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IF Ht$(LMHHD$ HD$(CHIx HIHHKHAH~LKH*I9F(L-H=RIULFKHH tHCH5>HHH IMHx HH!L $EL $HI#A$tA$IFL EtEIFHhHI9Ak LHt$(L $HHD$ Lt$(L $IMIxHIuLL$FL$IExHIEuLL$FL$M} AtAI$NHI$HEMԅIHHEMtI$xHI$HHL[]A\A]A^A_fDL FqLIIH L=IF(H=qIWLH$aIIH tAIFH5XLHH IM Ix HIL=lH=LL$IWLHLL$HI;tAICLL$LL\$H59HH L\$LL$HHaIx HIH<$LL$L)FLL$HI+L5H=MH$IVL=HL$LL$HIh tAEIELL$LL$H5FHHn L$LL$IMIExHIEHAE1HH9C5 fInfInſLT$flLL$L$HT$HD$0)D$ FL$LL$HLT$IH5HT$HptHD$ LHLL$J40L\$LT$0L$HD$}GML$L\$LL$ItIExHIEIx HIMIx HIqIx HIEHx HHM(L $JAL $HI> A$tA$IEL IELpHI9A LHt$(L $HHD$ Ll$(L $IMIExHIE<Ix HIMI$xHI$MYfIx HIE1AMtIExHIEMtIx HIDH=>Mt;I$HI$E1HeHE09@HGHE;HHE-HeALXA7HL $DAL $HExHHEuM봐MkCLsyIH)E1E111AHHHHH@fL@cBHyHHE1E11ALh@kLX@7LH@dE1HHEE1LE1@HbHIH9GH=`1E1E1A11E1fAE1E11DL}LmAtAAEtAEHExHHEIFHt$ LL|$ HD$(bIIHIwL/?jf.I]M}tAtAIExHIEIF Ht$ LH\$ HD$(HHHHH>vfDE1E1ALMcDLLL$k>LL$HX>LL$D>L$LL$,>L$LL$HD$q@LyvL\$LL$HI5E1E11ADMtIx HIMtIx HIMIHIL=LL$t=L$MLLT$LL$L$J=LT$LL$L$L(=5LLT$L$=LT$L$:LL$tH|$8HG HGHHHH)HHH:HcAH9 AHD$HXtH-UH=HUH:IHtALH7H x HHIx HI~15IHKHD$HXtIc8IHHD$@fInH=1fHnHHD$(Hfl)D$@:IHx HHIExHIE01E1MRIGH;t H;AALE1HD$ Ix HINE1MH|$ 4HEHH9]I9HEJtIMtIExHIEHL$LyAtALyHAE1HI9GjfL\$@L\$HT$D$H7L\$HIH HT$HHtHD$(LLL\$LD$J4(H\$H8L\$LD$IMtIx HI%Ix HIqIx HImMTIFI;F AUtAUIVL,HIFIExHIEI[HtHT$8HL$8LHT$@HVHAP3_AXH|$8fDH)‹GHHcAH9WHH5H8a46HnA2HL$8HT$@LE1HL%AT螲Y^/H|$8HHALjL 9H @L3L2HLD$FLD$E1E1Mf.AxIx HIMtIExHIE{HtHExHHEpMtIx HIgDH=.E1EH|$8HTHIHH<22DE1E1IE1LIx HIH$HAxHHME11f1fDL1`Lx1 Lh1LD$fDHP1qL@1uHD$ LE1J@L1mL1xH0L0H0 GWHH HcAH9dGWHH HHcAH99@HD$ HHHLl$3LD$Ht"HH2H9PLD$2LD$HExHHEMIHIL/L/I9J\@=fM_MoAtAAEtAEIx HI7ME1R@Lp/L`/nLL1 IE117H(/{1HgIHHAtE11E1fL%iA$tA$HHt$HLHD$@HD$HHI$xHI$Ht 1H蒿HExHHEAu AxLL\$ME1B.L\$ L 3HHH@HHD$ HI ML-TH-lH'1H*H@`HHHHHrH@L%L9udDyHEHwiH)‹EHHcAH9HEHHEH-H聙HHtH@HHH)HHt~HtZH.0HcAH9tH_HH5H8s-HEHHEH,EUHH HcAH9 륋EUHH HHcAH9HLD$0,LD$ME1[f/H|HH5 H8,aH@`HtfHHtZHIHtML9`u2L˜AIEsHIEeL+XHIHu.HHH5 H8/,.HAtE11E1^rHHtakes no arguments%.200s() %s (%zd given)takes exactly one argumentBad call flags for CyFunctiontakes no keyword arguments%.200s() %san integer is required__pyx_capi____loader__loader__file__origin__package__parent__path__submodule_search_locationsneeds an argumentkeywords must be stringsendunparsable format string'complex double''signed char''unsigned char''short''unsigned short''int''unsigned int''long''unsigned long''long long''unsigned long long''double''complex long double''bool''char''complex float''float'a structPython objecta pointera string'long double'buffer dtypenpy_uint32cannot import name %Sat mostat leastgenerate_stateexactly__getstate____setstate____reduce____del__random_rawtupleExpected %s, got %.200s__pyx_unpickle_SeedSequence__setstate_cython__spawn_benchmarkname '%U' is not defined__init__BitGenerator__reduce_cython__Missing type object_int_to_uint32_array_coerce_to_uint32_arraybuiltinscython_runtime__builtins__numpy.random.bit_generatordoes not match_cython_3_1_04294967296__debug__numpyflatiterbroadcastndarraygenericnumberunsignedintegerinexactcomplexfloatingflexiblecharacterufuncnumpy.random._commondoubleLEGACY_POISSON_LAM_MAXuint64_tMAXSIZEPyObject *(bitgen_t *)prepare_cffiprepare_ctypesnumpy._core._multiarray_umathnumpy.core._multiarray_umath_ARRAY_API_ARRAY_API is NULL pointernumpy.import_array__orig_bases____module____dictoffset____vectorcalloffset____weaklistoffset__func_doc__doc__func_name__name____qualname__func_dict__dict__func_globals__globals__func_closure__closure__func_code__code__func_defaults__defaults____kwdefaults____annotations___is_coroutineentropyspawn_keypool_sizepooln_children_spawned_seed_seqlockcapsulebase class '%.200s' is not a heap typeextension type '%.200s' has no __dict__ slot, but base type '%.200s' has: either add 'cdef dict __dict__' to the extension type or add '__slots__ = [...]' to the base type%s() got an unexpected keyword argument '%U'__int__ returned non-int (type %.200s). The ability to return an instance of a strict subclass of int is deprecated, and may be removed in a future version of Python.