g. memory mapped. rFrAr|rGr+rbrcrdreNrdtype)rhrgrloss_outrT)rhrgr gradient_outr)rhrgrrrr)rhrgrr hessian_outrrhrgrrhr predict_proba)rggradient_proba)rhrgrr proba_outr)rirWrNr empty_liker&r+rrrQrfit_intercept_onlyconstant_to_optimal_zeror<rr)r+rrrrrrrrbrhrglgrrps r,test_loss_dtypersG$ 466DI9   FN]]8 $ $F#**844N #!2(CCC  }V9555 }^9===E*6222>BB  $5mDDM %#   A(199999 2 %#   A(199999 2   %#   DAq(199999 2(199999 2 D.}^9===  %# !  DAq(199999 2(199999 2D~]SSSS6GGG!!}!MMMt_%%: .999t%&& 7"")' #  1!,qDyyyyy6 ,qDyyyyyy6 7 7yr.rangect|dddd\}}|dkr-tjd|jd|jd }tj|}tj|}tj|}tj|}tj|}tj|} ||||| |j|||| t||||||| |j|||| t|||j ||||| |j ||||| t||t||| ||||| |j ||||| t||t|| dS)z:Test that Python and Cython functions return same results.rArrGrrr3rrzrhrgrrrhrgrrrhrgrrrrhrgrrrN) rirNrrrr+r8rrrr) r+rrhrgout_l1out_l2out_g1out_g2out_h1out_h2s r,test_loss_same_as_C_functionsrs:   FN Av|AFLOLLL ]6 " "F ]6 " "F ]> * *F ]> * *F ]> * *F ]> * *FII%#   JOO%#  FF###MM%#   J%#  FF###J%#  J%# FF###FF###%#  J%#  FF###FF#####r.ct|ddd|\}}|dkr-tjd|jd|jd}tj|}tj|}tj|}tj|}tj|} tj|} ||||| } ||||| } |||||| \} }||||| | \}}t| | t| |tj | |sJt| |tj | |sJt| |t| |t| |tj | |sJt||tj ||sJt|| tj || sJt|d r|j sJtj|}tj|}||||||\}}t| |t| |t||ttj|ddddSdS)zTest that loss and gradient are the same across different functions. Also test that output arguments contain correct results. rrArrrr3rrzrrrrrrhrgrrraxisdy=)rtolN)rirNrrrr+rrrrr shares_memoryr<rQrsum)r+rglobal_random_seedrhrgrrrrout_g3out_h3l1g1l2g2g3h3out_g4 out_probag4probas r, test_loss_gradients_are_the_samer?s/:   FN Av|AFLOLLL ]6 " "F ]6 " "F ]> * *F ]> * *F ]> * *F ]> * *F %#   B %#   B   %#  FB " "%# #FBBr6""" B ' ''' 'r6""" B ' ''' 'BBr6""" B ' ''' 'r6""" B ' ''' 'r6""" B ' ''' 't%&&>!!!!~..M.11 '')' (  E F###By)))u1---qu======>>r.onesrOc d}t||dd|\}}|dkr!tj|tj}nRtj|}||tj}t| ||||| ||d z| ||d \}}| |||\} } t||z| |j st||z| nt||d d d fz| | ||d \}} | |||\} } |j s(t||z| t| |z| d St||d d d fz| t| |d d d fz| d S) zTest sample weights in loss, gradients and hessians. Make sure that passing sample weights to loss, gradient and hessian computation methods is equivalent to multiplying by the weights. rCrArDrr)rrrLrN) rirNrfloat64rOrPnormalrWrr+rrQr) r+rrrbrhrgrflossesr losses_sw gradient_swhessian hessian_sws r,test_sample_weight_multipliesrstI9   FNirzBBB i##$677 2299"*EE  )'    )))      ))%*FH "//%#0I{ F]*I666  H=0+>>>>=D#99;GGG--%.Hg #33%#4K  F=0+>>>-/<<<<<=D#99;GGG-4"88*EEEEEr.c6t|dddd\}}|jdkr|dddf}t||||||t||||||t||||||t||||||dSdS) z5Test that reshaped raw_prediction gives same results.rrArrGrr3Nr~)rindimrr+rrr)r+rhrgraw_prediction_2ds r,test_graceful_squeezingrsW:   FNa*111d73 IIV4EI F F IIVNI C C       f=N  O O   f^  L L     MM8IM J J MMM G G      ! !