`iCddlZddlZddlmZddlmZddlmZ ddlmZej Z ej Z n'#e $rGdde Z Gdde Z YnwxYwGd d e Zd ZejZeZdS) N)_core)_util)_sputilsceZdZdS) SparseWarningN__name__ __module__ __qualname__l/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/cupyx/scipy/sparse/_base.pyrr r rceZdZdS)SparseEfficiencyWarningNrr r rrrrr rceZdZdZdZdTdZedZdUdZdZ d Z d Z d Z e Z d Zd ZdZdZdZdZdZdZdZdZdZdZdZdZdZdZdZdZdZ dZ!d Z"d!Z#d"Z$d#Z%d$Z&d%Z'ed&Z(ed'Z)ed(Z*ed)Z+ed*Z,ed+Z-ed,Z.e.j/d-Z.d.Z0d/Z1d0Z2dVd2Z3dVd3Z4e3je4_d4Z5d5Z6dWd7Z7d8Z8d9Z9d:Z:d;Z;d<ZZ>dXd?Z?d@Z@dAZAdUdBZBdCdDdEZCdFZDdWdGZEdXdHZFdYdIZGdZdKZHd[dLZId[dMZJd[dNZKdYdOZLd[dPZMd[dQZNd[dRZOdZdSZPdS)\spmatrixzOBase class of all sparse matrixes. See :class:`scipy.sparse.spmatrix` e2cR|jtkrtd||_dS)Nz7This class is not intended to be instantiated directly.) __class__r ValueErrormaxprint)selfrs r__init__zspmatrix.__init__!s2 >X % %IKK K  r ct)z(CUDA device on which this array resides.NotImplementedErrorrs rdevicezspmatrix.device's "!r Nct)a.Return a copy of the array on host memory. Args: stream (cupy.cuda.Stream): CUDA stream object. If it is given, the copy runs asynchronously. Otherwise, the copy is synchronous. Returns: scipy.sparse.spmatrix: An array on host memory. r)rstreams rgetz spmatrix.get,s "!r c td)Nz;sparse matrix length is ambiguous; use getnnz() or shape[0]) TypeErrorrs r__len__zspmatrix.__len__9s344 4r cDt|SN)strr#rs r__str__zspmatrix.__str__=s488::r c#`Kt|jdD]}||ddfVdSNr)rangeshape)rrs r__iter__zspmatrix.__iter__BsHtz!}%%  Aq!!!t*      r cL|jdkr |jdkStd)N)r2rz\The truth value of an array with more than one element is ambiguous. Use a.any() or a.all().)r.nnzrrs r__bool__zspmatrix.__bool__Fs6 :  8q= MNN Nr cP||Sr()tocsr__eq__rothers rr7zspmatrix.__eq__Ozz||""5)))r cP||Sr()r6__ne__r8s rr<zspmatrix.__ne__Rr:r cP||Sr()r6__lt__r8s rr>zspmatrix.__lt__Ur:r cP||Sr()r6__gt__r8s rr@zspmatrix.__gt__Xr:r cP||Sr()r6__le__r8s rrBzspmatrix.__le__[r:r cP||Sr()r6__ge__r8s rrDzspmatrix.__ge__^r:r cN|Sr()r6__abs__rs rrFzspmatrix.__abs__aszz||##%%%r cP||Sr()r6__add__r8s rrHzspmatrix.__add__dzz||##E***r cP||Sr()r6__radd__r8s rrKzspmatrix.__radd__gzz||$$U+++r cP||Sr()r6__sub__r8s rrNzspmatrix.__sub__jrIr cP||Sr()r6__rsub__r8s rrPzspmatrix.__rsub__mrLr cP||Sr()r6__mul__r8s rrRzspmatrix.__mul__prIr ctj|st|r|jdkr||zS |j}n#t $r t cYSwxYw|j|zjSr,)cupyisscalarisdensendimTAttributeErrorNotImplemented)rr9trs r__rmul__zspmatrix.__rmul__ssx =   #75>> #ejAoo%<  &W! & & &%%%% &FRK? "s=AAcrtj|rtd||SNz0Scalar operands are not allowed, use '*' instead)r isscalarlikerrRr8s r __matmul__zspmatrix.__matmul__~s>  e $ $ 2122 2||E"""r crtj|rtd||Sr^)rr_rr\r8s r __rmatmul__zspmatrix.__rmatmul__s>  e $ $ 2122 2}}U###r cP||Sr()r6__div__r8s rrdzspmatrix.__div__rIr cP||Sr()r6__rdiv__r8s rrfzspmatrix.__rdiv__rLr cP||Sr()r6 __truediv__r8s rrhzspmatrix.__truediv__szz||''...r cP||Sr()r6 __rtruediv__r8s rrjzspmatrix.__rtruediv__szz||((///r c,| Sr()r6rs r__neg__zspmatrix.