`i7ddlZddlZddlmZddlZddlmZddlmZddlm Z ddlm Z ddl Z dZ ddZ d Zdd Zd Zd ZddZddZdS)N)linalg)internal)device)_decomposition)_utilcdddlm}ddlm}m}|jdkr%|jd|kr |||Stj||tj |tj ||j|jks|j|jdzkr(|jdd|jd|jdz kstdtj ||\}}|j dkrtj|j|S|jdkr]||d d }||d d }|||||d S||d d }tj||}|jdd}t't)j|D]V} t)j| |} || |d d } ||| | | || <W|S)a&Solves a linear matrix equation. It computes the exact solution of ``x`` in ``ax = b``, where ``a`` is a square and full rank matrix. Args: a (cupy.ndarray): The matrix with dimension ``(..., M, M)``. b (cupy.ndarray): The matrix with dimension ``(..., M)`` or ``(..., M, K)``. Returns: cupy.ndarray: The matrix with dimension ``(..., M)`` or ``(..., M, K)``. .. 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.solve` r)lapack) batched_gesvget_batched_gesv_limitNzEa must have (..., M, M) shape and b must have (..., M) or (..., M, K)TFcopyorderFrCdtype)cupyxr cupy.cublasr r ndimshaper_assert_cupy_array_assert_stacked_2d_assert_stacked_square ValueErrorlinalg_common_typesizecupyemptyastypegesv empty_likerangenumpyprod unravel_index) abr r r r out_dtypexriindexbis f/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/cupy/linalg/_solve.pysolver3sK0@@@@@@@@vzzagbk%;%;%=%===|Aq!!! Q""" Q  ### 16  QVqvz11 GCRCLAGKQVaZK0 0 0  /155E9v{{z!'9---v{{ HHUSH 1 1 HHUSH 1 1 Aqxx x... T--A +++A GCRCLE 5:e$$ % %#Au-- uX__US_ 9 9 AeHb!!!% Hc|ktt|j}|D]2}||||j|3||}|j|j|jz d}tj|}| d|}| }t||}| |S)aSolves tensor equations denoted by ``ax = b``. Suppose that ``b`` is equivalent to ``cupy.tensordot(a, x)``. This function computes tensor ``x`` from ``a`` and ``b``. Args: a (cupy.ndarray): The tensor with ``len(shape) >= 1`` b (cupy.ndarray): The tensor with ``len(shape) >= 1`` axes (tuple of ints): Axes in ``a`` to reorder to the right before inversion. Returns: cupy.ndarray: The tensor with shape ``Q`` such that ``b.shape + Q == a.shape``. .. 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.tensorsolve` Nr ) listr'rremoveinsert transposerrr)reshaperavelr3)r+r,axesallaxeskoldshaper)results r2 tensorsolverATs2 uQV}}%% & &A NN1    NN161 % % % % KK w!&)**+H = " "D "dA  A 1a[[F >>( # ##r4c|jj}tj|}tjtj||dS)Nr axis)rcharlowerr"ascontiguousarraysumsquareview)r. real_dtypes r2_nrm2_last_axisrL}sR##%%J q!!A 8DKz 2 233" = = ==r4warnc|dkrtjdtd}tj||tj||jdkr,tjd |j|j dd\}}|j d}||krtjd tj |d \}}}|0tj|jjt#||z}n*|dks|d krtj|jj}d |z } tj|jtj} |jdkrE||z} || k} d| | <| | tj z} tj|j|| zj} tj|j| }||ks| |krtjd|j }n>|||z }tjt7|j}||| |fS)asReturn the least-squares solution to a linear matrix equation. Solves the equation `a x = b` by computing a vector `x` that minimizes the Euclidean 2-norm `|| b - a x ||^2`. The equation may be under-, well-, or over- determined (i.e., the number of linearly independent rows of `a` can be less than, equal to, or greater than its number of linearly independent columns). If `a` is square and of full rank, then `x` (but for round-off error) is the "exact" solution of the equation. Args: a (cupy.ndarray): "Coefficient" matrix with dimension ``(M, N)`` b (cupy.ndarray): "Dependent variable" values with dimension ``(M,)`` or ``(M, K)`` rcond (float): Cutoff parameter for small singular values. For stability it computes the largest singular value denoted by ``s``, and sets all singular values smaller than ``s`` to zero. Returns: tuple: A tuple of ``(x, residuals, rank, s)``. Note ``x`` is the least-squares solution with shape ``(N,)`` or ``(N, K)`` depending if ``b`` was two-dimensional. The sums of ``residuals`` is the squared Euclidean 2-norm for each column in b - a*x. The ``residuals`` is an empty array if the rank of a is < N or M <= N, but iff b is 1-dimensional, this is a (1,) shape array, Otherwise the shape is (K,). The ``rank`` of matrix ``a`` is an integer. The singular values of ``a`` are ``s``. .. 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.lstsq` rMa `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions. To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.r r zA{}-dimensional array given. Array must be at most two-dimensionalrNrzIncompatible dimensionsF full_matricesrr)r)warningsrM FutureWarningrr _assert_2drr LinAlgErrorformatrr"svdr(finforepsmaxarrayr!int32rHdotTconjr# atleast_1drL)r+r,rcondmnm2usvhs1rankcutoff sing_valszr.residses r2lstsqrns;N   *     Q""" Qvzz "99?II I 7233>>G*j!_DJ???KZM<<>>G E&!W\%sK,<,@ , C!4jBBBKII z 99W   $ $YU $ ; ;;r4V瞯rs*  &&&&&& C C C L&$&$&$&$R>>> XXXXv(+(+(+V:<:<:<|+O+O+O+O\$$$$$$$$$$$$r4