Vpf dZddlmZddlmZddlmZddlZddlZ ddl m Z ddl m Z ddl m Z dd lmZdd lmZdd lmZdd lmZmZdd lmZmZmZmZmZmZmZmZm Z m!Z!ej"Z#e j$e j%e j&dZ'dZ(ddZ)ddZ*e e j+deedddZ+e e,e de j-deedddZ.e e j/deedddZ/e e j-deedddZ-e e j0deedddZ0e e j1deeddd Z1e e j2deeddd!Z2e e j3deeddd"Z3e e j4deeddd#Z4e e j5deeddd$Z5e e j6deeddd%Z6e e j7deeddd&Z7e e j8deeddd'Z8e e j9deeddd(Z9e e j:deeddd)Z:e e j;deeddd*Z;e e j<deeddd+Z<e e j=deeddd,Z=e e j>deeddd-Z>e e j?deeddd.Z?e e j@deeddd/Z@e e jAdeeddd0ZAe e jBdedd1ZBe e jCdeeddd2ZCe e jDdeeddd3ZDe e jEdeeddd4ZEe e jFdeeddd5ZFe e jGdeeddd7ZGe e jHdeeddd8ZHe e jIdeeddd9ZIe e jJdeeddd:ZJe e jKdeeddd;ZKe e jLdeeddd<ZLe e,e d=e jLdeeddd>ZMe e jNdeeddd?ZNe e jOdeeddd@ZOe e jPdeedddAZPe e jQdeedddBZQe e jRdeedddCZRe e jSdeedddDZSe e jTdeedddEZTe e jUdeedddFZUe e jVdeedddGZVe e jWdeedddHZWe e jXdeedddIZXe e jYdeedddJZYddMZZe e j[deedddNZ[e e j\deedddOZ\e e j]deedddPZ]e e j^deedddQZ^eedddRZ_eedddSZ`eedddTZaeedddUZbeedddVZceedddWZdeedddXZeeddYZfeeddd\Zge e,e d]e jgdeeddd^Zheeddd_Zieeddd`ZjeddaZkeddbZle e jmdeedddcZmemZnedddZoeddfZpddgZqe e jrdddhZrerZseedddiZtdjZuee e jvdeddkZvdlZwevjxdmZyee e jzdeddnZzezjxdoZ{eedddpZ|eedddqZ}e e j~deedddrZ~e e jdeddsZdtZe e jdedduZe e jdeddvZe e jdeddwZe e jdeZe e jdeddxZe e jdeedddyZe e jdeedddzZe e jdeeddd{ZeZeZe e jdeeddd|ZeZe e jeeddd~Ze e jeedddZe e jddgedddZe e jdeedddZe e jdeddZddZe e jdddZe e jdddZe e jdeedddZe e jdeddZe jde e jdeddZe e jdeedddZe e jdeddZeeddZejxdZdS)z" Implements ufuncs for jax.numpy. ) annotations)Callable)partialN)core) deprecations)dtypes)jit) custom_jvp)lax)Array ArrayLike) check_arraylike promote_argspromote_args_inexactpromote_args_numericpromote_dtypes_inexactpromote_dtypes_numericpromote_shapes_where implementscheck_no_float0s) @cRtj|tj|S)Ndtype)nparrayrr)xconsts U/var/www/html/nettyfy-visnx/env/lib/python3.11/site-packages/jax/_src/numpy/ufuncs.py_constant_liker#/s %v|A / / //r r returnr ctjtt|tj||SN)r selectisposinfreal_zerosr s r" _replace_infr-2s, HT!WW%%sz!}}a 8 88r$cl|jtkr|n"tj|t |dS)Nr)rboolr ne _lax_constr,s r"_to_boolr25s,goo36!Z1-=-=#>#>>r$numpy)moduleT)inlinec:tjtd|S)Nfabs)r absrr,s r"r7r78s &vq11 22r$bitwise_invertc:tjtd|S)Nr9r bitwise_notrr,s r"r9r9=s ,'7;; <> (!44 55r$ctd|tjtj|drt j|St jtd|S)NceilrJ)rrrLrr rErNrr,s r"rNrNcsW&! ^FLOO%9:: ;q>> '22 33r$c:tjtd|S)Nexp)r rPrr,s r"rPrPk &ua00 11r$c:tjtd|S)Nlog)r rSrr,s r"rSrSprQr$c:tjtd|S)Nexpm1)r rUrr,s r"rUrUu (!44 55r$c:tjtd|S)Nlog1p)r rXrr,s r"rXrXzrVr$c:tjtd|S)Nsin)r rZrr,s r"rZrZrQr$c:tjtd|S)Ncos)r r\rr,s r"r\r\rQr$c:tjtd|S)Ntan)r r^rr,s r"r^r^rQr$c:tjtd|S)Narcsin)r asinrr,s r"r`r` '!44 55r$c:tjtd|S)Narccos)r acosrr,s r"rdrdrbr$c:tjtd|S)Narctan)r atanrr,s r"rgrgrbr$c:tjtd|S)Nsinh)r rjrr,s r"rjrj '22 33r$c:tjtd|S)Ncosh)r rmrr,s r"rmrmrkr$c:tjtd|S)Narcsinh)r asinhrr,s r"roro (A66 