__int__ returned non-int (type %.200s)value too large to convert to intC variable %.200s.%.200s has wrong signature (expected %.500s, got %.500s)%.200s does not export expected C variable %.200sC function %.200s.%.200s has wrong signature (expected %.500s, got %.500s)%.200s does not export expected C function %.200sInterpreter change detected - this module can only be loaded into one interpreter per process.Shared Cython type %.200s is not a type objectShared Cython type %.200s has the wrong size, try recompilingmetaclass conflict: the metaclass of a derived class must be a (non-strict) subclass of the metaclasses of all its basesunbound method %.200S() needs an argument%.200s.%.200s is not a type object%.200s.%.200s size changed, may indicate binary incompatibility. Expected %zd from C header, got %zd from PyObject%s.%s size changed, may indicate binary incompatibility. Expected %zd from C header, got %zd from PyObjectUnexpected format string character: '%c'%.200s() keywords must be strings%s() got multiple values for keyword argument '%U'invalid vtable found for imported typejoin() result is too long for a Python string__annotations__ must be set to a dict object__qualname__ must be set to a string object__name__ must be set to a string object__kwdefaults__ must be set to a dict objectchanges to cyfunction.__kwdefaults__ will not currently affect the values used in function calls__defaults__ must be set to a tuple objectchanges to cyfunction.__defaults__ will not currently affect the values used in function callsfunction's dictionary may not be deletedsetting function's dictionary to a non-dictinstance exception may not have a separate valuecalling %R should have returned an instance of BaseException, not %Rraise: exception class must be a subclass of BaseException while calling a Python objectNULL result without error in PyObject_CallBuffer dtype mismatch, expected %s%s%s but got %sBuffer dtype mismatch, expected '%s' but got %s in '%s.%s'Expected a dimension of size %zu, got %zuExpected %d dimensions, got %dPython does not define a standard format string size for long double ('g')..Buffer dtype mismatch; next field is at offset %zd but %zd expectedBig-endian buffer not supported on little-endian compilerBuffer acquisition: Expected '{' after 'T'Cannot handle repeated arrays in format stringDoes not understand character buffer dtype format string ('%c')Expected a dimension of size %zu, got %dExpected a comma in format string, got '%c'Expected %d dimension(s), got %dUnexpected end of format string, expected ')'Buffer has wrong number of dimensions (expected %d, got %d)Item size of buffer (%zd byte%s) does not match size of '%s' (%zd byte%s)value too large to convert to uint32_tcan't convert negative value to uint32_tnumpy/random/bit_generator.pyxnumpy.random.bit_generator.__defaults__%.200s() takes %.8s %zd positional argument%.1s (%zd given)numpy.random.bit_generator.SeedlessSeedSequence.generate_statestrings are too large to concatnumpy.random.bit_generator.SeedSequence.__repr__numpy.random.bit_generator.SeedSequence.state.__get__Out of bounds on buffer access (axis %d)numpy.random.bit_generator.SeedSequence.mix_entropynumpy.random.bit_generator.BitGenerator.__getstate__numpy.random.bit_generator.BitGenerator.__setstate__numpy.random.bit_generator.BitGenerator.