`iPtddlZddlZddlmZddlmZddlmZddlm Z dZ dZ dZ d Z dd Zd ZddZdS)N)runtime)internal)device)_utilc ddlm}ddlm}|j}|d}||dd||}|jd}t j||ftj }t j|ftj }|d z||zk} | rtj } |} || z|j z} |j j} | | |zz}t j| || t j}|tjkr|j}nJ|tjkr|j}n2|tjkr|j}n|tjkr|j}nJ|| ||j j| |j j|j j|ntj} |tjkr|j}|j}n_|tjkr|j}|j}n@|tjkr|j}|j}n!|tjkr|j }|j!}nJtE|D]u}||j j}|| ||||}t j||}|| |||||j j||j j||j jv||||d d||d dfS) aCompute pivoted LU decomposition. Decompose a given batch of square matrices. Inputs and outputs are transposed. Args: a_t (cupy.ndarray): The input matrix with dimension ``(..., N, N)``. The dimension condition is not checked. dtype (numpy.dtype): float32, float64, complex64, or complex128. Returns: tuple: lu_t (cupy.ndarray): ``L`` without its unit diagonal and ``U`` with dimension ``(..., N, N)``. piv (cupy.ndarray): 1-origin pivot indices with dimension ``(..., N)``. dev_info (cupy.ndarray): ``getrf`` info with dimension ``(...)``. .. seealso:: :func:`scipy.linalg.lu_factor` rcublascusolverC)orderdtypeiFN)#cupy_backends.cuda.libsr r shapeastypereshapecupyemptynumpyint32rget_cublas_handleitemsizedataptrarangeuintpfloat32 sgetrfBatchedfloat64 dgetrfBatched complex64 cgetrfBatched complex128 zgetrfBatchedget_cusolver_handlesgetrf_bufferSizesgetrfdgetrf_bufferSizedgetrfcgetrf_bufferSizecgetrfzgetrf_bufferSizezgetrfrange)a_trr r orig_shapen batch_sizeipivdev_info use_batchedhandleldastepstartstopa_array getrfBatchedgetrf_bufferSizegetrfia_ptr buffersize workspaces n/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/cupy/linalg/_decomposition.py _lu_factorrG s2/.....000000J2A **U#* & & . .r1a 8 8C1J :z1oU[ 9 9 9Dz:-u{;;;Hu$A-K.8)++3w% tj((+eT4tzBBB EM ! !!/LL em # #!/LL eo % %!/LL e& & &!/LL 5 Aw|'dim M z + + + + +-- EM ! !'9 OEE em # #'9 OEE eo % %'9 OEE e& & &'9 OEE 5z"" 8 8AFKOE))&!QqAAJ :U;;;I E1eQ (:Q  (1+"2"6 8 8 8 8 J Z_%%CRC)) c ddlm}ddlm}ddlm}|dst dt j|\}}|jdkrtj |j |S|dkr|j }n#|dkr|j }n|d kr|j}n|j}||d d }tj|}|j d } |jd|jjz} t-j} t1j|j dd} tj | t4j} || |j| |jj| | jj| tjj || tj!||dS)aBatched Cholesky decomposition. Decompose a given array of two-dimensional square matrices into ``L * L.T``, where ``L`` is a lower-triangular matrix and ``.T`` is a conjugate transpose operator. Args: a (cupy.ndarray): The input array of matrices with dimension ``(..., N, N)`` Returns: cupy.ndarray: The lower-triangular matrix. rrr )check_availability potrfBatchedzpotrfBatched is not availablefdFr Trcopyrr NrFrP)"rr r cupyx.cusolverrJ RuntimeErrorrlinalg_common_typesizerrr spotrfBatched dpotrfBatched cpotrfBatched zpotrfBatchedr_core _mat_ptrsstridesrrrr(rprodrrCUBLAS_FILL_MODE_UPPERrrlinalg3_check_cusolver_dev_info_if_synchronization_allowedtril)ar r rJr out_dtyperKxxpr4ldxr9r5r7s rF_potrf_batchedrgjs/.....000000111111  n - -<:;;;/22E9v{{z!'9--- ||- #- #- -  c--A   a B  A )B-17+ +C  ' ) )Fqwss|,,Jz*EK888HL-q"'+s :''' KIIh    9Q<<  yu  5 55rHc ddlm}ddlm}tj|tj|tj||jdkrt|Stj |\}}|j dkrtj |j |S||dd}t|}t!j}tj dt$j }|d kr|j} |j} n8|d kr|j} |j} n#|d kr|j} |j} n|j} |j} | ||j||jj|} tj | | } | ||j||jj|| jj| |jjtjj | |tj!