77r$ctjtd|}tj|jt jr4tt|dktj ||}|S)Narccoshr) r acoshrr issubdtyperrcomplexfloatingrr*rB)r results r"rsrss^ 9*9a88 9& v|R%788? DLL1$cgfoov > >F -r$c:tjtd|S)Ntanh)r ryrr,s r"ryryrkr$c:tjtd|S)Narctanh)r atanhrr,s r"r{r{rqr$c:tjtd|S)Nsqrt)r r~rr,s r"r~r~rkr$c:tjtd|S)Ncbrt)r rrr,s r"rrrkr$yctd||\}}|jtkrtj||ntj||S)Nadd)rrr/r r bitwise_orr rs r"rrsC eQ " "$!Q'T//As~a/C/CCr$ctd||\}}|jtkrtj||ntj||S)Nmultiply)rrr/r mul bitwise_andrs r"rrsC j!Q ' '$!Q'T//Asq!/D/DDr$c<tjtd||S)Nr)r rrrs r"rr ,}a;; <>> x1 = jnp.array([64, 32, 31, 20]) >>> # 64 = 0b1000000, 32 = 0b100000, 31 = 0b11111, 20 = 0b10100 >>> jnp.bitwise_count(x1) Array([1, 1, 5, 2], dtype=uint8) >>> x2 = jnp.array([-16, -7, 7]) >>> # |-16| = 0b10000, |-7| = 0b111, 7 = 0b111 >>> jnp.bitwise_count(x2) Array([1, 3, 3], dtype=uint8) >>> x3 = jnp.array([[2, -7],[-9, 7]]) >>> # 2 = 0b10, |-7| = 0b111, |-9| = 0b1001, 7 = 0b111 >>> jnp.bitwise_count(x3) Array([[1, 3], [2, 3]], dtype=uint8) bitwise_countuint8)rr population_countr8astyper,s r"rrms:>OQ//"! c!ff % % , ,W 5 55r$x1x2cttjj||\}}tj|jtjr tjn tj }|||S)aRRight shift the bits of ``x1`` to the amount specified in ``x2``. LAX-backend implementation of :func:`numpy.right_shift`. Args: x1: Input array, only accepts unsigned integer subtypes x2: The amount of bits to shift each element in ``x1`` to the right, only accepts integer subtypes Returns: An array-like object containing the right shifted elements of ``x1`` by the amount specified in ``x2``, with the same shape as the broadcasted shape of ``x1`` and ``x2``. Note: If ``x1.shape != x2.shape``, they must be compatible for broadcasting to a shared shape, this shared shape will also be the shape of the output. Right shifting a scalar x1 by scalar x2 is equivalent to ``x1 // 2**x2``. Examples: >>> def print_binary(x): ... return [bin(int(val)) for val in x] >>> x1 = jnp.array([1, 2, 4, 8]) >>> print_binary(x1) ['0b1', '0b10', '0b100', '0b1000'] >>> x2 = 1 >>> result = jnp.right_shift(x1, x2) >>> result Array([0, 1, 2, 4], dtype=int32) >>> print_binary(result) ['0b0', '0b1', '0b10', '0b100'] >>> x1 = 16 >>> print_binary([x1]) ['0b10000'] >>> x2 = jnp.array([1, 2, 3, 4]) >>> result = jnp.right_shift(x1, x2) >>> result Array([8, 4, 2, 1], dtype=int32) >>> print_binary(result) ['0b1000', '0b100', '0b10', '0b1'] ) rr right_shift__name__rurunsignedintegerr shift_right_logicalshift_right_arithmeticrrlax_fns r"rrs\Z  7R @ @&"bM"(B.// P3 " "585O Br$bitwise_right_shiftctd||\}}tj|jtjr t jn t j}|||S)Nr)rrrurrr rrrs r"rrsW 5r2 > >&"bM"(B.