9j;$SSKJr SSKrSSKJr SSKJr SSKJr SSKJ r \RRSSS S 5r SS jrSS jrSS jrSSjrSSjrSSjrSSjrSrg)) annotationsN)_routines_logic)_fusion_thread_local)search)_utilzraw T X, int64 lenzbool zzBz = (i == 0 || X[i] != X[i-1]) && (i == len - 1 || X[i] != X[i+1]) setxorkernelc[R"5(a6U(a [S5e[R"[R XUS9$[ R"USS9 UR XUS9$)aTests whether all array elements along a given axis evaluate to True. Parameters ---------- a : cupy.ndarray Input array. axis : int or tuple of ints Along which axis to compute all. The flattened array is used by default. out : cupy.ndarray Output array. keepdims : bool If ``True``, the axis is remained as an axis of size one. Returns ------- y : cupy.ndarray An array reduced of the input array along the axis. See Also -------- numpy.all z3cupy.all does not support `keepdims` in fusion yet.axisoutaarg_namer r keepdims)r is_fusingNotImplementedErrorcall_reduction_logicallr check_arrayr r r rs K/home/wildlama/miniconda3/lib/python3.13/site-packages/cupy/_logic/truth.pyrrk2%%'' %EG G#22 JJ#/ / a#& 55dh5 77c[R"5(a6U(a [S5e[R"[R XUS9$[ R"USS9 UR XUS9$)aTests whether any array elements along a given axis evaluate to True. Parameters ---------- a : cupy.ndarray Input array. axis : int or tuple of ints Along which axis to compute all. The flattened array is used by default. out : cupy.ndarray Output array. keepdims : bool If ``True``, the axis is remained as an axis of size one. Returns ------- y : cupy.ndarray An array reduced of the input array along the axis. See Also -------- numpy.any z3cupy.any does not support `keepdims` in fusion yet.r r rr)rrrrranyrrrs rrr7rrcUR5nUR5nURS:XdURS:XaaU(a-[R"UR[R S9$[R "UR[R S9$[R"U5n[R"XURU5$)aTests whether each element of a 1-D array is also present in a second array. Returns a boolean array the same length as ``ar1`` that is ``True`` where an element of ``ar1`` is in ``ar2`` and ``False`` otherwise. Parameters ---------- ar1 : cupy.ndarray Input array. ar2 : cupy.ndarray The values against which to test each value of ``ar1``. assume_unique : bool, optional Ignored invert : bool, optional If ``True``, the values in the returned array are inverted (that is, ``False`` where an element of ``ar1`` is in ``ar2`` and ``True`` otherwise). Default is ``False``. Returns ------- y : cupy.ndarray, bool The values ``ar1[in1d]`` are in ``ar2``. rdtype) ravelsizecupyonesshapebool_zerossort_search_exists_kernel)ar1ar2 assume_uniqueinverts rin1dr/\s6 ))+C ))+C xx1}A 99SYYdjj9 9::ciitzz: : ))C.C  ! !#CHHf ==rc[R"URUR5nU(dcU(a/[R"USS9up[R"USS9upOM[R"U5n[R"U5nO UR 5nUR 5nU(d5[ R "XURS5nXRU5$[ R"XURS5upxXRU5n [R"U5n Xn U(d WU n WU n XU 4$)aFind the intersection of two arrays. Returns the sorted, unique values that are in both of the input arrays. Parameters ---------- arr1, arr2 : cupy.ndarray Input arrays. Arrays will be flattened if they are not in 1D. assume_unique : bool By default, False. If set True, the input arrays will be assumed to be unique, which speeds up the calculation. If set True, but the arrays are not unique, incorrect results and out-of-bounds indices could result. return_indices : bool By default, False. If True, the indices which correspond to the intersection of the two arrays are returned. Returns ------- intersect1d : cupy.ndarray Sorted 1D array of common and unique elements. comm1 : cupy.ndarray The indices of the first occurrences of the common values in `arr1`. Only provided if `return_indices` is True. comm2 : cupy.ndarray The indices of the first occurrences of the common values in `arr2`. Only provided if `return_indices` is True. See Also -------- numpy.intersect1d T) return_indexF) r# result_typer uniquer!r)r*r"astype_exists_and_searchsorted_kernel flatnonzero) arr1arr2r-return_indices common_dtypeind1ind2maskv1int1d arr1_indices arr2_indicess r intersect1drBsB##DJJ ;L  T=JDT=JD$;;t$D;;t$Dzz|zz| %%d$))UCz  ..66 DIIu&HD J  l +E##D)L8L L) L)  ,,rcJ[XUUS9RUR5$)a(Calculates element in ``test_elements``, broadcasting over ``element`` only. Returns a boolean array of the same shape as ``element`` that is ``True`` where an element of ``element`` is in ``test_elements`` and ``False`` otherwise. Parameters ---------- element : cupy.ndarray Input array. test_elements : cupy.ndarray The values against which to test each value of ``element``. This argument is flattened if it is an array or array_like. assume_unique : bool, optional Ignored invert : bool, optional If ``True``, the values in the returned array are inverted, as if calculating element not in ``test_elements``. Default is ``False``. Returns ------- y : cupy.ndarray, bool Has the same shape as ``element``. The values ``element[isin]`` are in ``test_elements``. r-r.)r/reshaper%)element test_elementsr-r.s risinrHs&8 m &ww}}56rcU(a[R"U5nO,[R"U5n[R"U5nU[XSSS9$)a`Find the set difference of two arrays. It returns unique values in `ar1` that are not in `ar2`. Parameters ---------- ar1 : cupy.ndarray Input array ar2 : cupy.ndarray Input array for comparison assume_unique : bool By default, False, i.e. input arrays are not unique. If True, input arrays are assumed to be unique. This can speed up the calculation. Returns ------- setdiff1d : cupy.ndarray Returns a 1D array of values in `ar1` that are not in `ar2`. It always returns a sorted output for unsorted input only if `assume_unique=False`. See Also -------- numpy.setdiff1d TrD)r#r!r3r/)r+r,r-s r setdiff1drJsD6jjokk#kk# tCD> ??rc `U(d,[R"U5n[R"U5n[R"X4SS9nURS:XaU$UR 5 U[ X3R[R "UR[RS95$)aFind the set exclusive-or of two arrays. Parameters ---------- ar1, ar2 : cupy.ndarray Input arrays. They are flattened if they are not already 1-D. assume_unique : bool By default, False, i.e. input arrays are not unique. If True, input arrays are assumed to be unique. This can speed up the calculation. Returns ------- setxor1d : cupy.ndarray Return the sorted, unique values that are in only one (not both) of the input arrays. See Also -------- numpy.setxor1d Nr rr)r#r3 concatenater"r( _setxorkernelr'r&)r+r,r-auxs rsetxor1drPs. kk#kk#   C:D 1C xx1} HHJ }S((!ZZ CE FFrcV[R"[R"X4SS95$)aYFind the union of two arrays. Returns the unique, sorted array of values that are in either of the two input arrays. Parameters ---------- arr1, arr2 : cupy.ndarray Input arrays. They are flattened if they are not already 1-D. Returns ------- union1d : cupy.ndarray Sorted union of the input arrays. See Also -------- numpy.union1d NrL)r#r3rM)r7r8s runion1drR*s"* ;;t'' 4@ AAr)NNF)FF)F) __future__rr# cupy._corerrr cupy._sortingrr)r_coreElementwiseKernelrNrrr/rBrHrJrPrRrrrYsk" 0++ ,, H  "8J"8J%>P;-|6@ @F"FJBr