__reduce__numpy.random.bit_generator.BitGenerator.state.__get__numpy.random.bit_generator.BitGenerator.state.__set__numpy.random.bit_generator.BitGenerator.random_rawnumpy.random.bit_generator.BitGenerator.ctypes.__get__numpy.random.bit_generator.BitGenerator.cffi.__get__numpy/random/bit_generator.pxdnumpy.random.bit_generator.SeedSequence.pool_size.__get__numpy.random.bit_generator.SeedSequence.n_children_spawned.__get__'NoneType' object is not subscriptablehasattr(): attribute name must be stringnumpy.random.bit_generator.__pyx_unpickle_SeedSequence__set_statenumpy.random.bit_generator.__pyx_unpickle_SeedSequencenumpy.random.bit_generator.SeedSequence.__setstate_cython__numpy.random.bit_generator.ISpawnableSeedSequence.spawnobject of type 'NoneType' has no len()numpy.random.bit_generator.__pyx_unpickle_SeedlessSeedSequence__set_statenumpy.random.bit_generator.SeedlessSeedSequence.__setstate_cython____pyx_unpickle_SeedlessSeedSequencenumpy.random.bit_generator.__pyx_unpickle_SeedlessSeedSequencenumpy.random.bit_generator.SeedSequence.spawnnumpy.random.bit_generator.BitGenerator._benchmarknumpy.random.bit_generator.ISeedSequence.generate_statenumpy.random.bit_generator.SeedlessSeedSequence.spawn__mro_entries__ must return a tuplenumpy.random.bit_generator.BitGenerator.__init__numpy.random.bit_generator.SeedlessSeedSequence.__reduce_cython__Cannot convert %.200s to %.200snumpy.random.bit_generator.SeedSequence.__init__numpy.random.bit_generator._int_to_uint32_array%.200s object is not an iteratornumpy.random.bit_generator.SeedSequence.generate_statenumpy.random.bit_generator.SeedSequence.__reduce_cython__numpy.random.bit_generator._coerce_to_uint32_arraynumpy.random.bit_generator.SeedSequence.get_assembled_entropynumpy.random.bit_generator.BitGenerator.spawnUnable to initialize pickling for %.200sModule 'bit_generator' has already been imported. Re-initialisation is not supported.compile time Python version %d.%d of module '%.100s' %s runtime version %d.%dmultiple bases have vtable conflict: '%.200s' and '%.200s'PyObject *(bitgen_t *, PyObject *, Py_ssize_t, PyObject *)PyObject *(bitgen_t *, PyObject *, PyObject *, PyObject *)_ARRAY_API is not PyCapsule objectmodule compiled against ABI version 0x%x but this version of numpy is 0x%xmodule was compiled against NumPy C-API version 0x%x (NumPy 1.20) but the running NumPy has C-API version 0x%x. Check the section C-API incompatibility at the Troubleshooting ImportError section at https://numpy.org/devdocs/user/troubleshooting-importerror.html#c-api-incompatibility for indications on how to solve this problem.FATAL: module compiled as unknown endianFATAL: module compiled as little endian, but detected different endianness at runtime../numpy/__init__.cython-30.pxdinit numpy.random.bit_generator_cython_3_1_0.cython_function_or_methodnumpy.random.bit_generator.__pyx_defaultsnumpy.random.bit_generator.SeedlessSeedSequence A seed sequence for BitGenerators with no need for seed state. See Also -------- SeedSequence, ISeedSequence numpy.random.bit_generator.SeedlessSequencenumpy.random.bit_generator.SeedSequence SeedSequence(entropy=None, *, spawn_key=(), pool_size=4) SeedSequence mixes sources of entropy in a reproducible way to set the initial state for independent and very probably non-overlapping BitGenerators. Once the SeedSequence is instantiated, you can call the `generate_state` method to get an appropriately sized seed. Calling `spawn(n) ` will create ``n`` SeedSequences that can be used to seed independent BitGenerators, i.e. for different threads. Parameters ---------- entropy : {None, int, sequence[int]}, optional The entropy for creating a `SeedSequence`. All