o X۷i0@sddlmZddlZddlZddlZddlZddlmZddZddZ edd Z ed d Z ed d Z ddZ ddZddZdddZddZddZdS)) annotationsN) RankWarningcs"ddfdd}t|S)NcSsZt|tjr |jSt|rt|St|tjr)t|}|jdkr%|Stdt d)Nz)Multidimensional inputs are not supportedzUnsupported type) isinstancecupypoly1d_coeffsisscalar atleast_1dndarrayndim ValueError TypeErrorxrM/home/ubuntu/vllm_env/lib/python3.10/site-packages/cupy/lib/_routines_poly.py _get_coeffs s      z'_wraps_polyroutine.._get_coeffscsffdd|D}|}tdd|Dr|St|tjr#t|St|tr1tdd|DSJ)Ncsg|]}|qSrr.0r)rrr sz7_wraps_polyroutine..wrapper..css|] }t|tj VqdS)N)rrrrrrr sz6_wraps_polyroutine..wrapper..cSsg|]}t|qSr)rrrrrrr"s)allrrr rtuple)argscoeffsoutrfuncrrwrappers   z#_wraps_polyroutine..wrapper) functoolsupdate_wrapper)rrrrr_wraps_polyroutine s r"cCs8|}|jdkr,|jd|jdkr,|jddkr,t||jr(tj|}ntd|jdkr>|j t |j j dd}nt d|jdkrIdSd|jd}t|df|j }|d d dfdtj||d |jdfd |dkr|d}tjj|d |||d d }|dksx|dd |jdfS) aComputes the coefficients of a polynomial with the given roots sequence. Args: seq_of_zeros (cupy.ndarray): a sequence of polynomial roots. Returns: cupy.ndarray: polynomial coefficients from highest to lowest degree. .. warning:: This function doesn't support general 2d square arrays currently. Only complex Hermitian and real symmetric 2d arrays are allowed. .. seealso:: :func:`numpy.poly` rrKOnly complex Hermitian and real symmetric 2d arrays are supported currentlyFcopyz.Input must be 1d or non-empty square 2d array.g?N)rfull)r shaper array_equalconjTlinalgeigvalshNotImplementedErrorastype mintypecodedtypecharr size bit_lengthzerosfillnegative_mathmisc _fft_convolve) seq_of_zerosrr3arrrpoly(s&,  "r=cCsP|j|jkr ||}}t||j|jdf}|jt||dd}||7}|S)a<Computes the sum of two polynomials. Args: a1 (scalar, cupy.ndarray or cupy.poly1d): first input polynomial. a2 (scalar, cupy.ndarray or cupy.poly1d): second input polynomial. Returns: cupy.ndarray or cupy.poly1d: The sum of the inputs. .. seealso:: :func:`numpy.polyadd` rFr%)r3rpadr/ result_typea1a2rrrrpolyaddSs  rCcCs|jd|jdkr+t||jd|jddf}|jt||dd}||8}|St||jd|jddf}|jt||dd}|d||8}|S)aJComputes the difference of two polynomials. Args: a1 (scalar, cupy.ndarray or cupy.poly1d): first input polynomial. a2 (scalar, cupy.ndarray or cupy.poly1d): second input polynomial. Returns: cupy.ndarray or cupy.poly1d: The difference of the inputs. .. seealso:: :func:`numpy.polysub` rFr%r#)r(rr>r/r?r@rrrpolysubis  rDcCs\tj|dd}tj|dd}|jdkrtdg|j}|jdkr(tdg|j}t||S)aDComputes the product of two polynomials. Args: a1 (scalar, cupy.ndarray or cupy.poly1d): first input polynomial. a2 (scalar, cupy.ndarray or cupy.poly1d): second input polynomial. Returns: cupy.ndarray or cupy.poly1d: The product of the inputs. .. seealso:: :func:`numpy.polymul` f)trimrg)r trim_zerosr3arrayr1convolve)rArBrrrpolymuls   rJcCs\|dkrdS|dkr |S|ddkrtt|||dSt|tt|||ddS)Nrrr#)_polypowrrI)rnrrr_polypow_directs "rMc Cs|dkrdS|dkr |Stjj||d}|dkrt||S|dkrf|jjdkr2tjjtjj}}n tjj tjj }}|j d|d}ddl }|j j|}|||}t|||} || |} | d|SJ)Nrrr'directfftc)rr8r9_choose_conv_methodrMr1kindrOifftrfftirfftr3cupyx.scipy.fftscipy next_fast_lenpower) rrLmethodrOrSout_sizecupyxr3fxfyyrrrrKs&     rKcCs,|jjdkr|jtjddS|jtjddS)NrPFr%)r1rRr/numpy complex128float64rrrr_polyfit_typecasts rcFcCs|jjdkr|jjdkrtd|jtjkrtdt|}t|}t|}|dkr.t d|j dkr7td|j dkr@td |j dksJ|j d krNtd |j |j dkrZtd t jj||d d d d df}|}|d urt|}|j dkr~td|j |j krtd||d d d f9}|j d kr|d d d f}||9}|d ur|j t |jj}t t |jdd} || }t j|||\} } } } |j dkr| dd} | | } |d}| |kr|sd}tj|tdd|r| jjdkrt | } | | | | |fS|rEt jt |j|}|t | | }|dkr#d}n|j |kr1| |j |}nt d|j dkr?