__neg__s }r ctSr(rZr8s r__iadd__zspmatrix.__iadd__r ctSr(rnr8s r__isub__zspmatrix.__isub__rpr ctSr(rnr8s r__imul__zspmatrix.__imul__rpr c,||Sr() __itruediv__r8s r__idiv__zspmatrix.__idiv__s  '''r ctSr(rnr8s rrvzspmatrix.__itruediv__rpr c|j\}}||krtdtj|rt |}|dkrt d|dkr+ddl}|jj ||j dS|dkr| S| |dz}|dzr||z|zS||zStj |rt d tS) asCalculates n-th power of the matrix. This method calculates n-th power of a given matrix. The matrix must be a squared matrix, and a given exponent must be an integer. Args: other (int): Exponent. Returns: cupyx.scipy.sparse.spmatrix: A sparse matrix representing n-th power of this matrix. zmatrix is not squarerzexponent must be >= 0Ncsr)dtypeformatr2zexponent must be an integer)r.r%r isintlikeintrcupyx.scipy.sparsescipysparseidentityr{copy__pow__r_rZ)rr9mncupyxtmps rrzspmatrix.__pow__sz1 66233 3 ?5 ! ! "JJEqyy !8999zz)))){)22TZ3777!yy{{"ll5A:..19%#:++9$   & & ":;; ;! !r c*|S)zDense ndarray representation of this matrix. This property is equivalent to :meth:`~cupyx.scipy.sparse.spmatrix.toarray` method. toarrayrs rAz spmatrix.As||~~r c*|Sr() transposers rrXz spmatrix.T~~r c*|Sr()getHrs rHz spmatrix.Hsyy{{r cdS)Nr}r rs rrWz spmatrix.ndimsqr c*|Sr(getnnzrs rsizez spmatrix.size{{}}r c*|Sr(rrs rr3z spmatrix.nnzrr c*|Sr() get_shapers rr.zspmatrix.shaperr c0||dSr() set_shape)rvalues rr.zspmatrix.shapes ur cV| ||jkr|St|d|zS)zwReturn this matrix in a given sparse format. Args: format (str or None): Format you need. Nto)r|getattr)rr|s rasformatzspmatrix.asformats6 >Vt{22K/74//11 1r c|jjdkr|Stj|jd}||S)a&Upcasts matrix to a floating point format. When the matrix has floating point type, the method returns itself. Otherwise it makes a copy with floating point type and the same format. Returns: cupyx.scipy.sparse.spmatrix: A matrix with float type. f)r{kindnumpy promote_typesastype)rtyps rasfptypezspmatrix.asfptypes> :?c ! !K%dj#66C;;s## #r c|||jS)zCasts the array to given data type. Args: t: Type specifier. Returns: cupyx.scipy.sparse.spmatrix: A copy of the array with the given type and the same format. )r6rrr|)rts rrzspmatrix.astypes0zz||""1%%..t{;;;r Tc|jjdkr*||dS|r|S|S)aElement-wise complex conjugation. If the matrix is of non-complex data type and `copy` is False, this method does nothing and the data is not copied. Args: copy (bool): If True, the result is guaranteed to not share data with self. Returns: cupyx.scipy.sparse.spmatrix : The element-wise complex conjugate. crF)r{rr6conjrrrs rrz spmatrix.conjsS :?c ! !::4:((--5-99 9  99;; Kr c.