o i7@sddlZddlZddlmZddlZddlmZddlmZddlm Z ddlm Z ddl Z ddZ dd d Z d d ZdddZddZddZdddZdddZdS)N)linalg)internal)device)_decomposition)_utilc Csddlm}ddlm}m}|jdkr |jd|kr |||St||t |t ||j|jks>|j|jdkrO|jdd|jd|jdksSt dt ||\}}|j dkrgt|j|S|jdkr|j|d d d }|j|d d d }||||j|d d S|j|d dd }tj||d}|jdd}tt|D]} t| |} || j|d d d } ||| | | || <q|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.cublasrr ndimshaper_assert_cupy_array_assert_stacked_2d_assert_stacked_square ValueErrorlinalg_common_typesizecupyemptyastypegesv empty_likerangenumpyprod unravel_index) abrrr r out_dtypexriindexbir0O/home/ubuntu/veenaModal/venv/lib/python3.10/site-packages/cupy/linalg/_solve.pysolves:     "     r2cCs|dur!tt|j}|D]}||||j|q ||}|j|j|j d}t|}| 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'reshaperavelr2)r)r*axesallaxeskoldshaper'resultr0r0r1 tensorsolveTs      r>cCs0|jj}t|}tjt||ddS)Nr axis)rcharlowerr ascontiguousarraysumsquareview)r, real_dtyper0r0r1_nrm2_last_axis}s  rHwarncCs|dkr tdtd}t||t||jdkr%td |j|j dd\}}|j d}||krrHrirnrkrrr0r0r0r1s"      F) [+ >.