integer values must be non-negative. spawn_key : {(), sequence[int]}, optional An additional source of entropy based on the position of this `SeedSequence` in the tree of such objects created with the `SeedSequence.spawn` method. Typically, only `SeedSequence.spawn` will set this, and users will not. pool_size : {int}, optional Size of the pooled entropy to store. Default is 4 to give a 128-bit entropy pool. 8 (for 256 bits) is another reasonable choice if working with larger PRNGs, but there is very little to be gained by selecting another value. n_children_spawned : {int}, optional The number of children already spawned. Only pass this if reconstructing a `SeedSequence` from a serialized form. Notes ----- Best practice for achieving reproducible bit streams is to use the default ``None`` for the initial entropy, and then use `SeedSequence.entropy` to log/pickle the `entropy` for reproducibility: >>> sq1 = np.random.SeedSequence() >>> sq1.entropy 243799254704924441050048792905230269161 # random >>> sq2 = np.random.SeedSequence(sq1.entropy) >>> np.all(sq1.generate_state(10) == sq2.generate_state(10)) True numpy.random.bit_generator.BitGenerator BitGenerator(seed=None) Base Class for generic BitGenerators, which provide a stream of random bits based on different algorithms. Must be overridden. Parameters ---------- seed : {None, int, array_like[ints], SeedSequence}, optional A seed to initialize the `BitGenerator`. If None, then fresh, unpredictable entropy will be pulled from the OS. If an ``int`` or ``array_like[ints]`` is passed, then it will be passed to `~numpy.random.SeedSequence` to derive the initial `BitGenerator` state. One may also pass in a `SeedSequence` instance. All integer values must be non-negative. Attributes ---------- lock : threading.Lock Lock instance that is shared so that the same BitGenerator can be used in multiple Generators without corrupting the state. Code that generates values from a bit generator should hold the bit generator's lock. See Also -------- SeedSequence Get or set the PRNG state The base BitGenerator.state must be overridden by a subclass Returns ------- state : dict Dictionary containing the information required to describe the state of the PRNG Get the seed sequence used to initialize the bit generator. .. versionadded:: 1.25.0 Returns ------- seed_seq : ISeedSequence The SeedSequence object used to initialize the BitGenerator. This is normally a `np.random.SeedSequence` instance. ctypes interface Returns ------- interface : namedtuple Named tuple containing ctypes wrapper * state_address - Memory address of the state struct * state - pointer to the state struct * next_uint64 - function pointer to produce 64 bit integers * next_uint32 - function pointer to produce 32 bit integers * next_double - function pointer to produce doubles * bitgen - pointer to the bit generator struct CFFI interface Returns ------- interface : namedtuple Named tuple containing CFFI wrapper * state_address - Memory address of the state struct * state - pointer to the state struct * next_uint64 - function pointer to produce 64 bit integers * next_uint32 - function pointer to produce 32 bit integers * next_double - function pointer to produce doubles * bitgen - pointer to the bit generator struct @ddd@dddddd`ddddcddcccdddddddddddddddd@d@dcddPd`ddddcddd@dcd@dԄt&@ZȄރ͂͂ҁށfr~&@ZƁ  J 7  IIIIIIIIIIIIIIIIIIIIIIIIIII˅IIIIIIItddtddddd ddddddddddddddddddddtt9dL& dddddtdtօօօ;5(߅߅R߅w700010203040506070809101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899Used in tests random_raw(self, size=None) Return randoms as generated by the underlying BitGenerator Parameters ---------- size : int or