||S)Nr)rrs r conjugatezspmatrix.conjugate3syydy###r c0||dS)zReturns a copy of this matrix. No data/indices will be shared between the returned value and current matrix. Tr)rrs rrz spmatrix.copy8s ~~d~...r ct)z)Number of non-zero entries, equivalent torrs r count_nonzerozspmatrix.count_nonzero@!!r rcR||S)aReturns the k-th diagonal of the matrix. Args: k (int, optional): Which diagonal to get, corresponding to elements a[i, i+k]. Default: 0 (the main diagonal). Returns: cupy.ndarray : The k-th diagonal. )k)r6diagonal)rrs rrzspmatrix.diagonalDs#zz||$$q$)))r c>tj|r||zS||zS)zOrdinary dot product)rrUr8s rdotz spmatrix.dotPs( >%  %< %< r cN|Sr()rrrs rrz spmatrix.getHWs~~$$&&&r ctr(rrs rrzspmatrix.get_shapeZs!!r c|jSr()r|rs r getformatzspmatrix.getformat_s {r c|jSr()rrs r getmaxprintzspmatrix.getmaxprintbs }r ct)z2Number of stored values, including explicit zeros.r)raxiss rrzspmatrix.getnnzerr cP||Sr()r6maximumr8s rrzspmatrix.maximumkrIr cZd}tj||jj}||j}||r tj}nt j|j}|r tjn|}||}|E|t j|jd|jdzz ||S|dkr|dz }|dkr)|d|jdz z d||S|d|jdz z d||S) a Compute the arithmetic mean along the specified axis. Returns the average of the matrix elements. The average is taken over all elements in the matrix by default, otherwise over the specified axis. `float64` intermediate and return values are used for integer inputs. Args: axis {-2, -1, 0, 1, None}: optional Axis along which the mean is computed. The default is to compute the mean of all elements in the matrix (i.e., `axis` = `None`). dtype (dtype): optional Type to use in computing the mean. For integer inputs, the default is `float64`; for floating point inputs, it is the same as the input dtype. out (cupy.ndarray): optional Alternative output matrix in which to place the result. It must have the same shape as the expected output, but the type of the output values will be cast if necessary. Returns: m (cupy.ndarray) : Output array of means .. seealso:: :meth:`scipy.sparse.spmatrix.mean` c~tj|tjptj|tjSr()rT issubdtypeintegerbool_r{s r _is_integralz#spmatrix.mean.._is_integrals.OE4<887OE4:66 8r Nrr2r{outr}g?)rr{r) r validateaxisr{typerTfloat64rarrayr.sum) rrr{rr res_dtypeintegral inter_dtype inter_selfs rmeanz spmatrix.meannsX< 8 8 8 d###JO < ++ = ) L  5)).I'/=dllI [[-- < 1  1 -"/"//9#.. / !88 AID 199# 1 "56;;iS<22 2# 1 "56;;iS<22 2r cP||Sr()r6minimumr8s rrzspmatrix.minimumrIr cP||S)z+Point-wise multiplication by another matrix)r6multiplyr8s rrzspmatrix.multiplyszz||$$U+++r cT|||S)Nr)r6power)rrr{s rrzspmatrix.powers#zz||!!!5!111r Corderctj||j}||jkr|S|||S)a5Gives a new shape to a sparse matrix without changing its data. Args: shape (tuple): The new shape should be compatible with the original shape. order: {'C', 'F'} (optional) Read the elements using this index order. 'C' means to read and write the elements using C-like index order. 'F' means to read and write the elements using Fortran-like index order. Default: C. Returns: cupyx.scipy.sparse.coo_matrix: sparse matrix r)r check_shaper.tocooreshape)rrr.s rrzspmatrix.reshapesK $UDJ77 DJ  Kzz||##E#777r c0||dSr()r)rr.s rrzspmatrix.set_shapes Ur ct)arSet diagonal or off-diagonal elements of the array. Args: values (cupy.ndarray): New values of the diagonal elements. Values may have any length. If the diagonal is