@Q ! R R  ! ! ! O O      r.c`|jstjgd}t|jt rRd}|jj}|jjs||z}|jj }|jj s||z }tj |||}|j |}ntj |jt }tj|j|jftjd t }tjd|jdd|jdz<|dkr-tjd|jd|jd }|||| }||| }t1|| d d dS)z~Test value of perfect predictions. Loss of y_pred = y_true plus constant_to_optimal_zero should sums up to zero. )rrrrrMr|绽|=r|)rrkrNr3rrrzrr+=r)atolr)rQrNrr9rYr rZrIr`rJraclipinverserVrSrWrXfullexprUrrr+rr) r+rrgrqrIrJrh loss_value constant_terms r,test_loss_of_perfect_predictionr s  @"<"<"<== di . . @C&*C'5 Ci',D'6 "czW^S$??N"">224>**11%88>4>2r {    68VBZZ11t~112 Av|AFLOLLL %#J 11]2M JUGGGGGGr.c@ d}t|dd|\ dkr-tjd jd jd  \}}|j jksJ|j jksJjsc fd }t | d }t||d d fd}t | d } jrdSt|| d ddStj D]  fd}t | dd fd }t|dd f|d d  fd}t | dd fd } jrqt|dd f| d ddS)zTest gradients and hessians with numerical derivatives. Gradient should equal the numerical derivatives of the loss function. Hessians should equal the numerical derivatives of gradients. rrArDrrr3rrzrc4|SNr)r+rpr+rrhs r, loss_funcz6test_gradients_hessians_numerically..loss_funcGs'99 + r.ư>)rqh㈵>rrrc4|Srrrs r, grad_funcz6test_gradients_hessians_numerically..grad_funcQs'== +! r.cn}||ddf<|Sr)copyr+rprawkr+rgrrhs r,rz6test_gradients_hessians_numerically..loss_funcfsI$))++AAAqD yy!#&"/!r.Nh㈵>c}||ddf<|ddfSr)rrrs r,rz6test_gradients_hessians_numerically..grad_funcrs[$))++AAAqD }}!#&"/%!!Q$ r.) rirNrrrrQrwrapprox_hessianrrS) r+rrrbrrrr g_numericr h_numericrrgrhs `` @@@r,#test_gradients_hessians_numericallyr#(sI9   FN Av|AFLOLLL  %# !  DAq 7n* * * * * 7n* * * * *  ;K       )NMMM 94e<<<<       )NMMM   A D Ayt% @ @ @ @ @ @t~&& K KA         -Yqqq!t8LRVWWWI AaaadGYT F F F F         -Yqqq!t8LRVWWWI" K!!!Q$EJJJJJ9 K Kr.zloss, x0, y_true) ) squared_errorgrG)r$g@]@g?)r$rr) binomial_lossrr)r%ir)r%r) poisson_lossrmr)r'rr)r'g6g$@ctdtjgtjtj|gtj}dtjdtjffd }dtjdtjffd }dtjdtjffd }t ||||d d }|}tj |t||d d t |d ddS)acTest that gradients are zero at the minimum of the loss. We check this on a single value/sample using Halley's method with the first and second order derivatives computed by the Loss instance. Note that methods of Loss instances operate on arrays while the newton root finder expects a scalar or a one-element array for this purpose. Nrrrpreturnc`|zS)zCompute loss plus constant term. The constant term is such that the minimum function value is zero, which is required by the Newton method. r~rh)r+rrpr+rhs r,roztest_derivatives..funcs> yy!   ) ) ) 8 89 9r.c2|S)Nr~rr-s r,fprimez test_derivatives..fprimes}}F1}===r.c>|dS)Nr~r3)rr-s r,fprime2z!test_derivatives..fprime2s!$$F1$EEaHHr.rCgHj>)x0r/r1maxitertolrrrr~gƠ>) rrNrrndarrayr ravelrrYrr)r+r2rhror/r1optimums` ` r,test_derivativesr9s4 4=t , , ,D Xvhbj 1 1 1F 2$bj ) ) )B9 9rz9999999>"*>>>>>>>>I2:I"*IIIIIII   G\\^^FmmooGDI%%g..777DDMM151111DMMMHH!RVWWWWWWr.c djs0jtjddnAtjtjjzdddd<dkrtjd d   }fd }jst|d ddi} tj |}|j tksJ|jjksJt!