tuple of ints, optional Output shape. If the given shape is, e.g., ``(m, n, k)``, then ``m * n * k`` samples are drawn. Default is None, in which case a single value is returned. output : bool, optional Output values. Used for performance testing since the generated values are not returned. Returns ------- out : uint or ndarray Drawn samples. Notes ----- This method directly exposes the raw underlying pseudo-random number generator. All values are returned as unsigned 64-bit values irrespective of the number of bits produced by the PRNG. See the class docstring for the number of bits returned. spawn(n_children) Create new independent child bit generators. See :ref:`seedsequence-spawn` for additional notes on spawning children. Some bit generators also implement ``jumped`` as a different approach for creating independent streams. .. versionadded:: 1.25.0 Parameters ---------- n_children : int Returns ------- child_bit_generators : list of BitGenerators Raises ------ TypeError When the underlying SeedSequence does not implement spawning. See Also -------- random.Generator.spawn, random.SeedSequence.spawn : Equivalent method on the generator and seed sequence. spawn(n_children) Spawn a number of child `SeedSequence` s by extending the `spawn_key`. See :ref:`seedsequence-spawn` for additional notes on spawning children. Parameters ---------- n_children : int Returns ------- seqs : list of `SeedSequence` s See Also -------- random.Generator.spawn, random.BitGenerator.spawn : Equivalent method on the generator and bit generator. generate_state(n_words, dtype=np.uint32) Return the requested number of words for PRNG seeding. A BitGenerator should call this method in its constructor with an appropriate `n_words` parameter to properly seed itself. Parameters ---------- n_words : int dtype : np.uint32 or np.uint64, optional The size of each word. This should only be either `uint32` or `uint64`. Strings (`'uint32'`, `'uint64'`) are fine. Note that requesting `uint64` will draw twice as many bits as `uint32` for the same `n_words`. This is a convenience for `BitGenerator`\ s that express their states as `uint64` arrays. Returns ------- state : uint32 or uint64 array, shape=(n_words,) spawn(n_children) Spawn a number of child `SeedSequence` s by extending the `spawn_key`. See :ref:`seedsequence-spawn` for additional notes on spawning children. Parameters ---------- n_children : int Returns ------- seqs : list of `SeedSequence` s generate_state(n_words, dtype=np.uint32) Return the requested number of words for PRNG seeding. A BitGenerator should call this method in its constructor with an appropriate `n_words` parameter to properly seed itself. Parameters ---------- n_words : int dtype : np.uint32 or np.uint64, optional The size of each word. This should only be either `uint32` or `uint64`. Strings (`'uint32'`, `'uint64'`) are fine. Note that requesting `uint64` will draw twice as many bits as `uint32` for the same `n_words`. This is a convenience for `BitGenerator`\ s that express their states as `uint64` arrays. Returns ------- state : uint32 or uint64 array, shape=(n_words,) Coerce an input to a uint32 array. If a `uint32` array, pass it through directly. If a non-negative integer, then break it up into `uint32` words, lowest bits first. If a string starting with "0x", then interpret as a hex integer, as above. If a string of decimal digits, interpret as a decimal integer, as above. If a sequence of ints or strings, interpret each element as above and concatenate. Note that the handling of `int64` or `uint64` arrays are not just straightforward views as `uint32` arrays. If an element is small enough to fit into a `uint32`, then it will only take up one `uint32` element in the output. This is to make sure that the interpretation of a sequence of integers is the same regardless of numpy's default integer type, which differs on different platforms. Parameters ---------- x : int, str, sequence of int or str Returns ------- seed_array : uint32 array Examples -------- >>> import numpy as np >>> from numpy.random.bit_generator import _coerce_to_uint32_array >>> _coerce_to_uint32_array(12345) array([12345], dtype=uint32) >>> _coerce_to_uint32_array('12345') array([12345], dtype=uint32) >>> _coerce_to_uint32_array('0x12345') array([74565], dtype=uint32) >>> _coerce_to_uint32_array([12345, '67890']) array([12345, 67890], dtype=uint32) >>> _coerce_to_uint32_array(np.array([12345, 67890], dtype=np.uint32)) array([12345, 67890], dtype=uint32) >>> _coerce_to_uint32_array(np.array([12345, 67890], dtype=np.int64)) array([12345, 67890], dtype=uint32) >>> _coerce_to_uint32_array([12345, 0x10deadbeef, 67890, 0xdeadbeef]) array([ 12345, 3735928559, 16, 67890, 3735928559], dtype=uint32) >>> _coerce_to_uint32_array(1234567890123456789012345678901234567890) array([3460238034, 2898026390, 3235640248, 2697535605, 3], dtype=uint32) Incompatible checksums (0x%x vs (0x3eaa222, 0xc464c19, 0xf88304a) = (entropy, n_children_spawned, pool, pool_size, spawn_key)) Abstract base class for seed sequences that can spawn. seedless SeedSequences cannot generate statenumpy._core.umath failed to importnumpy._core.multiarray failed to importThe underlying SeedSequence does not implement spawning.The size of the entropy pool should be at least SeedlessSeedSequence.generate_stateSeedlessSeedSequence.__reduce_cython__SeedSequence expects int or sequence of ints for entropy not {}Not implemented in base BitGeneratorIncompatible checksums (0x%x vs (0xe3b0c44, 0xda39a3e, 0xd41d8cd) = ())BitGenerator is a base class and cannot be instantizedbz%zQgU&1qQ 1Cq 1Kq 1CuA vQa 1A *AQz$gQ#1A 1D iq 3as#Q 2V1Db !*!3d%qrQaT44Dt>> import numpy as np >>> from numpy.random.bit_generator import _coerce_to_uint32_array >>> _coerce_to_uint32_array(12345) array([12345], dtype=uint32) >>> _coerce_to_uint32_array('12345') array([12345], dtype=uint32) >>> _coerce_to_uint32_array('0x12345') array([74565], dtype=uint32) >>> _coerce_to_uint32_array([12345, '67890']) array([12345, 67890], dtype=uint32) >>> _coerce_to_uint32_array(np.array([12345, 67890], dtype=np.uint32)) array([12345, 67890], dtype=uint32) >>> _coerce_to_uint32_array(np.array([12345, 67890], dtype=np.int64)) array([12345, 67890], dtype=uint32) >>> _coerce_to_uint32_array([12345, 0x10deadbeef, 67890, 0xdeadbeef]) array([ 12345, 3735928559, 16, 67890, 3735928559], dtype=uint32) >>> _coerce_to_uint32_array(1234567890123456789012345678901234567890) array([3460238034, 2898026390, 3235640248, 2697535605, 3], dtype=uint32) BitGenerator base class and SeedSequence used to seed the BitGenerators. SeedSequence is derived from Melissa E. O'Neill's C++11 `std::seed_seq` implementation, as it has a lot of nice properties that we want. https://gist.github.com/imneme/540829265469e673d045 https://www.pcg-random.org/posts/developing-a-seed_seq-alternative.html The MIT License (MIT) Copyright (c) 2015 Melissa E. O'Neill Copyright (c) 2019 NumPy Developers Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. _BitGenerator__bit_generator_ctor Abstract base class for seed sequences. ``BitGenerator`` implementations should treat any object that adheres to this interface as a seed sequence. See Also -------- SeedSequence, SeedlessSeedSequence A,.a. $1 fAQ :U&1 uF!2Q q *AQ&&!E$a IU!1 t1A  !   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