i4SrSSKrSSKJr SS/rS SjrSrg) z1 Determines if a contraction can use BLAS or not N)helperscan_blas tensor_blasc[U5S:wagUupE[XE-5HRnURU5URU5pUS:dUS:dXx-S:a gXx-S- [Xa;5:XdMR g Ub;UH5nUSUR U5USUR U5:wdM5 g [U5S:XagUV s/sHn [U 5PM n n U SU- n U SU- n [U5n USUS:XagU SU S:XagXM*SUSU :Xag USU X]*S:Xag XM*SX]*S:Xag USU USU :Xag [U 5S:Xd[U 5S:Xag g s sn f) a Checks if we can use a BLAS call. Parameters ---------- inputs : list of str Specifies the subscripts for summation. result : str Resulting summation. idx_removed : set Indices that are removed in the summation shapes : sequence of tuple[int], optional If given, check also that none of the indices are broadcast dimensions. Returns ------- type : str or bool The type of BLAS call to be used or False if none. Notes ----- We assume several operations are not efficient such as a transposed DDOT, therefore 'ijk,jki->' should prefer einsum. These return the blas type appended with "/EINSUM" to differentiate when they can still be done with tensordot if required, e.g. when a backend has no einsum. Examples -------- >>> can_blas(['ij', 'jk'], 'ik', set('j')) 'GEMM' >>> can_blas(['ijj', 'jk'], 'ik', set('j')) False >>> can_blas(['ab', 'cd'], 'abcd', set()) 'OUTER/EINSUM' >>> # looks like GEMM but actually 'j' is broadcast: >>> can_blas(['ij', 'jk'], 'ik', set('j'), shapes=[(4, 1), (5, 6)]) False FrNrz OUTER/EINSUMDOTz DOT/EINSUMGEMMz GEMV/EINSUMTDOT)lensetcountintfind)inputsresult idx_removedshapes input_left input_rightcnlnrxsets keep_left keep_rightrss O/var/www/html/banglarbhumi/venv/lib/python3.13/site-packages/opt_einsum/blas.pyrr sV 6{a$J ) *!!!$k&7&7&:B FQBGaK 7Q;#ak* *+Aay+,q +:J:J1:M0NN  ;1# #FqCFFD #Q+%Ia;&J [ BayF1I aDG #$;s++ CRK- - CD [. . CRK, , i.A 3z?a#7G $s E*c ^[U5n[U5U- n[U5U- n0m[XR5H upU TU'M [X2R5H upU TU'M [U5n [R "UT5n [R "UT5n [R "UT5n X-nUHn UR U S5nM X:Xa5[R"UR5UR55nGOX*SUSU :Xa7[R"URX5URX55nGO=USU X:*S:XaJ[R"URX5RURX5R5nOX*SX:*S:Xa@[R"URX5URX5R5nOUSU USU :Xa@[R"URX5RURX55nOOSunnUH-n UURU 54- nUURU 54- nM/ [R"XUU4S9n[U4SjU55nURU:wa-[U5S:aUUlO[R"U5nX:wa[R "US-U-U5nU$)a Computes the dot product between two tensors, attempts to use np.dot and then tensordot if that fails. Parameters ---------- view_left : array_like The left hand view input_left : str Indices of the left view view_right : array_like The right hand view input_right : str Indices of the right view index_result : str The resulting indices idx_removed : set Indices removed in the contraction Returns ------- type : array The resulting BLAS operation. Notes ----- Interior function for tensor BLAS. This function will attempt to use `np.dot` by the iterating through the four possible transpose cases. If this fails all inner and matrix-vector operations will be handed off to einsum while all matrix-matrix operations will first copy the data, perform the DGEMM, and then copy the data to the required order. Examples -------- >>> a = np.random.rand(4, 4) >>> b = np.random.rand(4, 4) >>> tmp = tensor_blas(a, 'ij', b, 'jk', 'ik', set('j')) >>> np.allclose(tmp, np.dot(a, b)) N)r")axesc3.># UH nTUv M g7fNr").0rdimension_dicts r tensor_blas..sBMq*Msrz->)r zipshaper rcompute_size_by_dictreplacenpdotravelreshapeTr tensordottuplesqueezeeinsum) view_leftr view_rightr index_resultrrrisrdim_left dim_right dim_removed tensor_resultnew_viewleft_pos right_pos tensor_shaper's @rrr{sZk"KJ+-I[!K/JNJ0q1K!1!12q3" [ B++I~FH,,ZHI..{NKK,M %--a4   66)//+Z-=-=-?@ CD ["- -66)++HBJDVDVWbDno CRK- -66)++KBDDjFXFXYbFpFrFrs CD [. .66)++HBJDVDVW`DnDpDpq CRK, ,66)++KBDDjFXFXYdFpq %)A +. .H +**1-0 0I<< XyrHs) } %l^xrD