|d ||dS)a6Cholesky decomposition. Decompose a given two-dimensional square matrix into ``L * L.H``, where ``L`` is a lower-triangular matrix and ``.H`` is a conjugate transpose operator. Args: a (cupy.ndarray): Hermitian (symmetric if all elements are real), positive-definite input matrix with dimension ``(..., M, M)``. Returns: cupy.ndarray: The lower-triangular matrix of shape ``(..., M, M)``. .. warning:: This function calls one or more cuSOLVER routine(s) which may yield invalid results if input conditions are not met. To detect these invalid results, you can set the `linalg` configuration to a value that is not `ignore` in :func:`cupyx.errstate` or :func:`cupyx.seterr`. .. seealso:: :func:`numpy.linalg.cholesky` rrr r TrOrrLrMrN)kFrQ)"rr r r_assert_cupy_array_assert_stacked_2d_assert_stacked_squarendimrgrTrUrrrrlenrr(rrspotrfspotrf_bufferSizedpotrfdpotrf_bufferSizecpotrfcpotrf_bufferSizezpotrfzpotrf_bufferSizer^rrr_r`_tril) rbr r rrcrdr4r9r7potrfpotrf_bufferSizerDrEs rFcholeskyr|s./.....000000 Q Q  ###vzza   /22E9v{{z!'9--- c--A AA  ' ) )Fz!5;///H ||#5 ##5 ##5#5!!-q!&*aAAJ :U333I E-q!&*aJ (9;;; KII x KQ 88IE8 * **rHcddlm}|jdd}tj|}|jdd\}}t ||}|dks|dkrt j|\}} |dkr4tj |||fz| tj |||fz| fS|dkr2t j ||| } | tj |||fz| fS|dkrtj |||fz| S|dkr3tj |||fz| tj ||fz| fS|j dg|jddR}|||} |dkr%| || jddzS| \} } | || jddz} |dkrdnd} | || j| dz} | | fS) Nr)_geqrf_orgqr_batchedr reducedcompleterrawr) rRr~rrr]minrrTrrstacked_identityr)rbmoder~ batch_shaper5mr4rkrrcqoutridxs rF _qr_batchedrs)333333'#2#,K{++J 7233> > U]]J{aV3Y??J{aT19==? ?  "& &&&A  q$ ' 'C s{{{{;2337888 DAq + ,--A ""2C + -..A q6MrHrc " ddlm}tj||dvr>|dvrd|}nd|}t ||jdkrt||Stj|\}}|j \}}t||}|dkr|dkr.tj |df|tj d|f|fS|d kr,tj ||tj ||f|fS|d krtj d|f|Stj ||f|tj d |fS||d d } t!j} tj dt$j} |dkr|j} |j} nh|dkr|j} |j} nS|dkr|j} |j} n>|dkr|j} |j} n)d|j}t || | ||| jj|}tj ||}tj ||}| | ||| jj||jj|jj|| jj tjj | | |d krI| ddd|f}tj!||dS|dkr.| |d||dfS|d kr ||kr|}tj ||f|}n|}tj ||f|}| |d|<|dkr|j"}|j#}n>|dkr|j$}|j%}n)|dkr|j&}|j'}n|dkr|j(}|j)}|| ||||jj||jj}tj ||}|| ||||jj||jj|jj|| jj tjj || |d|}| ddd|f}||dtj!||dfS)aQR decomposition. Decompose a given two-dimensional matrix into ``Q * R``, where ``Q`` is an orthonormal and ``R`` is an upper-triangular matrix. Args: a (cupy.ndarray): The input matrix. mode (str): The mode of decomposition. Currently 'reduced', 'complete', 'r', and 'raw' modes are supported. The default mode is 'reduced', in which matrix ``A = (..., M, N)`` is decomposed into ``Q``, ``R`` with dimensions ``(..., M, K)``, ``(..., K, N)``, where ``K = min(M, N)``. Returns: cupy.ndarray, or tuple of ndarray: Although the type of returned object depends on the mode, it returns a tuple of ``(Q, R)`` by