`i52ddlZddlZddlZddlZddlmZddlmZddlm Z ddl m Z ddl m Z e ej dddd Z dd Zd ZddZdZddZddZdZdZdZdS)N)_core)internal)_GUFunc)_solve)_utilz(n?,k),(k,m?)->(n?,m?)Tamatmul(x1, x2, /, out=None, \*\*kwargs) Matrix product of two arrays. Returns the matrix product of two arrays and is the implementation of the `@` operator introduced in Python 3.5 following PEP465. The main difference against cupy.dot are the handling of arrays with more than 2 dimensions. For more information see :func:`numpy.matmul`. Args: x1 (cupy.ndarray): The left argument. x2 (cupy.ndarray): The right argument. out (cupy.ndarray, optional): Output array. \*\*kwargs: ufunc keyword arguments. Returns: cupy.ndarray: Output array. .. seealso:: :func:`numpy.matmul` )supports_batched supports_outdocc.|||S)aCReturns a dot product of two arrays. For arrays with more than one axis, it computes the dot product along the last axis of ``a`` and the second-to-last axis of ``b``. This is just a matrix product if the both arrays are 2-D. For 1-D arrays, it uses their unique axis as an axis to take dot product over. Args: a (cupy.ndarray): The left argument. b (cupy.ndarray): The right argument. out (cupy.ndarray): Output array. Returns: cupy.ndarray: The dot product of ``a`` and ``b``. .. seealso:: :func:`numpy.dot` )dotabouts h/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/cupy/linalg/_product.pyr r +s( 55C==c |j|jkrtd|jjdkr|}t j||ddd|jdS)a~Returns the dot product of two vectors. The input arrays are flattened into 1-D vectors and then it performs inner product of these vectors. Args: a (cupy.ndarray): The first argument. b (cupy.ndarray): The second argument. Returns: cupy.ndarray: Zero-dimensional array of the dot product result. .. seealso:: :func:`numpy.vdot` Axis dimension mismatchcN)size ValueErrordtypekindconjrtensordot_core)rrs rvdotrBs]  v2333w|s FFHH  1dAq!&" = ==rc| |fdz\}}}tj|}tj|}tj||j}tj||j}tj||d}tj||d}|jddvs|jddvrd}t|tj|d|dj}|jddks|jddkr'|dz }tj|t|}tj |j |j }tj ||} |d} |d} |jddkr|d } |d} |d}|jddkr|d }| jd kr)| jddkr| d}| d}| d }|jdd kr|jdd kr!tj | || | | | zz} | S|jddksJtj | || tj | || tj|| tj | || || | zz}n"|jddksJ|jddkrtj | || | |z}||z}tj | | | tj | || ||z}tj | || tj | | | ||z}nv|jdd ksJtj | || tj|| tj | | | tj | || || | zz}tj| d|S) aReturns the cross product of two vectors. The cross product of ``a`` and ``b`` in :math:`R^3` is a vector perpendicular to both ``a`` and ``b``. If ``a`` and ``b`` are arrays of vectors, the vectors are defined by the last axis of ``a`` and ``b`` by default, and these axes can have dimensions 2 or 3. Where the dimension of either ``a`` or ``b`` is 2, the third component of the input vector is assumed to be zero and the cross product calculated accordingly. In cases where both input vectors have dimension 2, the z-component of the cross product is returned. Args: a (cupy.ndarray): Components of the first vector(s). b (cupy.ndarray): Components of the second vector(s). axisa (int, optional): Axis of ``a`` that defines the vector(s). By default, the last axis. axisb (int, optional): Axis of ``b`` that defines the vector(s). By default, the last axis. axisc (int, optional): Axis of ``c`` containing the cross product vector(s). Ignored if both input vectors have dimension 2, as the return is scalar. By default, the last axis. axis (int, optional): If defined, the axis of ``a``, ``b`` and ``c`` that defines the vector(s) and cross product(s). Overrides ``axisa``, ``axisb`` and ``axisc``. Returns: cupy.ndarray : Vector cross product(s). .. seealso:: :func:`numpy.cross` Nr)r!zDincompatible dimensions for cross product (dimension must be 2 or 3)).r)r!).r).r"rr"r)cupyasarrayr_normalize_axis_indexndimmoveaxisshaper broadcastlen promote_typesremptymultiplynegative)rraxisaaxisbaxiscaxismsgr)rcpa0a1a2b0b1b2cp0cp1cp2tmps rcrossr@ZsL #gkue QA QA  *5!