o W۷iF@sddlmZddlZddlZddlZddlZddlZddlmZddl m Z GdddZ Gddde Z e Z Gd d d e ZeZ efd d Zd dZdddZd ddZd!ddZd"ddZd!ddZd"ddZd!ddZdS)#) annotationsN) from_data)joinc@s2eZdZdZddZddd Zd d Zd d ZdS)AxisConcatenatorzTranslates slice objects to concatenation along an axis. For detailed documentation on usage, see :func:`cupy.r_`. This implementation is partially borrowed from NumPy's one. c CsZ||}|dkr||d7}tt|}|}|d|||d|||}||S)Nr)listrange transpose) selfobjndimndmintrans1dk2defaxesk1axesrM/home/ubuntu/vllm_env/lib/python3.10/site-packages/cupy/_indexing/generate.py _output_objs    zAxisConcatenator._output_objrFrcCs||_||_||_||_dSN)axisrmatrixr )r rrr rrrr__init__"s zAxisConcatenator.__init__c sR|j}|j}g}g}g}ttrtttsftD]\\}}t|tr*tt|tr9|dkr7tdtt |t j vrMt j ||d} ||n)t j |d|d} |dkrqt j |ddj} |dkrq| |krq|| | ||} || || qt jg|fd d |DR} | dur|D] }||| ||<qtjt||jd S) Nrz+special directives must be the first entry.)r F)copyr rrrcsg|]}|qSrr).0kkeyrr Hsz0AxisConcatenator.__getitem__..)r)rr isinstancestrNotImplementedErrortuple enumerateslice ValueErrortypenumpy ScalarTyperarrayappendr r result_typeastyper concatenater) r r rr objsarraysscalarsirnewobjr final_dtyperrr __getitem__(sB       "zAxisConcatenator.__getitem__cCsdS)Nrrr rrr__len__OszAxisConcatenator.__len__N)rFrr)__name__ __module__ __qualname____doc__rrr7r9rrrrrs   'rceZdZfddZZS)CClasscstjdddddS)Nrr)r rsuperrr8 __class__rrrUszCClass.__init__r:r;r<r __classcell__rrrCrr?Sr?cr>)RClasscstdSrrAr8rCrrrvszRClass.__init__rErrrCrrHtrGrHcCsxt|}t|}d|}tj|f||d}t|D]\}}tj||d|d||f||dd||<q|S)aReturns an array representing the indices of a grid. Computes an array where the subarrays contain index values 0,1,... varying only along the corresponding axis. Args: dimensions: The shape of the grid. dtype: Data type specifier. It is int by default. Returns: ndarray: The array of grid indices, ``grid.shape = (len(dimensions),) + tuple(dimensions)``. Examples -------- >>> grid = cupy.indices((2, 3)) >>> grid.shape (2, 2, 3) >>> grid[0] # row indices array([[0, 0, 0], [1, 1, 1]]) >>> grid[1] # column indices array([[0, 1, 2], [0, 1, 2]]) .. seealso:: :func:`numpy.indices` rdtypeNr)r%lencupyemptyr&arangereshape) dimensionsrKNshaperesr4dimrrrindicess  rVcGsg}t|}t|D]B\}}t|}|jdkrtd|jdkr'|tj }t |j t j r4|\}|d||jfd||d}||q t|S)aConstruct an open mesh from multiple sequences. This function takes N 1-D sequences and returns N outputs with N dimensions each, such that the shape is 1 in all but one dimension and the dimension with the non-unit shape value cycles through all N dimensions. Using `ix_` one can quickly construct index arrays that will index the cross product. ``a[cupy.ix_([1,3],[2,5])]`` returns the array ``[[a[1,2] a[1,5]], [a[3,2] a[3,5]]]``. Args: *args: 1-D sequences Returns: tuple of ndarrays: N arrays with N dimensions each, with N the number of input sequences. Together these arrays form an open mesh. Examples -------- >>> a = cupy.arange(10).reshape(2, 5) >>> a array([[0, 1, 2, 3, 4], [5, 6, 7, 8, 9]]) >>> ixgrid = cupy.ix_([0,1], [2,4]) >>> ixgrid (array([[0], [1]]), array([[2, 4]])) .. warning:: This function may synchronize the device. .. seealso:: :func:`numpy.ix_` rz!Cross index must be 1 dimensionalrrI)rLr&rasarrayr r(sizer/r*intprM issubdtyperKbool_nonzerorPr-r%)argsoutndrnewrrrix_s'     & rawrapCc Cst|}t||krtd||D]}t|tjs$tdt|qt|tr/|f|}t t j |t t jjkrAtdd}dg|}|durNdn|}|dkrnt|dddD]}|||d}|||<q^n|d krtd|D]}|||d}|||<qwntd t j|}t j|d jt jd } t||||D]f\}} } } t| t jstd t | t jdstd| jt j| jt jdd} | dkrt t | |k| d krtdn| dkrt | d |d} n| dkr| |} ntd| | | | 7} q| S)a" Converts a tuple of index arrays into an array of flat indices, applying boundary modes to the multi-index. Args: multi_index (tuple of cupy.ndarray) : A tuple of integer arrays, one array for each dimension. dims (tuple of ints): The shape of array into which the indices from ``multi_index`` apply. mode ('raise', 'wrap' or 'clip'), optional: Specifies how out-of-bounds indices are handled. Can specify either one mode or a tuple of modes, one mode per index: - *'raise'* -- raise an error - *'wrap'* -- wrap around (default) - *'clip'* -- clip to the range In 'clip' mode, a negative index which would normally wrap will clip to 0 instead. order ('C' or 'F'), optional: Determines whether the multi-index should be viewed as indexing in row-major (C-style) or column-major (Fortran-style) order. Returns: raveled_indices (cupy.ndarray): An array of indices into the flattened version of an array of dimensions ``dims``. .. warning:: This function may synchronize the device when ``mode == 'raise'``. Notes ----- Note that the default `mode` (``'wrap'``) is different than in NumPy. This is done to avoid potential device synchronization. Examples -------- >>> cupy.ravel_multi_index(cupy.asarray([[3,6,6],[4,5,1]]), (7,6)) array([22, 41, 37]) >>> cupy.ravel_multi_index(cupy.asarray([[3,6,6],[4,5,1]]), (7,6), ... order='F') array([31, 41, 13]) >>> cupy.ravel_multi_index(cupy.asarray([[3,6,6],[4,5,1]]), (4,6), ... mode='clip') array([22, 23, 19]) >>> cupy.ravel_multi_index(cupy.asarray([[3,6,6],[4,5,1]]), (4,4), ... mode=('clip', 'wrap')) array([12, 13, 13]) >>> cupy.ravel_multi_index(cupy.asarray((3,1,4,1)), (6,7,8,9)) array(1621) .. seealso:: :func:`numpy.ravel_multi_index`, :func:`unravel_index` z5parameter multi_index must be a sequence of length {}z-{} object cannot be interpreted as an integerzQinvalid dims: array size defined by dims is larger than the maximum possible sizerNrcr@rForder not understoodrrJz+elements of multi_index must be cupy arrays same_kindzgmulti_index entries could not be cast from dtype('{}') to dtype('{}') according to the rule 'same_kind'Frraisez"invalid entry in coordinates arraycliprbzUnrecognized mode: {})rLr(formatr"numbersIntegral TypeErrorr)r# functoolsreduceoperatormulrMiinfoint64maxupperrbroadcast_arrayszerosrSzipndarraycan_castrKr/any logical_orrh) multi_indexdimsmodeorderr ds ravel_stridesr4raveled_indicesstrideidx_moderrrravel_multi_indexsp8           rcCs|durdn|}|dkrt|}n |dkrntdt|tjds0td|jtj|dk r:tdg}|D] }| ||||}q>|dk rVtd|dkr^t|}t |S) aConverts array of flat indices into a tuple of coordinate arrays. Args: indices (cupy.ndarray): An integer array whose elements are indices into the flattened version of an array of dimensions :obj:`dims`. dims (tuple of ints): The shape of the array to use for unraveling indices. order ('C' or 'F'): Determines whether the indices should be viewed as indexing in row-major (C-style) or column-major (Fortran-style) order. Returns: tuple of ndarrays: Each array in the tuple has the same shape as the indices array. Examples -------- >>> cupy.unravel_index(cupy.array([22, 41, 37]), (7, 6)) (array([3, 6, 6]), array([4, 5, 1])) >>> cupy.unravel_index(cupy.array([31, 41, 13]), (7, 6), order='F') (array([3, 6, 6]), array([4, 5, 1])) .. warning:: This function may synchronize the device. .. seealso:: :func:`numpy.unravel_index`, :func:`ravel_multi_index` NrcrdrerfzlIterator operand 0 dtype could not be cast from dtype('{}') to dtype('{}') according to the rule 'same_kind'rzinvalid entry in index array) rtreversedr(rMryrrrlrirKrzr-r%)rVr}runraveled_coordsrUrrr unravel_indexls0     rcCs"tj||ftjd}|||S)a< Return the indices to access (n, n) arrays, given a masking function. Assume `mask_func` is a function that, for a square array a of size ``(n, n)`` with a possible offset