||t#|jd k|t#ddkdSt)|tjjdddidt-tjdjfdd} tj|df}|jjksJt!|t3||jddt3|ddddS)zzTest that fit_intercept_only returns the argmin of the loss. Also test that the gradient is zero at the minimum. 2rrzrNrFrrr4rcjstj|}n/tjtj|jf}|S)N)rrkrr)rQrNr ascontiguousarray broadcast_torS)rprgr+rbrrhs r,funz%test_loss_intercept_only..funss! WI1EEENN1)T^)DEEENt)'    r.gHz>r3rC)r4optionsrr-q=)rgvIh%<=SLSQPr3)r4rBmethod constraintsrrrr5)rQrYrrNrrVrWrrSrrrrnrtuplerrrrprrzerosrrrr)r+rarAoptgradrbrhs`` @@r,test_loss_intercept_onlyrMsI  ""2;r1)#D#D#DEE9%%,,RZ884>Isss  C :::  v]KKA           9cti5EFFF}}<22'   w%''!!!!w&,&&&&! VCEt $ $ $$$  fQE*******  Hdn & &$(!T^1D)E)Eq!LL    }}71y!n55'   w&,&&&&!35t%8888a((!%888888r.zloss, func, random_distrc.tj|dS)N)q)rN percentile)rps r,rR sr}Q"/E/E/Er.poisson exponentialbinomialctj|}|dkr|ddd}nt ||d}||}t ||t|j||ksJ|j |t||ksJt|tr(t|j |||j jrD||j j||}t ||j jrF||j j||}t |dSdS)zTest that fit_intercept_only returns the correct functional. We test the functional for specific, meaningful distributions, e.g. squared error estimates the expectation of a probability distribution. rUr3r}rCrLr,N)rNrOrPrUgetattrrrrrYrr9r rr]r`fillrIrarJ)r+ro random_distrrfy_trainbaseline_predictions r, test_specific_fit_intercept_onlyr\s$ )   2 3 3Cj  ,,q#C,00+'#{++555111AA)*** &W )F)F"G"G G G G G 9  0 1 1VDDMM5J5J J J J J$ %%U ))*=>>@STTT )/ T)-..."55W5EE-... */ T).///"55W5EE-.....//r.c tjd}d}t|}|d|dzdtj}||}|j|fksJtj ||j }t|D]}||k ||<t|tj|tj tj|z t|d d d f|j|d d d ftj d tjd fD]X}|tj}||}|j |j ksJt#|Yd S) zATest that fit_intercept_only returns the mean functional for CCE.rrrr3rCrLr,rNr|r>)rNrOrPrrandintrWrrrrIrrmeanrlogrYrr)rfrSr+rZr[rrs r,(test_multinomial_loss_fit_intercept_onlyra1s )   " "CI  3 3 3Dkk!Y]k55<.alt_losss> EAIwrva"&!h"7"7788999r.cNd|zdz }| dtj||zzz Srm)rNr rns r, alt_gradientz>test_binomial_vs_alternative_formulation..alt_gradients/ EAIrQH ---..r.N)rrWrrr)rhr global_dtyperqrsbin_lossdatums r,(test_binomial_vs_alternative_formulationrwws":::///  !!H ]]< ( (F ]]< ( (F V E 8U vhh&677 7 7 7 7%H%u-||U/CDDDDDr.c d}t||dd|\}}t|drT||}|j||jfksJt j|dtdd ksJt|d rd d t j|ft j|d ft j|t j|ffD]\}}| ||d || \}}|j||jfksJt j|dtdd ksJt|| ||d d d Sd S)z22{y$.99999ve!$$$qe(<(<(<<<<<t%&&  2=00 1 ]> * *D 1 ]> * *BM.,I,I J    KD% ---"! .KD%;9dn"=====6%a(((F1%,@,@,@@@@@  !#1"&!%     !  r.rorder)CFcd}|dkrtj|}||}||||\}}|jr|j|fksJ|jdksJnL|jr)|j||jfksJ|j||jfksJn|j|fksJ|j|fksJ|j|ksJ|j|ksJ|dkr|jj sJ|jj sJdS|jj sJ|jj sJdS)zTest that init_gradient_and_hessian works as expected. passing sample_weight to a loss correctly influences the constant_hessian attribute, and consequently the shape of the hessian array. rFrr))rbrrz)r3r{N) rNrinit_gradient_and_hessianconstant_hessianrrQrSrflags c_contiguous f_contiguous)r+rrrzrbrrs r,test_init_gradient_and_hessiansrsI ** 4m , , ,D667Hg  -~)----}$$$$$ -~)T^!