default. For details, please see the document of :func:`numpy.linalg.qr`. .. warning:: This function calls one or more cuSOLVER routine(s) which may yield invalid results if input conditions are not met. To detect these invalid results, you can set the `linalg` configuration to a value that is not `ignore` in :func:`cupyx.errstate` or :func:`cupyx.seterr`. .. seealso:: :func:`numpy.linalg.qr` rr )rrrr)rLfulleeconomicz)The deprecated mode '{}' is not supportedzUnrecognized mode '{}'rirrrrr TrOrjrrLrMrNDzDdtype must be float32, float64, complex64 or complex128 (actual: {})NFrQr)*rr rrlformat ValueErrorrorrTrrrridentity transposerrr(rrsgeqrf_bufferSizesgeqrfdgeqrf_bufferSizedgeqrfcgeqrf_bufferSizecgeqrfzgeqrf_bufferSizezgeqrfrrrr_r`_triusorgqr_bufferSizesorgqrdorgqr_bufferSizedorgqrcungqr_bufferSizecungqrzungqr_bufferSizezungqr)rbrr msgrrcrr4rkrdr9r7geqrf_bufferSizegeqrfrDrEtaurmcrorgqr_bufferSizeorgqrs rFqrrsK:100000 Q 666 1 1 1?FFtLLCC,33D99Coovzz1d###/22E9 7DAq Aq AAvv 9  :q!fi00$*aVY2O2OO O Z  =I.. Aq690M0MM M S[[:q!fi00 0:q!fi00$*T92M2MM M U#D99A  ' ) )Fz!5;///H ||#5 ##5 ##5 ##5%vag oo"!&!Q A>>J :U333I *Qe $ $ $C E&!Q A (, *J 8IKKKKII x s{{ aaa!eH   {1~~$$YU$;;; u}} HHYUH + + JJyuJ - -/ / za!ee  J1vu % %  J1vu % % AbqbE ||#5 ##5 ##5 ##5!!2q!&*a77J :U333I E2q!&*ay~7IHM%''' KII x #2#A !!!SbS& A '' Aie44 66rHc0ddlm}m}|jdd}t j|}|jdd\}}t j|\} } | j } |dkrt||} tj || fz| } |rt|r7tj |||fz| }tj |||fz| }n6tj ||| fz| }tj || |fz| }|| |fS| S|dks|dkrtj |dz| } |rj|r-t j ||| }t j ||| }n6tj ||dfz| }tj |d|fz| }|| |fS| S|jdg|jddR}tjs |dkr-|dkr'|| dd }||||d }n||| j||d }|r|\}} }|| d }|jg||jddR}| | d } | jg|| jddR} || d }|jg||jddR}|| |ddfS|} | | d } | jg|| jddR} | S) Nr)_gesvdj_batched_gesvd_batchedr rrr r FrOrQ)rRrrrrr]rrTcharlowerrrrrrris_hiprswapaxesconj)rb full_matrices compute_uvrrrr5r4rruv_dtypes_dtyperksuvtrvs rF _svd_batchedrs>>>>>>>>'#2#,K{++J 7233 2`` and the matrix dimensions <= 32, a fast code path based on Jacobian method (``gesvdj``) is taken. Otherwise, a QR method (``gesvd``) is used. On ROCm, there is no such a fast code path that switches the underlying algorithm. .. seealso:: :func:`numpy.linalg.svd` rr rirrr TrOFNAOS)rrNrjrLrMrNrQ)#rr rrlrorrTrrrrreyerrordrrrr(rrsgesvdsgesvd_bufferSizedgesvddgesvd_bufferSizecgesvdcgesvd_bufferSizezgesvdzgesvd_bufferSizerrrr_r`)rbrrr rr real_dtyperr4rrrrrd trans_flagrkjob_ujob_vtu_ptrvt_ptrr9r7gesvdgesvd_bufferSizerDrE rwork_ptrrworks rFsvdrs1H100000 QvzzA}j999.q11OE8!!##Jm!!##G 7DAqAvva JtW % %   8HQh///Xax000J1vX666ZAh777a8OH Avv HHU#DH 1 1 w1 KKMM c = =  A   Aq6///A111bqb5BHHEXXFFAQF%000BHHEXXF BGKv vCS 1J'''A  ' ) )Fz!5;///H ||#5 ##5 ##5#5!!&!Q//J :U333I >#  3q!99Q;g666JN  Evq!QVZAFJq9>%z9  KII x u%%A HHXEH * * YYxeY , ,  ;;==!R\\^^3 3q!8OrH)r)TT)rrcupy_backends.cuda.apir cupy._corer cupy.cudar cupy.linalgrrGrgr|rrrrrHrFrs ******]]]@060606fA+A+A+H###LC6C6C6C6L>>>DFFFFFFrH