i* H%SSKrSSKrSSKrSSKrSSKrSSKJrJrJr SSK J r SSKJ r SSK J r Jr SSKJr SSKrSSKJrJr SSKJrJrJr \ (aSS K Jr "S S \5rO \Rr\ "5r\"\5r\"\\05r\\ \4\!S '"S S5r"Sq#\S-\!S'\(d\(dS\S\ 4Sjr$\$"\%"55r&OSr&S\SS4Sjr'\("5r)\(\\!S'SS\S\*\/S4\/S444Sjjr+\RXSS\ S\S4Sjj5r-g)N)Callable GeneratorHashable)count)Random) TYPE_CHECKINGAny)WeakValueDictionary)HypothesisWarningInvalidArgument)FREE_THREADED_CPYTHONGRAALPYPYPY)ProtocolcV\rSrSrS\S\S\4SjrS\S\S\4SjrS\S\S\4SjrSrg ) RandomLikeargskwargsreturncgNselfrrs Z/var/www/html/ai-image-ml/venv/lib/python3.13/site-packages/hypothesis/internal/entropy.pyseedRandomLike.seed s#cgrrrs rgetstateRandomLike.getstate!crcgrrrs rsetstateRandomLike.setstate"r#rrN) __name__ __module__ __qualname____firstlineno__r rr!r%__static_attributes__rrrrrs8=c=S=S=A#AAAA#AAArrRANDOMS_TO_MANAGEc\rSrSrSSjrSrg)NumpyRandomWrapper1NcS[R;deSSKnURRUlURR UlURRUlg)Nnumpyr) sysmodules numpy.randomrandomr get_stater! set_stater%)rr1s r__init__NumpyRandomWrapper.__init__2sL#++%%% LL%%  ..  .. r)r!rr%rN)r'r(r)r*r8r+rrrr.r.1s/rr. NP_RANDOMrrc.[R"U5$r)r2 getrefcount)r<s r_get_platform_base_refcountr?Bsq!!rc[US5(a"[US5(a[US5(d[SU<S35eU[RR 5R 5Vs/sHnU"5=ncMUPM sn;ag[ (d[(d[R"5 [R"U5(dR[R"U5[::a[SUS35e[(d[ R""S [$S S 9 U[['[(5'gs snf) aRegister (a weakref to) the given Random-like instance for management by Hypothesis. You can pass instances of structural subtypes of ``random.Random`` (i.e., objects with seed, getstate, and setstate methods) to ``register_random(r)`` to have their states seeded and restored in the same way as the global PRNGs from the ``random`` and ``numpy.random`` modules. All global PRNGs, from e.g. simulation or scheduling frameworks, should be registered to prevent flaky tests. Hypothesis will ensure that the PRNG state is consistent for all test runs, always seeding them to zero and restoring the previous state after the test, or, reproducibly varied if you choose to use the :func:`~hypothesis.strategies.random_module` strategy. ``register_random`` only makes `weakrefs `_ to ``r``, thus ``r`` will only be managed by Hypothesis as long as it has active references elsewhere at runtime. The pattern ``register_random(MyRandom())`` will raise a ``ReferenceError`` to help protect users from this issue. This check does not occur for the PyPy interpreter. See the following example for an illustration of this issue .. code-block:: python def my_BROKEN_hook(): r = MyRandomLike() # `r` will be garbage collected after the hook resolved # and Hypothesis will 'forget' that it was registered register_random(r) # Hypothesis will emit a warning rng = MyRandomLike() def my_WORKING_hook(): register_random(rng) rr!r%zr=z' does not have all the required methodsNz `register_random` was passed `r=z` which will be garbage collected immediately after `register_random` creates a weakref to it. This will prevent Hypothesis from managing this PRNG. See the docs for `register_random` for more details.zIt looks like `register_random` was passed an object that could be garbage collected immediately after `register_random` creates a weakref to it. This will prevent Hypothesis from managing this PRNG. See the docs for `register_random` for more details.) stacklevel)hasattrr r,datacopyvaluesrrgccollect get_referrersr2r>_PLATFORM_REF_COUNTReferenceErrorr warningswarnr next_RKEY)r<refr5s rregister_randomrRMsP Av  71j#9#9ga>T>T$KLMM$))..0779 9CeOF 9   DGG ""q!%88$6qc:+*  Q& &'d5k"E s 3EE_known_random_state_hashesrc^^[T[5(deSTs=::aS:de e0mS[R;a'[c [ 5=q[ [[5'SUU4SjjnSU4SjjnX4$)aReturn a pair of functions which respectively seed all and restore the state of all registered PRNGs. This is used by the core engine via `deterministic_PRNG`, and by users via `register_random`. We support registration of additional random.Random instances (or other objects with seed, getstate, and setstate methods) to force determinism on simulation or scheduling frameworks which avoid using the global random state. See e.g. #1709. rlr1c>T(ae[RR5R5HupU"5nUcMUR 5TU'U[ :XaG[ 5nURT5 [R[UR 555 URT5 M gr) r,rErFitemsr!_global_random_rkeyrrrSaddhash)krQr< dummy_randomrstatess rseed_all)get_seeder_and_restorer..seed_allsz (,,11399;FAAy F1I'' &x !!$'*..tL4I4I4K/LM FF4L-TR5HXup[RU5nUcMU[:Xa[R [ U55 URU5 MZ TR5 gr) rVr,getrWrSrXrYr%clear)rZstater<r\s r restore_all,get_seeder_and_restorer..restore_alls_ HA!%%a(Ay''*..tE{; JJu '  rr:) isinstanceintr2r3r;r.r,rOrP)rr]rcr\s` @rget_seeder_and_restorerrgsz dC   u    "F#++  9K9M MI)$u+6''R    r)NNNc#V# [RRRcT[ 5[RRl[ [RRR5 [ U5upU"5 Sv U"5 g!U"5 f=f7f)a-Context manager that handles random.seed without polluting global state. See issue #1266 and PR #1295 for details and motivation - in short, leaving the global pseudo-random number generator (PRNG) seeded is a very bad idea in principle, and breaks all kinds of independence assumptions in practice. N) hypothesiscore threadlocal_hypothesis_global_randomrrRrg)rr]rcs rdeterministic_PRNGrmsm ##==E@F ##= 33MMN3D9H J  sBB)BB) B&&B))r). contextlibrHr5r2rMcollections.abcrrr itertoolsrrtypingrr weakrefr hypothesis.corerihypothesis.errorsr r hypothesis.internal.compatr rrrrrPrOrWr,rf__annotations__r.r;r?objectrKrRsetrStuplergcontextmanagerrmrrrr{si 99%'@KKBXB J 5k;N&!;&sJ7 / / $ : # "s"s" 6fh?M'zM'dM'j(+uCH,K! K! 8BH xD1 12K!\ S3C)Dr