3j SrSSKJr SSKrSSKJrJr SSKrSSKJ r SSK J r SSK J r SS KJr \(aSS KJr SS jr"S S 5rSSSjjrSSSjjrSSjrSSSjjrSSSjjrg)zM Python implementation of function wrapping functionality for functorch.dim. ) annotationsN)Any TYPE_CHECKING)tree_map)DimEntry)EnableAllLayers) TensorInfo)CallablecU$)z8Handle tensor conversion for torch function integration.)tensors M/home/wildlama/miniconda3/lib/python3.13/site-packages/functorch/dim/_wrap.pyhandle_from_tensorrs Mc<\rSrSrSrSSSjjrS SjrSrg) WrappedOperatorzH This class wraps PyTorch operations to support first-class dimensions. c@XlX l[USS5Ul[USS5UlX0lSUlSUlSUlSUl SUl UR(a4UR (a"URSUR S 3Ulggg) N__name____doc__FrrTz Argument 'z5' can be either an integer or a torchdim.Dim object. ) origwrapper_implementationgetattrnamedocdim_name is_pointwise dim_offsetkeepdim_offset single_dimreduce)selfrrrs r__init__WrappedOperator.__init__ s &<#D*b1 4D1 !  88 ((< >tuDH&8rc|^SU4Sjjn[R"UTRSSS9 TRUlU$)z@Create a wrapped function that calls our wrapper implementation.c0>TR"T/UQ70UD6$)N)r)argskwargsr$s r wrapped_func.WrappedOperator.function..wrapped_func6s..tEdEfE Er)rr )assignedupdated)r)rr*rreturnr) functoolsupdate_wrapperrrr)r$r+s` rfunctionWrappedOperator.function3s: F   $))mR  $xx r) rr rrr!rrr#r"rN)dim)rr rr rstr)r/r )r __module__ __qualname____firstlineno__rr%r2__static_attributes__r rrrrs4 QVvv6>vJMv& rrcSSKJn [X5(aU(a [S5e[ U5$[U[ 5(aUnUS:a XA-nUS:aM [ U5$[ 5$)z:Convert single dimension specification to DimEntry object.r)Dimz8cannot preserve first-class dimensions with keepdim=Truer)rr; isinstance ValueErrorrint)r4ndimkeepdimr;is r _wrap_dimrBBsd# WX X} C   1f IA1f{zrc[XU5n/nUR5(dURU5 U$UHnUR[XQU55 M U$)z[U[R5(a#SSKJn UR UTTR 5$U$)Nr)Tensor)r<torchrOrfrom_positional has_device)objrOinfo new_levelss r wrap_result'patched_dim_method..wrap_results5 c5<< ( ( ))#z4??K K r)rSrr/r)r=getrr lenr createrr levels batchedtensorAssertionErrorinplace_update_layerslistr from_batchedrRr#r!boolr?rI enumeratehasattrrMr5rEtuplecopyrr)wrapperr)r*dim_argdim_idxguardnew_argsrGr@ keepdim_arg keepdim_idxr?dims dim_indicesseenrHmidxrAlevel level_strs py_indices new_kwargsrVrTrUs @@rpatched_dim_methodru_s @AAjj))*G7--D 9$$q( SY mG  aeT<<00 0 T[[ )U!!)$%LMM  ' '(:(:DKK HDzH,T-?-?@HQK\\86v6F%%fdoo>* )   T!W %D ||T,V,,G~~jj+  7#9#9CI#E!0014KSY&"/  ";'G 99;D gW -D K 7S% %D !$++.HAuz/ <%dkk255),,q1A1AD3 |6:kkBkUc%jk B -j\9KA3OT 4 +0J~~g!$++.HAu77!!%(/[[^  ;1%a. ;' DzHJ {{=>>$T[[1HQK:%'1 7##$$$q( S] "H~H *H \\8 2z 2F K ((E* )`Cs8BQ:Q QcU=(d Sn[U[U5nUbXlUbX&lUbXFlUbXVlUR 5$)a Wrap a PyTorch function to support first-class dimensions. Args: orig: Original function to wrap dim_offset: Offset for dimension argument (default: 0) keepdim_offset: Offset for keepdim argument (default: 1) dim_name: Name of dimension parameter (default: "dim") single_dim: Whether function takes single dimension (default: False) reduce: Whether function reduces dimensions (default: True) r4)rrur r!r"r#r2)rr r!rr"r#rfs r_wraprws[& 5Hd$6AG'!!/'     rc<Uc0nSSKJn URXX45$)z8 Handle __torch_function__ calls for wrapped operators. r)_Tensor)rry__torch_function__)rffunctypesr)r*rys rcall_torch_functionr}s(~  % %d4 @@r)r torch.Tensorr/r~)F)r4rr?r>r@rar/r)r4rr?r>r@rar/zlist[DimEntry])rfrr)rr*rr/r)NNNNN)rr r int | Noner!rrz str | Noner" bool | Noner#rr/r )r N) rfrr{r r|rdr)rdr*z dict | Noner/r)r __future__rr0typingrrrPtorch.utils._pytreer _dim_entryr_enable_all_layersr _tensor_infor collections.abcr rrrBrIrurwr}r rrrs#% ( /$( $$N" w)x"!%"           N A A A A  A  A  Ar