|d}| ||fS| S)aReturns the least squares fit of polynomial of degree deg to the data y sampled at x. Args: x (cupy.ndarray): x-coordinates of the sample points of shape (M,). y (cupy.ndarray): y-coordinates of the sample points of shape (M,) or (M, K). deg (int): degree of the fitting polynomial. rcond (float, optional): relative condition number of the fit. The default value is ``len(x) * eps``. full (bool, optional): indicator of the return value nature. When False (default), only the coefficients are returned. When True, diagnostic information is also returned. w (cupy.ndarray, optional): weights applied to the y-coordinates of the sample points of shape (M,). cov (bool or str, optional): if given, returns the coefficients along with the covariance matrix. Returns: cupy.ndarray or tuple: p (cupy.ndarray of shape (deg + 1,) or (deg + 1, K)): Polynomial coefficients from highest to lowest degree residuals, rank, singular_values, rcond (cupy.ndarray, int, cupy.ndarray, float): Present only if ``full=True``. Sum of squared residuals of the least-squares fit, rank of the scaled Vandermonde coefficient matrix, its singular values, and the specified value of ``rcond``. V (cupy.ndarray of shape (M, M) or (M, M, K)): Present only if ``full=False`` and ``cov=True``. The covariance matrix of the polynomial coefficient estimates. .. warning:: cupy.exceptions.RankWarning: The rank of the coefficient matrix in the least-squares fit is deficient. It is raised if ``full=False``. .. seealso:: :func:`numpy.polyfit` ebz0float16 x and bool y are not currently supportedzfloat16 y are not supportedrzexpected deg >= 0rzexpected 1D vector for xzexpected non-empty vector for xr#zexpected 1D or 2D array for yz$expected x and y to have same lengthNz expected a 1-d array for weightsz(expected w and y to have the same length)axisz!Polyfit may be poorly conditioned) stacklevelrPunscaledzJthe number of data points must exceed order to scale the covariance matrix.N) r1r2rRr.r`float16rrcintr r r3r(r polynomial polyvanderfinfoepssqrtsquaresumr,lstsqreshapewarningswarnrabsoluteinvdotr+outer)rr_degrcondr'wcovlhsrhsscalerPresidsranksordermsgbasefactorrrrpolyfitsr)   "            rcCsnt|tjr |j}t|tjr|jdkrtd|jdkr!tdt|tjrZt |jd}ttj dg|d}ttj dg|d}|dddD] }|||}||}qK|St|tjset |}t |j d|}|j|dd }|jdkrt|j|S|tjkr|||dSt|stj ||dd }|tj|j|d}|ddd|jd|d S) aEvaluates a polynomial at specific values. Args: p (cupy.ndarray or cupy.poly1d): input polynomial. x (scalar, cupy.ndarray): values at which the polynomial is evaluated. Returns: cupy.ndarray or cupy.poly1d: polynomial evaluated at x. .. warning:: This function doesn't currently support poly1d values to evaluate. .. seealso:: :func:`numpy.polyval` rz%p must be 1d ndarray or poly1d objectrzp must be 1d array)r1NrfFr%rk)rgr1)rrrrr r rr r`r?rHasarrayr1typer/r3r5r(bool_anyr arangert)prr1resprodrPrrrpolyval6s4          rcCst|tjr |j}|jjdkrtd|jdkrtd|j dkr&t gStj j |dddg\}|j dkr>t gS|j dkr]|d |dd}|ddkr[|jtj}|Stj j |}t||jrttj|}ntd ||jS) a!Computes the roots of a polynomial with given coefficients. Args: p (cupy.ndarray or cupy.poly1d): polynomial coefficients. Returns: cupy.ndarray: polynomial roots. .. warning:: This function doesn't support currently polynomial coefficients whose companion matrices are general 2d square arrays. Only those with complex Hermitian or real symmetric 2d arrays are allowed. The current `cupy.roots` doesn't guarantee the order of results. .. seealso:: :func:`numpy.roots` rez boolean inputs are not supportedrz"0-dimensional input is not allowedr#Nrfrr$)rrrrr1rRr.r rr3rHrn polyutils as_seriesrealr/r`rb polycompanionr)r*r+r,r-)rrcmatrixrrrrootses*          r)NFNF) __future__rr rwr`rcupy.exceptionsrr"r=rCrDrJrMrKrcrrrrrrrs(  +     s /