// P3 " "585O Br$ctd|tj|}|tjkstj|tjrtj|ntj |S)aCalculate the absolute value element-wise. LAX-backend implementation of :func:`numpy.absolute`. This is the same function as :func:`jax.numpy.abs`. Args: x: Input array Returns: An array-like object containing the absolute value of each element in ``x``, with the same shape as ``x``. For complex valued input, :math:`a + ib`, the absolute value is :math:`\sqrt{a^2+b^2}`. Examples: >>> x1 = jnp.array([5, -2, 0, 12]) >>> jnp.absolute(x1) Array([ 5, 2, 0, 12], dtype=int32) >>> x2 = jnp.array([[ 8, -3, 1],[ 0, 9, -6]]) >>> jnp.absolute(x2) Array([[8, 3, 1], [0, 9, 6]], dtype=int32) >>> x3 = jnp.array([8 + 15j, 3 - 4j, -5 + 0j]) >>> jnp.absolute(x3) Array([17., 5., 5.], dtype=float32) absolute) rrrrbool_rurr rEr8)r dts r"rrs^<*a    |A">>V->r2CU-V-V>Q\_\cde\f\ffr$c t|S)z$Alias of :func:`jax.numpy.absolute`.)rr,s r"r8r8s !r$ctd|tj|}|tkstj|t jrtj|tj Stj|t j rStj ttj |ttj|Stj|tjjS)aRounds the elements of x to the nearest integer LAX-backend implementation of :func:`numpy.rint`. Args: x: Input array Returns: An array-like object containing the rounded elements of ``x``. Always promotes to inexact. Note: If an element of x is exactly half way, e.g. ``0.5`` or ``1.5``, rint will round to the nearest even integer. Example: >>> x1 = jnp.array([5, 4, 7]) >>> jnp.rint(x1) Array([5., 4., 7.], dtype=float32) >>> x2 = jnp.array([-2.5, -1.5, -0.5, 0.5, 1.5, 2.5, 3.5, 4.5]) >>> jnp.rint(x2) Array([-2., -2., -0., 0., 2., 2., 4., 4.], dtype=float32) >>> x3 = jnp.array([-2.5+3.5j, 4.5-0.5j]) >>> jnp.rint(x3) Array([-2.+4.j, 4.-0.j], dtype=complex64) rint)rrrr/rurintegerr convert_element_typefloat_rvcomplexrr*rroundRoundingMethodTO_NEAREST_EVENr rs r"rrs<&! ,q//% d]]f'rz::]  #Av} 5 55 ub011= ;tCHQKK(($sx{{*;*; < << 1c(8 9 99r$c`td||\}}tjtj|tjrt dtt| ttj | tj |S)aCopies the sign of each element in ``x2`` to the corresponding element in ``x1``. LAX-backend implementation of :func:`numpy.copysign`. Args: x1: Input array x2: The array whose elements will be used to determine the sign, must be broadcast-compatible with ``x1`` Returns: An array object containing the potentially changed elements of ``x1``, always promotes to inexact dtype, and has a shape of ``jnp.broadcast_shapes(x1.shape, x2.shape)`` Examples: >>> x1 = jnp.array([5, 2, 0]) >>> x2 = -1 >>> jnp.copysign(x1, x2) Array([-5., -2., -0.], dtype=float32) >>> x1 = jnp.array([6, 8, 0]) >>> x2 = 2 >>> jnp.copysign(x1, x2) Array([6., 8., 0.], dtype=float32) >>> x1 = jnp.array([2, -3]) >>> x2 = jnp.array([[1],[-4], [5]]) >>> jnp.copysign(x1, x2) Array([[ 2., 3.], [-2., -3.], [ 2., 3.]], dtype=float32) copysignz/copysign does not support complex-valued inputs) rrrurrrv TypeErrorrsignbitrr/r r8rrs r"rrsB B 3 3&"b v|B'');<<G E F FF  ""4((372;;, D DDr$cTtd||\}}tj||S)N true_divide)rr divrs r"rrBs) r2 6 6&"b Rr$cptd||\}}tj|}tj|tjrt j||Stj|tjrxt j||}tt j |t j |kt j ||dk}t||dz |Stj|tj rtdt||dS)aACalculates the floor division of x1 by x2 element-wise LAX-backend implementation of :func:`numpy.floor_divide`. Args: x1: Input array, the dividend x2: Input array, the divisor Returns: An array-like object containing each of the quotients rounded down to the nearest integer towards negative infinity. This is equivalent to ``x1 // x2`` in Python. Examples: >>> x1 = jnp.array([10, 20, 30]) >>> x2 = jnp.array([3, 4, 7]) >>> jnp.floor_divide(x1, x2) Array([3, 5, 4], dtype=int32) >>> x1 = jnp.array([-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]) >>> x2 = 3 >>> jnp.floor_divide(x1, x2) Array([-2, -2, -1, -1, -1, 0, 0, 0, 1, 1, 1], dtype=int32) >>> x1 = jnp.array([6, 6, 6], dtype=jnp.int32) >>> x2 = jnp.array([2.0, 2.5, 3.0], dtype=jnp.float32) >>> jnp.floor_divide(x1, x2) Array([3., 2., 2.], dtype=float32) Note: ``x1 // x2`` is equivalent to ``jnp.floor_divide(x1, x2)`` for arrays ``x1`` and ``x2`` See Also: :func:`jnp.divide` and :func:`jnp.true_divide` for floating point division floor_dividerz3floor_divide does not support complex-valued inputs)rrrrurrr rrrrGremrrvr _float_divmod)rrrquotientr(s r"rrKsJ B 7 7&"b ,r  % ub011 $ 72r??  ++$wr2H ""5swr2!7K L LF &(Q, 1 11  233$ I J JJ R  ##r$tuple[Array, Array]ctd||\}}tjtj|tjr t ||t||fSt||S)aCalculates the integer quotient and remainder of x1 by x2 element-wise LAX-backend implementation of :func:`numpy.divmod`. Args: x1: Input array, the dividend x2: Input array, the divisor Returns: A tuple of arrays ``(x1 // x2, x1 % x2)``. Examples: >>> x1 = jnp.array([10, 20, 30]) >>> x2 = jnp.array([3, 4, 7]) >>> jnp.divmod(x1, x2) (Array([3, 5, 4], dtype=int32), Array([1, 0, 2], dtype=int32)) >>> x1 = jnp.array([-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]) >>> x2 = 3 >>> jnp.divmod(x1, x2) (Array([-2, -2, -1, -1, -1, 0, 0, 0, 1, 1, 1], dtype=int32), Array([1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2], dtype=int32)) >>> x1 = jnp.array([6, 6, 6], dtype=jnp.int32) >>> x2 = jnp.array([1.9, 2.5, 3.1], dtype=jnp.float32) >>> jnp.divmod(x1, x2) (Array([3., 2., 1.], dtype=float32), Array([0.30000007, 1. , 2.9 ], dtype=float32)) See Also: - :func:`jax.numpy.floor_divide`: floor division function - :func:`jax.numpy.remainder`: remainder function divmod) rrrurrrr remainderrrs r"rrsjF "b 1 1&"b v|B''44! B  2r!2!2 22 R  r$ctj||}tjtj|||}tj|dktj|tj|k}tj|||z|}tj||t|dz |}tj||fS)Nrr) r rrrrrGr(r#r)rrmodrinds r"rrs B# C  "%%# q#(2,,#(3--"?@@# 3b#&&# 3nS!444c::# 3 r$cTtd||td||ttj|tjrK t j|}t|\}tj ||S#t$rYnwxYwt||S)Npower) rr isinstancerget_aval ConcreteArrayoperatorindexrr integer_powr_powerrs r"rrs'2r"""7B###  b!!4#566%% >"  b #2 & &cb _R $ $$     d  BsB BBctd||\}}td||\}}tjtj|t js1tjtj|t jrAt jtj|j dksJt||Stj|tj|}}tj|t j r4tj|t jrtj ||Stj ||S)Nrr)rrrrurrrriinfobits _pow_int_intinexactr r)rrx1_x2_d1d2s r"r r s '2r * *&"b"'2r 2 2(#s  S))2:66"  S))2844" 8FL%% & & +r 1 1 1 1 S ! !! <  V\"--b" r2:&&6+$3J3J%K%K L LE '$ #'%..11 2 2C ;sx}}mCHSMM25&I&I J JJr$cZt||}t|d|z}t|d}tjtj|||}tjtj||tj|||}tj||S)zWraps `x` between `[-a, a]`.r r)r#r rrr(rr)r _aatwo_arrs r"r#r# sQ! AF # #% 1  $ 1 u%%# 36#t$$cgc5&9&93??