uki3 UddlmZddlZddlmZmZddlmZddlmZddlm Z ddl m Z m Z ddlZgdZd Zd ed ej$fd Zeej$eezfZeed <ie j2dej$ej4dej$e j6dej$e j8dej$ej:dej$ej<dej$ej>dej$ej@dej$e jBdej$e jDdej$ejFdej$ejHdej$ejJdej$ejLdej$e jNdej$e jPdej$e jRdej$e jTdej$e jVdej$e jXdej$e jZdej$e j\dej$e j^dej$e j`dej$ejbdej$ejddej$ejfdej$ejhdej$ejjdi Z6eed<dZ7ej$e jNdej$e jPdej$e jRdej$e jTdej$e jVdej$e jXdej$e jZdej$e j\dej$e j^dej$e j`dej$ejbdej$ejddej$ejfdej$ejhdej$ejjdiZ8eed<ded e9fdZ:d/dZ;d0dej$deezezdzd eezfdZd"Z?d#Z@d$ZAd%ZBee eBejZCee eBejZDee d&ZEee eBejZFd'ZGd(ZHefd)ZId*ZJddedfd+ZKddedfd,ZL d1d-ZMd.ZNy)2)partialN)Any TypeAlias)api)config)dtypes)tree_map tree_reduce) check_grads check_jvp check_vjpg-C6?xreturnct|dr |jStjj t |x}|St j|jS)Ndtype)hasattrr_dtypespython_scalar_types_to_dtypesgettypenpasarray)rdts T/home/cdr/jupyterlab/.venv/lib/python3.12/site-packages/jax/_src/public_test_util.py_dtyper$sN Q 77N3377Q@@M I ::a=   ToleranceDictg?g?g{Gz?gMbP?gư>gV瞯<_default_tolerancectSN)rrrdefault_tolerancer"Ns rgMb`?gh㈵>default_gradient_tolerancevalc|t|tj xr t|ttt t fSr ) isinstancergenericboolintfloatcomplex)r$s ris_python_scalarr,es, RZZ ( ( YZdCPW=X-YYrc |j|jcxk(rtjk(r&nn#tjj |||ytj tjtjtjtjtjtjtjtjtjg fd}||}||}i}|r||d<|r||d<tj d5tjj"||fi|d|idddy#1swYyxYw)Nerr_msgcX|jvr|jtjS|jtj vr_|jt j |jjdkrtjStjS|S)Nr) rastyperfloat32r _intn_dtypesiinfominint8uint8)rcustom_float_dtypess r maybe_upcastz,_assert_numpy_allclose..maybe_upcastzsuww%% XXbjj !! ww'&&& XXqww!7!;!;a!?bgg NNRXX NN Hratolrtolignoreinvalidr0)rrfloat0rtestingassert_array_equal float4_e2m1fnfloat8_e8m0fnu float8_e3m4 float8_e4m3float8_e4m3b11fnuz float8_e4m3fnfloat8_e4m3fnuz float8_e5m2float8_e5m2fnuzbfloat16errstateassert_allclose)abr;r<r0r:kwr9s @r_assert_numpy_allcloserRhsWW)7>>)JJ!!!Q!8             1o!1o! " 2f: 2f: {{8$<JJq!;r;7;<<._assert_dtypes_matchsZ  AY&) ## #((3((3454rr )rcrdrls r_check_dtypes_matchrns5  R(rcRd}ttjt|||S)Nctjtjtj|j d|j dS)N)rrealdotconjreshaperjs rcontractzinner_prod..contracts7 77266"''!*,,R0!))B-@ AAr)r raddr )rcrdrvs r inner_prodrxs"B RVVXhB7 88rc tjd5tjtj||tjd|tj |||cdddS#1swYyxYw)z1Subtraction that with `inf - inf == 0` semantics.r=r>rrN)rrMwhereequalarraysubtract)rrkrs r_safe_subtractrsX {{8$4 88BHHQNBHHQ$6KK1E2 4444s AA66A?cfd}|S)Nct|d}tj||}td|Dr|j }|S)Nrrzc32K|]}t|ywr )r,).0args r z9_preserve_input_types..wrapped..s 1S C 1s)rrr}allitem)argsrresultfs rwrappedz&_preserve_input_types..wrappedsB 47OE XXahe ,F 1D 11{{}f Mrr!)rrs` r_preserve_input_typesrs .rc0t||t|SNrz)rrrjs rrsq!6!9 Erc&fd}t||S)Nct|}tj|tj||}t |r|j S|Sr)rrmultiplyr}r,r)rrrrOs rmulzscalar_mul..mulsA 1IE [[BHHQe4E BF,Q/6;;=;V;rrm)rcrOrs ` r scalar_mulrs< #r rc*tj|t|fd}tjtj r"|j d|zz}n|}t|r|jS|S)NcLtjjSr)rrrandn)rrngr^srrzrand_like..s"**YSYY.e<ry?) rr^rr issubdtypecomplexfloatingrr,r)rrrrrr^s` @@r rand_likerso ((1+% )% <% r112 Wuzz$'%'1 1F WF*1-969rct||}|t||}|t||}tt||d|z S)Ng?)rrwsubsafe_sub)rprimalstangentsepsdeltaf_posf_negs r numerical_jvprsH Xs #% S% !% S% !% HUE*C#I 66rc||St|ts|S|j}|jD]\}}||t j |<|Sr )r&rUcopyrVrr)rSdefaultoutkvs r_merge_tolerancersV[ N C  J #iikdaC  *rct|t}t|t}tjj d}t t t||}|||\} } t| | ||} t| | t||||} t| | |||r|dndt| | |||r |dydy) aCheck a JVP from automatic differentiation against finite differences. Gradients are only checked in a single randomly chosen direction, which ensures that the finite difference calculation does not become prohibitively expensive even for large input/output spaces. Args: f: function to check at ``f(*args)``. f_vjp: function that calculates ``jax.jvp`` applied to ``f``. Typically this should be ``functools.partial(jax.jvp, f))``. args: tuple of argument values. atol: absolute tolerance for gradient equality. rtol: relative tolerance for gradient equality. eps: step size used for finite differences. err_msg: additional error message to include if checks fail. Raises: AssertionError: if gradients do not match. rr primalprimalr]z tangenttangentN) rr#rrandom RandomStater rrrnrrf) rf_jvprr;r<rr0rrv_outt_outv_out_expectedt_out_expecteds rr r s( $ : ;$ $ : ;$ a # WY,d 3'tW%,%eU#d8.e^, D's;.e^$T-4 )(D e^$T.5 *F;DFrct|t}t|t}tttj j d}||\}} ||} t|| |||r|dndt||} t||| |} t||} t| t| }t| |}t| | }t|||||r |dydy) aCheck a VJP from automatic differentiation against finite differences. Gradients are only checked in a single randomly chosen direction, which ensures that the finite difference calculation does not become prohibitively expensive even for large input/output spaces. Args: f: function to check at ``f(*args)``. f_vjp: function that calculates ``jax.vjp`` applied to ``f``. Typically this should be ``functools.partial(jax.jvp, f))``. args: tuple of argument values. atol: absolute tolerance for gradient equality. rtol: relative tolerance for gradient equality. eps: step size used for finite differences. err_msg: additional error message to include if checks fail. Raises: AssertionError: if gradients do not match. rrrr]rz cotangent projectionzcotangent projectionN) rr#rrrrrrfr rrtrx)rf_vjprr;r<rr0 _rand_likervjpfunrr tangent_out cotangent cotangent_outip ip_expecteds rr r s( $ : ;$ $ : ;$y"))"7"7":;*,-%d8. e^$T-4 )(D Z &'awC8+z5))vd9o./-'=)"; 2+ b+Dt!""78@'=@rc t|}|xst}tt|||tt||| d fd |||y)aCheck gradients from automatic differentiation against finite differences. Gradients are only checked in a single randomly chosen direction, which ensures that the finite difference calculation does not become prohibitively expensive even for large input/output spaces. Args: f: function to check at ``f(*args)``. args: tuple of argument values. order: forward and backwards gradients up to this order are checked. modes: lists of gradient modes to check ('fwd' and/or 'rev'). atol: absolute tolerance for gradient equality. rtol: relative tolerance for gradient equality. eps: step size used for finite differences. Raises: AssertionError: if gradients do not match. )r;r<rcd vrZ|rd|nd} ttj|||dkDr(ttj||f|dz |d vrE|rd|nd} ttj|||dkDrfd }|||dz |d vrH|rd |nd } tt|||dkDrtt||f|dz |yyy) NfwdzJVP of JVPr/revzVJP of VJPcFtjg|\}}||Sr )rvjp)r out_primal_pyvjp_pyrs rrz0check_grads.._check_grads..f_vjpes&"%''!"3d"3 - & &rlinzLIN of LIN)rrjvpr _jvp_from_lin) rrorderr0fwd_msgrev_msgrlin_msg _check_grads _check_jvp _check_vjpmodess ` rrz!check_grads.._check_gradsZs ~'.''#EgGCGGQ'w? WSWWa(4, 7K ~'.''#EgGCGGQ'w?  ' UD%!)W5 ~'.''#EgGM1-tWE W]A.t eaiQ rN)r-)tupleEPSrr r ) rrrrr;r<rrrrs ` @@@rr r @sQ( t$ s#yt$C@*yt$C@*RR,q$rcFtj|g|\}}||}||fSr )r linearize)rrr primal_outf_linrs rrrrs/mmA00*ex + [  r)NNr-r ))rrNNN)O functoolsroperatortypingrrjax._srcrrrrjax._src.tree_utilr r numpyr__all__rrrrUr)r*r__annotations__r@bool_int2int4r7int16int32int64uint2uint4r8uint16uint32uint64rCrErFrDrGrHrIrJrKrLfloat16r3float64 complex64 complex128rr"r#r(r,rRrZrarfrnrxrrrwrrrtrrrrr r r rr!rrrs!&4 4 cbhh #+ 56 y6% NNA% BHHRXX% BHHW\\A% BHHW\\A %  BHHRWWq %  BHHRXX % BHHRXX% BHHRXX% BHHW]]Q% BHHW]]Q% BHHRXX% BHHRYY% BHHRYY% BHHRYY% BHHW " "#S%  BHHW !4!%" BHHW !4#%$ BHHW # #$c BHHW ' '($ BHHW " "#T BHHW $ $%t BHHW !4 BHHW $ $%t BHHW   BHHRZZ$ BHHRZZ$ BHHRZZ% BHHR\\D BHHR]]U;%M@  "((7 !3 "((7   "((7   "((7 ! !"C "((7 % %& "((7 !4 "((7 " "#T "((7   "((7 " "#T "((7  d "((2:: "((2:: "((2:: "((2<<$ "((2==4-M&Z#Z$Z%