<<<<<}DN ;;;;;;} ,,,,} ,,,, >U " " " " =E ! ! ! ! ||~****}))))))~****}))))))r.zparams, err_msgz+Valid options for 'dtype' are .* Got dtype=z instead.c|}tjttf|5|jdddi|\}}ddddS#1swxYwYdS)zDTest that init_gradient_and_hessian raises errors for invalid input.matchrbrFNr))pytestraises ValueError TypeErrorr~)r+paramserr_msgrrs r,%test_init_gradient_and_hessian_raisesrs 466D  I.g > > >RR:D:QQQQ&QQ'RRRRRRRRRRRRRRRRRRsA  AAzloss, params, err_type, err_msgr/z4quantile must be an instance of float, not NoneType.zquantile == 0, must be > 0.zquantile == 1.1, must be < 1.cttj||5|di|ddddS#1swxYwYdS)z/Test that loss raises errors for invalid input.rNr))rr)r+rerr_typers r,#test_loss_init_parameter_validationrsB xw / / / vs -11cd}t||ddd\}}tj|}tj|}|||t |||ksJdS)z Test that losses can be pickled.rrArDrGrr~N)ripickledumpsloadsr)r+rbrhrg pickled_lossunpickled_losss r,test_loss_pickler%sI9   FN<%%L\,//N 4vn = = =f^DDDBB      r.r)r0rr3rr4rMcBt|}t|}d}t||d\}}|j|}|||||z}|||||z}t|||||\} } |||\} } t| || zt| || z|dz| zzdS)zCTest for identical losses when only the link function is different.r1r|rGrcr~r4N) rrrirYrr+rrr) rhalf_tweedie_loghalf_tweedie_identityrbrhrgrloss_log loss_identity gradient_log hessian_loggradient_identityhessian_identitys r,%test_tweedie_log_identity_consistencyr7s'Q///3!<<<I9 FN " * *> : :F $$n%11&99:H*..f/66v>>?MHm,,,!1 A An!B!!L++@*P*Pf+Q++''L&+<"<===V//&!)>N2NNr.z array_api_loss_class, loss_class)rrr method_name)__call__rr+ruse_sample_weightz"namespace, device_name, dtype_namec d}t|||\}} t|} |dkrdnd} d} d} ||| }|}t|| dd | \}}||}||}||| }||| }|rvt j| }|d d |  dd|}||| }nd}d}t||}t||}||||}td5||||}|dkrt j ||sJnNt|tr(t||D]\}}|||||| | n|||||| | ddddS#1swxYwYdS)Nctt|td||||j|jksJt |t |ksJdS)Ncpuxpr$r)rr!rNrarray_api_device result_xp result_npraw_prediction_xprrrs r,_assert_array_api_resultz5test_loss_array_api.._assert_array_api_result~sv  I"U 3 3 3YTPT    "3"99999 **.>?P.Q.QQQQQQQr.float32rrrGrCrrA)ir;rr#rrFrLrrT)array_api_dispatchrr)r%r rirWasarrayrNrOrPrTrrWr iscloser9rHzip)array_api_loss_class loss_classrr namespace device_name dtype_namerrr$rr random_seedrbarray_api_loss_instance loss_instancerhrg y_true_xprrfsample_weight_npsample_weight_xprFarray_api_methodrrres_xpres_nps r,test_loss_array_apirds4RRR&ijIIJB * % %D**44DKI22bHHHJLLM9   FN]]: & &F#**:66N 6& 11I >& AA i##K00 KKAIK . . 3 3At < < C CJ O O ::&6v:FF ]K 0 0F6 DDnDTI 4 0 0 0$$,*   : % %:i33 3 33 3)U++ &))Y&?&?NFF,,"("(*;!! )(''&7 -s5A;G==HHc Ttjd}d|j_t jddd}t |||\}}|D]}|dkr|||j|}n|||j |}tt|| ||} t| d | |z} | d ksJ| tj| |dkrd nd d ksJdS)NmpmathrCi(i,r)rr$)rgraw_prediction_exprr3rrrDr)r importorskipmpprecrNrr%rrrrXrr r`r) rrrrvalues_to_testrr$valuerpr result_mpmaths r, test_log1pexprsT   * *FFIN[b#..N%ijIIJB    " " 5 6 BBAA 5 6 BBA  #%66!99     fjjVZZ->->)>??