# ar$c|\}}|\}}td||||\}}}}t||}tjtj|t tjt|t|tj|t tjt|t|}||fS)N logaddexp_jvp)rrr rrrPrr-primalstangentsrrt1t2 primal_out tangent_outs r"_logaddexp_jvpr6s &"b &"b'RRHH."b"bR  *C R0@0@,zBZBZ([([$\$\]]C R0@0@,zBZBZ([([$\$\]]__+ [  r$cztd||\}}tj||}tj|jt jrtj||}tj tj |tj ||tj |tj tj ttjtj|t#|t jdStjtj ||tj|t#|d}tj |tj tj t|t#|t jd}tjtj|t-tj|t jt jdz S)N logaddexp2r )rr rrrurrr!rr(r"rrrXexp2rBr8r#rSrrr*r#rr$r%s r"r8r8 s b" 5 5&"b R$ rx-- W GBOOE :cj''gb"oogdCGCId37375>>;R;R6S6S,T,T,:2rvayy,I,I%K%KLL M MM GCGBOOSWT>$3J3J%K%K L LE '$ $u++ 6 6r26RS998U8UVV W WC ;sx}}mCHSMM2526RS99CT&U&U V VVr$c|\}}|\}}td||||\}}}}t||}tjtj|t tjt|t|tj|t tjt|t|}||fS)Nlogaddexp2_jvp)rr8r rrr9rr-r/s r"_logaddexp2_jvpr<2s &"b &"b'(8"b"bII."b"b"b!!*Db1A1A>> x1 = jnp.array([0.25, 0.5, 1, 2, 4, 8]) >>> jnp.log2(x1) Array([-2., -1., 0., 1., 2., 3.], dtype=float32) log2r rr rrSr#r,s r"r>r>=sC$FA&&"! SW^Aq%9%9:: ; ;;r$c td|\}tjtj|tjt |dS)aCalculates the base-10 logarithm of x element-wise LAX-backend implementation of :func:`numpy.log10`. Args: x: Input array Returns: An array containing the base-10 logarithm of each element in ``x``, promotes to inexact dtype. Examples: >>> x1 = jnp.array([0.01, 0.1, 1, 10, 100, 1000]) >>> with jnp.printoptions(precision=2, suppress=True): ... print(jnp.log10(x1)) [-2. -1. 0. 1. 2. 3.] log10 r?r,s r"rArASsC&GQ''"! SW^Ar%:%:;; < < @ @@ e  $ Yk!! C E EE  #( q(++! !! DJ(>"? J JJr$c tjtj|}t|j}t j||jk}t||t|d|j zz|}t|||j |d}t j |||fS)Nrr) rrGrrHrr r8tinyrr1rLrJ)r rMrNcondrrs r"_normalize_floatrRs fl1oo & &$  #( di $ dA 1a4:o666::" dHHdj[))88A;;77" !"h / / 33r$ctd||tj|}tj|}tj|tjstj|tjrtd||ftd||\}}tj tj |}tj |}t|j }tj||}tj||}d|jzdz }d|jz }t%|\} } || | |jz |zz|z z }t)|||jz } t+||} tj| d|} t)|| dz}t/|||jz|}t/|| d|jzz | } tj|tj}| ||jzz} | tj|||z|jzz} tj| |tj| |z} t/| tj| d|| } t/| tj|tj| tjz| } t/t9|t;|z|dkz|| S)Nldexpz$ldexp not supported for input types rrr)rrrrurrvrrFrcanonicalize_dtypeto_inexact_dtyperGrHrr rrKminexprRrLrrrErint32rJrGinfisinfisnan)rrx1_dtypex2_dtyperrMrNmaskbiasr eunderflow_cond overflow_condmrQs r"rTrTs'2r""" \"  ( \"  ( ""455T  8RZ 0 0T RXx>, a2 + +B &vr266 77r$cntd|t|\}tj|dS)Nsquarer )rrr r r,s r"roros5(Aa  "! A  r$ctd|\}tj|t|tjdz S)Ndeg2radrr rr1rr$r,s r"rqrqs7Iq))"! Jq"%#+.. / //r$ctd|\}tj|t|dtjz S)Nrad2degrrrsr,s r"rurus7Iq))"! Jq#+.. / //r$ctd|tj|rtj|ntj|S)N conjugate)rr iscomplexobjr conjrEr,s r"rwrw s=+q!!!** >! A>r$valctd|tj|rtj|ntj|dS)Nrr)rrrxr rrErzs r"rrsA&#/#.. I#CM#q4I4IIr$ctd|tj|rtj|ntj|S)Nr*)rrrxr r*rEr|s r"r*r*s?&#/#.. 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