argument `k`, when called as ``mask_func(a, k)`` returns a new array with zeros in certain locations (functions like :func:`~cupy.triu` or :func:`~cupy.tril` do precisely this). Then this function returns the indices where the non-zero values would be located. Args: n (int): The returned indices will be valid to access arrays of shape (n, n). mask_func (callable): A function whose call signature is similar to that of :func:`~cupy.triu`, :func:`~tril`. That is, ``mask_func(x, k)`` returns a boolean array, shaped like `x`. `k` is an optional argument to the function. k (scalar): An optional argument which is passed through to `mask_func`. Functions like :func:`~cupy.triu`, :func:`~cupy.tril` take a second argument that is interpreted as an offset. Returns: tuple of arrays: The `n` arrays of indices corresponding to the locations where ``mask_func(np.ones((n, n)), k)`` is True. .. warning:: This function may synchronize the device. .. seealso:: :func:`numpy.mask_indices` rJ)rMonesint8r\)n mask_funcrarrr mask_indicess!rcs4tj|||tdtfddtjjtdDS)aReturns the indices of the lower triangular matrix. Here, the first group of elements contains row coordinates of all indices and the second group of elements contains column coordinates. Parameters ---------- n : int The row dimension of the arrays for which the returned indices will be valid. k : int, optional Diagonal above which to zero elements. `k = 0` (the default) is the main diagonal, `k < 0` is below it and `k > 0` is above. m : int, optional The column dimension of the arrays for which the returned arrays will be valid. By default, `m = n`. Returns ------- y : tuple of ndarrays The indices for the triangle. The returned tuple contains two arrays, each with the indices along one dimension of the array. See Also -------- numpy.tril_indices rrKc3"|] }t|jVqdSrrM broadcast_torSrindstri_rr ztril_indices..rJrMtriboolr%rVrSintrrmrrr tril_indicess rcC,|jdkr tdt|jd||jddS)a6Returns the indices for the lower-triangle of arr. Parameters ---------- arr : cupy.ndarray The indices are valid for square arrays whose dimensions are the same as arr. k : int, optional Diagonal offset. See Also -------- numpy.tril_indices_from r@input array must be 2-drrr)r r(rrSarrrrrrtril_indices_froms rcs:tj|||dtdtfddtjjtdDS)aReturns the indices of the upper triangular matrix. Here, the first group of elements contains row coordinates of all indices and the second group of elements contains column coordinates. Parameters ---------- n : int The size of the arrays for which the returned indices will be valid. k : int, optional Refers to the diagonal offset. By default, `k = 0` i.e. the main dialogal. The positive value of `k` denotes the diagonals above the main diagonal, while the negative value includes the diagonals below the main diagonal. m : int, optional The column dimension of the arrays for which the returned arrays will be valid. By default, `m = n`. Returns ------- y : tuple of ndarrays The indices for the triangle. The returned tuple contains two arrays, each with the indices along one dimension of the array. See Also -------- numpy.triu_indices rrc3rrrrrrrr3rztriu_indices..rJrrrrr triu_indicess! rcCr)aReturns indices for the upper-triangle of arr. Parameters ---------- arr : cupy.ndarray The indices are valid for square arrays. k : int, optional Diagonal offset (see 'triu_indices` for details). Returns ------- triu_indices_from : tuple of ndarrays Indices for the upper-triangle of `arr`. See Also -------- numpy.triu_indices_from r@rrrr)r r(rrSrrrrtriu_indices_from7s r)rbrc)rc)r)rN) __future__rrmrjror*rMcupy._creationrcupy._manipulationrrr?c_rHr_rrVrarrrrrrrrrrrs0   C ) 7 t = + & '