& 9 9E  *5!& 9 9E a##A a##Awr{&  AGBKv$=$=,oo N1V9ai 0 0 6Ewr{a172;!++  .uc%jjAA  qw 0 0E E5 ! !B 6B 6Bwr{a vY 6B 6Bwr{a vY w!|| ))jjjwr{a 72;!   M"bb ) ) ) ) "r'MBI72;!#### M"bc * * * * M"bc * * * * M#3 ' ' ' ' M"bc * * * * 27NCCwr{a 72;!   M"bc * * * *r'C 3JC M"bc * * * * M"bc * * * * 3JC M"bc * * * * M"bc * * * * 3JCC72;!#### M"bc * * * * M#3 ' ' ' ' M"bc * * * * M"bc * * * * 27NC =R ' ''rc |j}|j}|dks|dkrtj||S|dz }|dz }|jd|jdkrt d|rtj||d}|rtj||d}|jdd|jddz}|jd}|j|z}|j|z} tj||d|| ||S)aGReturns the inner product of two arrays. It uses the last axis of each argument to take sum product. Args: a (cupy.ndarray): The first argument. b (cupy.ndarray): The second argument. Returns: cupy.ndarray: The inner product of ``a`` and ``b``. .. seealso:: :func:`numpy.inner` rrrrN) r'r$r.r)rrollaxisrrr) rra_ndimb_ndima_axisb_axis ret_shapeknms rinnerrKsVF VF {{fkk}Q""" aZF aZFwr{agbk!!2333 ( M!VQ ' ' ( M!VQ ' ' agabbk)I  A ! A ! A  1dAq!Y ? ??rctj|dddf|dddf|S)aReturns the outer product of two vectors. The input arrays are flattened into 1-D vectors and then it performs outer product of these vectors. Args: a (cupy.ndarray): The first argument. b (cupy.ndarray): The second argument. out (cupy.ndarray): Output array. Returns: cupy.ndarray: 2-D array of the outer product of ``a`` and ``b``. .. seealso:: :func:`numpy.outer` Nr#)r$r.ravelr s routerrNsE" =111d7+QWWYYtQQQw-?S I I IIrr"c L |j |j dks dkr0|dkr|dkrtdtj||St |t jjrVt|dkrtd|\}}tj |r|f}tj |r|f}nztensordot..C@@@tf}@@@rcg|]}|zSrr)rQr3rDs rrRztensordot..DrSrN)r'rr$r. isinstance collectionsabcSequencer+numpyisscalartuplerangezipr)_move_axes_to_headrprodrrr)rraxesa_axesb_axessum_ndimrErFrGrHrIrJrCrDs @@r tensordotrds<.VF VF {{fkk 199))MNN N}Q"""$ 011 $ t99>>?@@ @ >& ! ! WF >& ! ! WFuVd]F3344uT{{##6{{H3v;;/000ff--88 76?agfo - -677 7 . 1@@@@@@@AAA1@@@@@@@AAA "QWXYY%77I agixi())AAvv! 1AAvv! 1A  1dAq!Y ? ??rctj|tj|tj|t |t st d|dkrtj|S|dkrtj |}|dz}|dkrK|dkr|S|dkrtj ||Stj tj |||Sd\}}tj |dddD]:}||ntj ||}|d kr||ntj ||};|S) a Raise a square matrix to the (integer) power `n`. Args: M (~cupy.ndarray): Matrix to raise by power n. n (~int): Power to raise matrix to. Returns: ~cupy.ndarray: Output array. ..seealso:: :func:`numpy.linalg.matrix_power` zexponent must be an integerrrr!rr")NNN1) r_assert_cupy_array_assert_stacked_2d_assert_stacked_squarerUint TypeErrorstacked_identity_likerinvr$matmul binary_repr)MrIresultZrs r matrix_powerrsRsV Q Q  ### a  75666Avv*1--- Q JqMM R Avv 66H !VV;q!$$ $;t{1a00!44 4IFA  a 2 &EEAA Aq 1 1 88 .QQdk&!.D.DF Mrc "t|tj}t|tj}|r|r||zS|s|rtj||S|j}|j}|dks|dkrtj||S|}|j}|j}||kr||kr d||z z|z}n d||z z|z}|}|dz } tj||d|j |j d||z} t|D]} tj | | } | S)zReturns the kronecker product of two arrays. Args: a (~cupy.ndarray): The first argument. b (~cupy.ndarray): The second argument. Returns: ~cupy.ndarray: Output array. .. seealso:: :func:`numpy.kron` r)rrN)r3) rUnumbersNumberr$r.r'r)rrrr\concatenate_method) rr a_isnumber b_isnumberrCrDr'a_shapeb_shaper3r_s rkronr}~sHAw~..JAw~..Jj1u #Z#}Q""" VF VF {{fkk}Q""" DgGgG  F??fvo.8GGfvo.8GD !8D   1dAFAFAw'8 : :C 4[[77&s666 JrctD] \}}||krn|S|fdt|jDzS)Ncg|]}|v| Srr)rQir`s rrRz&_move_axes_to_head..s:::aATMMMMMr) enumerate transposer\r')rr`idxr3s ` rr^r^sqt__ T $;; E  ;; ::::5==:::: < <rsj ''''''  L     :.>>>0w(w(w(w(t%@%@%@PJJJJ(>@>@>@>@D)))X)))X < < < <