@@ q    FM "i//U        !  r.cdtjttjD}t |dks Jd|D]'}|jdksJ|jd|jd(dS)aCheck that Cython extension types in _loss have the correct __module__. When _loss_cython_tree in meson.build is missing __init__.py files, Cython can not detect the package hierarchy and set __module__ = '_loss' instead of 'sklearn._loss._loss' on all Cy* extension types, e.g. `CyHalfMultinomialLoss`. This breaks downstream tools like skops that rely on __module__ for serialization. cBg|]\}}|d|S)Cy) startswith)r*r?objs r,r-z/test_cy_loss_classes_module..s> D# ??4  r.rz+No Cy* classes found in sklearn._loss._losszsklearn._loss._lossz.__module__ == z , expected 'sklearn._loss._loss'N)inspect getmembers _loss_moduleisclasslen __module__r;) cy_classesclss r,test_cy_loss_classes_modulers +L'/JJJ z??Q    M     ~!6666| . .CN . . .7666  r.)rArDrG)grrnumpyrNr numpy.testingrrrscipy.optimizerrrr scipy.specialr sklearnr sklearn._lossr rsklearn._loss.linkr rsklearn._loss.lossrrrrrrrrrrrrrrrr sklearn.utilsrsklearn.utils._array_apir r!r"r$rsklearn.utils._testingr%r&r'listvalues ALL_LOSSESLOSS_INSTANCESr@rirwmark parametrizerinfY_COMMON_PARAMS Y_TRUE_PARAMS Y_PRED_PARAMSrrr`log1prrrrrrrrr r#r9rMr_medianr\rarerjrrwryrint64rrrrrrrrrr)r.r,rsv  ======== $#####""""""//////@@@@@@@@$,+++++  T.'."" # # 00Z000K ItO$O!O!O!O#!$$$!$$$!$$$#&&&      CE""""""""J U U U5GHH < <IH _1SzRVGRV+<=_3#srvgr4-HI_1SzRVGRq"&+IJ_1SzRVGRq"&+IJ2&&&c bfWbf4EF1%%%'>'>'>"&"&@QR3'''#srvgr45PQ1%%%SzRVGRq"&3QR1%%%SzRVGRq"&3QRBF7B26*BCB"&"c26 :;'2_R Y[[1#r_24_1ay"-_3!b)2&&&<1%%%ay"53'''!b1!Q$MMM2.  _QC _2MMM2_1r===1_3aS)2&&&MMM:1%%%}}}b93'''aS1aV$S#JA/  'm#77 7'm#77 7Js    S#q!Q/s #sCd3s c " " "Cad;s d # # #S#~xN s d # # #S#xE s Cq ) ) )3_dDQ s Cq ) ) )3ZtLs   CAFBF1II ,=uaHs #vrvayy&"&))e*;YNs q ! ! !3q 3DdDQs ! q ) ) )3QVRVAYY5FdSs ! q ) ) )3VRVAYY5FdSs $ #! , , ,   )    s,      BF1II BHQKK$* *    +sr    S%Aq1sst    S%r15usv    S$1a0wsx    S$R3ysz    S%r15{s|    S%Y8MN}s~    S%F+@*AA*EFFs@    S%y:OPAsB    S%F+@*AA*EFFCsD    S$I7LMEsF    S$E*?)@1)DEEGsH    S$a1FGIsJ    S%3JKKsL    S$1a0MsN    S$a3OsR       $ #  Qs`    S%Aq1asb    S#q!Q/csd    S#sAq1esh ! , , ,  OO Iooo & & ,    gsx ! , , ,  OO Iooo & & ,    wsH ! , , ,  OO Iooo & & ,    GsX ! , , ,  NN Innn % % .    Wsh mwwpBBqwwpB6,,*UDM::bj"*%=>>rz2:&>??4)44$++$++q!f--Y7Y7.-,+,+54@??>;:-,Y7x5GHH4/::K$K$;:IHK$\5GHH4/::L>L>;:IHL>^5GHH68*<==BFBF>=IHBFJ5GHH  IH <5GHH4/::-H-H;:IH-H`5GHH4/::VKVK;:IHVKr   "+X+X#$+X\5GHH4/::>9>9;:IH>9B    RWh/ ")X. d # # #%E%ExP   BGY/ "'=1   BG]3    RWj1  //  />///."""<"HBH[[[$9$9828KKK;P;P#QRRHBH^^^$<$S>S#TUUEEVUSRED5GHH((IH(V,,4/::2:rz":;;*--!*!*.-<;;:-,!*H,,bh  M"( M M M RR-,R%     B    O  )  z3'5TU     B    O  )  Z%z3RS5>?> 5GHHIH"55566))76)X& !#34 $&9: /2 GFFDDD,udm<<(--//PP =<"Pf(--//   8     r.