`irddlZddlZddlmZdZddZejdddd Zd Zdd ZddZ dZ dS)N)_corecjtj|}|j|jkrtdtj|}|d}|jdkrdS|jdkrtd|||ddS)a}Change elements of an array based on conditional and input values. This function uses the first N elements of `vals`, where N is the number of true values in `mask`. Args: arr (cupy.ndarray): Array to put data into. mask (array-like): Boolean mask array. Must have the same size as `a`. vals (array-like): Values to put into `a`. Only the first N elements are used, where N is the number of True values in `mask`. If `vals` is smaller than N, it will be repeated, and if elements of `a` are to be masked, this sequence must be non-empty. Examples -------- >>> arr = np.arange(6).reshape(2, 3) >>> np.place(arr, arr>2, [44, 55]) >>> arr array([[ 0, 1, 2], [44, 55, 44]]) .. warning:: This function may synchronize the device. .. seealso:: :func:`numpy.place` z$Mask and data must be the same size.rNz"Cannot insert from an empty array.wrapmode)cupyasarraysize ValueErrorravelnonzeroput)arrmaskvals mask_indicess i/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/cupy/_indexing/insert.pyplacers: <  D x49?@@@ <  D::<<''))!,LA yA~~=>>>GGL$VG,,,,,rc6||||dS)aReplaces specified elements of an array with given values. Args: a (cupy.ndarray): Target array. ind (array-like): Target indices, interpreted as integers. v (array-like): Values to place in `a` at target indices. If `v` is shorter than `ind` it will be repeated as necessary. mode (str): How out-of-bounds indices will behave. Its value must be either `'raise'`, `'wrap'` or `'clip'`. Otherwise, :class:`TypeError` is raised. .. note:: Default `mode` is set to `'wrap'` to avoid unintended performance drop. If you need NumPy's behavior, please pass `mode='raise'` manually. .. seealso:: :func:`numpy.put` rN)r)aindvrs rrr1s"$EE#qtErz%Q mask, raw S values, uint64 len_valszT outz3 if (mask) out = (T) values[i % len_vals]; cupy_putmask_kernelct|tjstdt|tjstdtj|s)t|tjstd|j|jkst d|tj }tj|r|||<dStj |j |j s-td |j |j |j|jkr ||||<dS| }t||t||dS)a Changes elements of an array inplace, based on a conditional mask and input values. Sets ``a.flat[n] = values[n]`` for each n where ``mask.flat[n]==True``. If `values` is not the same size as `a` and `mask` then it will repeat. Args: a (cupy.ndarray): Target array. mask (cupy.ndarray): Boolean mask array. It has to be the same shape as `a`. values (cupy.ndarray or scalar): Values to put into `a` where `mask` is True. If `values` is smaller than `a`, then it will be repeated. Examples -------- >>> x = cupy.arange(6).reshape(2, 3) >>> cupy.putmask(x, x>2, x**2) >>> x array([[ 0, 1, 2], [ 9, 16, 25]]) If `values` is smaller than `a` it is repeated: >>> x = cupy.arange(6) >>> cupy.putmask(x, x>2, cupy.array([-33, -44])) >>> x array([ 0, 1, 2, -44, -33, -44]) .. seealso:: :func:`numpy.putmask` z"`a` should be of type cupy.ndarrayz%`mask` should be of type cupy.ndarrayz'`values` should be of type cupy.ndarrayz#mask and data must be the same sizezACannot cast array data from {} to {} according to the rule 'safe'N) isinstancerndarray TypeErrorisscalarshaper astypenumpybool_can_castdtypeformatr _putmask_kernellen)rrvaluess rputmaskr*OsfF a & &><=== dDL ) )A?@@@ M& ! !CZ %E%ECABBB 7dj >??? ;;u{ # #D }V 6$ ^FL!' 2 2 6C ag6688 8 FL ,$fc&kk155555rFc|jdkrtdd}|jdkr.|jddz}|s|jd|jdz}nttjtj|jdkstddtj|jddz}||jd||<dS)a1Fills the main diagonal of the given array of any dimensionality. For an array `a` with ``a.ndim > 2``, the diagonal is the list of locations with indices ``a[i, i, ..., i]`` all identical. This function modifies the input array in-place, it does not return a value. Args: a (cupy.ndarray): The array, at least 2-D. val (scalar): The value to be written on the diagonal. Its type must be compatible with that of the array a. wrap (bool): If specified, the diagonal is "wrapped" after N columns. This affects only tall matrices. Examples -------- >>> a = cupy.zeros((3, 3), int) >>> cupy.fill_diagonal(a, 5) >>> a array([[5, 0, 0], [0, 5, 0], [0, 0, 5]]) .. seealso:: :func:`numpy.fill_diagonal` zarray must be at least 2-dNr/All dimensions of input must be of equal length) ndimr r r"alldiffcumprodsumflat)rvalrendsteps r fill_diagonalr9s4 vzz5666 Cv{{wqzA~ *'!*qwqz)CyAG,,122 PNOO O5="..22444AF9C9rr,c6tj|}|f|zS)aIReturn the indices to access the main diagonal of an array. Returns a tuple of indices that can be used to access the main diagonal of an array with ``ndim >= 2`` dimensions and shape (n, n, ..., n). Args: n (int): The size, along each dimension of the arrays for which the indices are to be returned. ndim (int): The number of dimensions. default `2`. Examples -------- Create a set of indices to access the diagonal of a (4, 4) array: >>> di = cupy.diag_indices(4) >>> di (array([0, 1, 2, 3]), array([0, 1, 2, 3])) >>> a = cupy.arange(16).reshape(4, 4) >>> a array([[ 0, 1, 2, 3], [ 4, 5, 6, 7], [ 8, 9, 10, 11], [12, 13, 14, 15]]) >>> a[di] = 100 >>> a array([[100, 1, 2, 3], [ 4, 100, 6, 7], [ 8, 9, 100, 11], [ 12, 13, 14, 100]]) Create indices to manipulate a 3-D array: >>> d3 = cupy.diag_indices(2, 3) >>> d3 (array([0, 1]), array([0, 1]), array([0, 1])) And use it to set the diagonal of an array of zeros to 1: >>> a = cupy.zeros((2, 2, 2), dtype=int) >>> a[d3] = 1 >>> a array([[[1, 0], [0, 0]], [[0, 0], [0, 1]]]) .. seealso:: :func:`numpy.diag_indices` )rarange)nr0idxs r diag_indicesr>sh +a..C 6D=rcDt|tjstd|jdkst dtjtj|jdkst dt|jd|jS)z Return the indices to access the main diagonal of an n-dimensional array. See `diag_indices` for full details. Args: arr (cupy.ndarray): At least 2-D. .. seealso:: :func:`numpy.diag_indices_from` zArgument must be cupy.ndarrayr,z input array must be at least 2-drr.) rrrrr0r r1r2r r>)rs rdiag_indices_fromr@s c4< ( (97888 8q==;<<< 8DIci((A- . .LJKKK  ! ch / //r)r)F)r,) r"rrrrElementwiseKernelr'r*r9r>r@rrrCs '-'-'-T**%)+W <6<6<6~&&&&R5555p00000r