longer than values, then the remaining diagonal entries will not be set. If values is longer than the diagonal, then the remaining values are ignored. If a scalar value is given, all of the diagonal is set to it. k (int, optional): Which diagonal to set, corresponding to elements a[i, i+k]. Default: 0 (the main diagonal). r)rvaluesrs rsetdiagzspmatrix.setdiags "!r ctj||j\}}|C|t j||j||S|dkr|dz }|dkrH|jt j||j d|}nB|t j||j |d}|6|j|jkrtdtj |||S|| |d S|S) a/Sums the matrix elements over a given axis. Args: axis (int or ``None``): Axis along which the sum is computed. If it is ``None``, it computes the sum of all the elements. Select from ``{None, 0, 1, -2, -1}``. dtype: The type of returned matrix. If it is not specified, type of the array is used. out (cupy.ndarray): Output matrix. Returns: cupy.ndarray: Summed array. .. seealso:: :meth:`scipy.sparse.spmatrix.sum` Nrrrr}r2zdimensions do not matchFr)rrr.rrTonesr{rrXrrrelementwise_copyr)rrr{rrrrets rrz spmatrix.sumsH$ d### z1 <88DIatz:::;;??@&& & !88 AID 199&**TYq ;;;<<DDQJJCC((49Qdj999::BB1aHHC ?yCI%% !:;;;  "3 , , ,J  ::e%:00 0Jr cT|||S)z5Return a dense ndarray representation of this matrix.rr)r6rrrrs rrzspmatrix.toarrays#zz||##%S#999r FcV||dS)z/Convert this matrix to Block Sparse Row format.rF)r6tobsr)r blocksizers rrzspmatrix.tobsr'zztz$$***666r cV||dS)z)Convert this matrix to COOrdinate format.rF)r6rrs rrzspmatrix.tocoorr cV||dS)z7Convert this matrix to Compressed Sparse Column format.rF)r6tocscrs rrzspmatrix.tocsc rr ct)z4Convert this matrix to Compressed Sparse Row format.rrs rr6zspmatrix.tocsr$rr c0|||S)z4Return a dense matrix representation of this matrix.rrrs rtodensezspmatrix.todense(s||%S|111r cV||dS)z.Convert this matrix to sparse DIAgonal format.rF)r6todiars rrzspmatrix.todia,rr cV||dS)z1Convert this matrix to Dictionary Of Keys format.rF)r6todokrs rrzspmatrix.todok0rr cV||dS)z*Convert this matrix to LInked List format.rF)r6tolilrs rrzspmatrix.tolil4rr cX|||dS)z-Reverses the dimensions of the sparse matrix.rF)axesr)r6r)rrrs rrzspmatrix.transpose8s)zztz$$..Du.EEEr )rr()T)r)NNN)NN)NF)F)Qr r r __doc____array_priority__rpropertyr r#r&r*r0r4 __nonzero__r7r<r>r@rBrDrFrHrKrNrPrRr\r`rbrdrfrhrjrlrorrrtrwrvrrrXrrWrr3r.setterrrrrrrrrrrrrrrrrrrrrrrrrrrrr6rrrrrr r rrrs !!!! ""X" " " " "444 NNNK******************&&&+++,,,+++,,,+++###### $$$ +++,,,///000(((&"&"&"PX  X XXXX  X  \\ 2 2 2$$$ < < <*$$$$ I///""" * * * *   '''""" """" +++@2@2@2@2D+++,,, 2222%(88888. " " " "----^::::777777777777""""2222777777777777FFFFFFr rc,t|tS)zChecks if a given matrix is a sparse matrix. Returns: bool: Returns if ``x`` is :class:`cupyx.scipy.sparse.spmatrix` that is a base class of all sparse matrix classes. ) isinstancer)xs rissparser =s a " ""r )rrTrrrr scipy.sparser_sparserr ImportErrorWarningobjectrr rV isspmatrixr r rrsM $$$$$$''''''  """""")M%=                -      bFbFbFbFbFvbFbFbFJ### -  s1!AA