+ ja#2Rt^RIt^RIHtHtHt^RIHt^RIt^RI H t RRlt !RR] ] 4t!R R ]]4tR R ltR RltR&RRlltR'RRlltRRltRRltRRltRR/RRlltRRltRRltR R!ltR(R"R#lltR$R%ltR#))zKAssorted utilities, which do not need anything other than torch and stdlib.N)IterableSequenceSized) TypeGuard) _dtypes_implcFV^8dQhR\R\\,/#)seqreturn)objectrr)formats"S/home/luca/screen-checking/.venv/lib/python3.14/site-packages/torch/_numpy/_util.py __annotate__r s  V  % 0 c\V\4'dR#\V\4'gR#\V4R# \dR#i;i)FT) isinstancestrrlen Exception)r s&r is_sequencer sG#s c5 ! ! C  s ? A Ac]tRt^tRtR#) AxisErrorN__name__ __module__ __qualname____firstlineno____static_attributes__rrr rrrrc]tRt^tRtR#)UFuncTypeErrorrNrrrr r!r!rrr!cV^8dQhR\PR\PR,R\P/#)rtensordtypeNr )torchTensorr$)r s"r rr!s25<< d0Bu||rcRVe#VPV8wdVPV4pV#N)r$to)r#r$s&&r cast_if_neededr*!s& V\\U25! 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Parameters ---------- axis : int, iterable of int The un-normalized index or indices of the axis. ndim : int The number of dimensions of the array that `axis` should be normalized against. argname : str, optional A prefix to put before the error message, typically the name of the argument. allow_duplicate : bool, optional If False, the default, disallow an axis from being specified twice. Returns ------- normalized_axes : tuple of int The normalized axis index, such that `0 <= normalized_axis < ndim` c3><"TFp\VSS4xK R#5ir()r8).0r3r5r4s& r 'normalize_axis_tuple..gsJTr'D'::Tzrepeated axis in `z ` argumentz repeated axis) rr=listoperatorindex TypeErrorrsetmapr6 ValueError)r:r4r5r;axesresults&ff& r normalize_axis_tuplerM9sH$ && NN4()DUJTJUUJTJ JF s3s3'7#89S[H 1'*EF F_- - M D sC CCc|V^8dQhR\\\R3,,R,R\R,/#)rr:.Nr )r6r=)r s"r rrps0uS#X!6!=#*rcVfV#\V\4'dV#\V4^8wd \R4hV^,#)Nzdoes not handle tuple axis)rr6rNotImplementedError)r:s&r allow_only_single_axisrQps> | $  4yA~!">?? 7NrcV^8dQhR\\,R\\\R3,,\\,,R\\,/#)r arr_shaper:.r )rr6r=rD)r s"r rrzsB  } $'%S/$9DI$E  #Y rc \V\\34'dTMV3p\V4\V4,p\ W#4p\ V4p\ V4Uu.uFqfV9d^M \V4NK ppV#uupi)rrDr=rrMiterrangenext)rSr:axis_seqout_ndim normalizedshape_itr3shapes&& r expand_shaper_zss"$u 66tTGH8}s9~-H%h9JIHAFx Q2 "QX 6E Q L Rs BcV^8dQhR\PR\\\R3,,R,R\R\P/#)rr#r:.Nr4r r%r&r6r=)r s"r rrsF   LL  #eCHo 5 < DG  \\ rcVf+RV,pVPV4P4pV#\VPV4pVP V4pV#)NrU)expand contiguousr_r^reshape)r#r:r4r^s&&& r apply_keepdimsrfsU |t u%002 MV\\40& Mrr:c V^8dQhR\PR\R,R\\\PR3,\3,/#)rtensorsr:Nr .ra)r s"r rrsDll"%* 5s" #S ()rcpVf1\;QJd.RV4FNK 5M !RV44pV^3#W3#)z#Flatten the arrays if axis is None.c3@"TFqP4xK R#5ir()flatten)r@ars& r rA$axis_none_flatten..s7w wsr=)r:rhs$*r axis_none_flattenros9 |%7w7%%7w77z}rcV^8dQhR\PR\PR\R\P/#)rt target_dtypecastingr )r%r&r$r)r s"r rrs8++ ||+#(;;+9<+ \\+rc \PpV!VPWR7'g \RVP RV RV R24h\ W4#)aDtype-cast tensor to target_dtype. Parameters ---------- t : torch.Tensor The tensor to cast target_dtype : torch dtype object The array dtype to cast all tensors to casting : str The casting mode, see `np.can_cast` Returns ------- `torch.Tensor` of the `target_dtype` dtype Raises ------ ValueError if the argument cannot be cast according to the `casting` rule )rszCannot cast array data from z to z according to the rule '')r can_cast_implr$rGr*)rqrrrscan_casts&&& r typecast_tensorrxs^0))H AGG\ ; ;*177)4~5gYa A   ! **rc V^8dQhR\\P,R\PR\R\ \PR3,/#)rrhrrrsr .)rr%r&r$rr=)r s"r rrsMMM ell #M38;;MILM 5<< Mrcnaa\;QJd.VV3RlV4FNK 5#!VV3RlV44#)c3><"TFp\VSS4xK R#5ir()rx)r@rqrsrrs& r rA#typecast_tensors..sLGqL'::GrCrn)rhrrrss&ffr typecast_tensorsr}s' 5LGL5L5LGL LLrcDV^8dQhR\R\P/#)robjr )r r%r&)r s"r rrs5<<rc\P!V4pV# \d#pRT R\T4 R2p\ T4hRp?ii;i)zfailed to convert z! to ndarray. Internal error is: .N)r% as_tensorrrrP)rr#emesgs& r _try_convert_to_tensorrsS(% M (#C5(J3q6(RST!$''(s AAAc V^8dQhR\R\PR,R\R\R\P /#)rrr$Ncopyndminr )r r%r$r<r6r&)r s"r rrsN@@ @ ;; @ @  @  \\ @rch\V\P4'dTpMo\P!4p\P!\ P !\P44\V4p\P!V4\WA4pW4P, pV^8d*VPRV,VP,4p\V4pV'dVP4pV# \P!T4i;i \dRpLDi;i)adThe core logic of the array(...) function. Parameters ---------- obj : tensor_like The thing to coerce dtype : torch.dtype object or None Coerce to this torch dtype copy : bool Copy or not ndmin : int The results as least this many dimensions is_weak : bool Whether obj is a weakly typed python scalar. Returns ------- tensor : torch.Tensor a tensor object with requested dtype, ndim and copy semantics. Notes ----- This is almost a "tensor_like" coercive function. Does not handle wrapper ndarrays (those should be handled in the ndarray-aware layer prior to invoking this function). 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