tj0ddlZddlmZddlZddlmcmZdZdZ dZ dZ dZ ej dZd Zd Zd Zd Zd ZdS)N) namedtuplec4tfd}|S)Nc dr"dj}||i|SdsdrYdrdnd}|dkrdnd}|j}t d|dd|d|d |i|S) Nautogradsave_for_backwardbackwardz We found a 'z' registration for  at z but were unable to find a 'z' registration. To use the CustomOp API to register a backward formula, please provide us both a backward function and a 'save for backward' function via `impl_backward` and `impl_save_for_backward` respectively.) _has_impl _get_implfunclocation RuntimeError)argskwargskernelmissingfoundlocautograd_fallback custom_ops W/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/torch/_custom_op/autograd.pyinnerz*autograd_kernel_indirection..inners&   z * * +((449F64*6** *   2 3 3 y7J7J:7V7V '0':'::'F'FV##J ,3j+@+@''jE%%e,,5C:u::::::4;::: ! $1&111)autograd_not_implemented)rrrs` @rautograd_kernel_indirectionrs70;;2222220 Lrcfd}|S)Nctjr'tjd||frt dtj5|i|cdddS#1swxYwYdS)NcDt|tjo|jSN) isinstancetorchTensor requires_gradxs rz:autograd_not_implemented..kernel..6sjEL11Eaorz.Autograd has not been implemented for operator)r!is_grad_enabledpytreetree_anyr_C_AutoDispatchBelowAutograd)rrrs rrz(autograd_not_implemented..kernel4s  " " Qv E Ef~( (  QOPP P X 0 0 2 2 . .9d-f-- . . . . . . . . . . . . . . . . . .sA//A36A3)rrs` rrr3s#..... 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At idx z , we received an object of type za that is not a Tensor, so it cannot have be marked as differentiable in output_differentiability.)r tuplelenAssertionError enumeratezipr!r"appendlistextendrtypemark_non_differentiable)ctxoutputoutput_differentiability tuple_outputnon_differentiable_tensorsidxdifferentiableouts rr7r7?s  +&%(( ""9LL!L ' ( (C ,=,= = = 837O3P3P88$' $5$588 &("*3 (, 7 7+ +    &C&.##u|,, %;.55c:::#t$$ %;.55c::: "15M11!11CG99111  & E 'C ')C D D D D=,+: E Erc&fd}|S)Nctj|\}d  fd} fd}t jdz||}|j|}t dtjt|S)Nc|dtjt| }tj5|}dddn #1swxYwYt tjt|}t |} ||}t|||ft|| tj |\} t|S)NT)set_materialize_gradsr(tree_unflattenr4r!r*r+namedtuple_argstree_mapr6save_pytree_for_backwardr7 tree_flattenr.)r8 flat_argsrr9 args_infosave_for_backward_fn_inputsto_save flat_output op_overloadout_specr:save_for_backward_fnschemaspecs rforwardz9construct_autograd_kernel..apply..forwardrs1  % %d + + +(i$??D4466 , ,$d+ , , , , , , , , , , , , , , ,(d0K0KLLI*9&$*G*G '**+FOOG $S7I*> ? ? ? #C1I J J J%+$7$?$? !K%% %sA))A-0A-c0 tdtjt| }t |\}}t }t |ts|f}||g|R}t||t||S)Nout_spec is unexpectedly None) r0r(rDr4 unpack_savedobjectr r.validate_grad_inputs_dictgrad_inputs_dict_to_flat_tuple) r8flat_grad_outputgradssavedrJ inner_ctxgrad_inputs_dict backward_fnrrOs rrz:construct_autograd_kernel..apply..backwards$%DEEE)$/?*@*@(KKE+C00 E9IeU++ !*{9eDeDDD  &&6 9 M M M12BINN Nr _customoprU)r(rHgen_autograd_function_opnameapplyr0rDr4)rrIrSr generated_clsrMrOrRr_rrNr:rPrQs @@rrcz(construct_autograd_kernel..applyns -d33 4 & & & & & & & & & && O O O O O O O".   +Wh  *m)95   !@AA A$T+%6%6AAArr,)rQr:rrNrPr_rcs`````` rconstruct_autograd_kernelrefsL/B/B/B/B/B/B/B/B/B/Bb Lrct|tjjft |t |d}|S)N)rSr)r6r!rFunction staticmethod)namerSrrds rrarasG  "#G,,$X..  M rcd|jjD}t|jdz}t ||}|S)Ncg|] }|j Sr,)ri.0args r z'namedtuple_args_cls..s===Csx===r_args) argumentsflat_allstrrir)rQattribsri tuple_clss rnamedtuple_args_clsrvsD==6#3#<===G v{  g %D4))I rct|tstdt|t |}||S)Nzexpected tuple, got )r r.r0r6rv)rQrrus rrErEsL dE " "B@DJJ@@AAA#F++I 9d rc fd}t|ts|dt|djjjD}|}||kr|d|d|d|D]\}}t||}t|tr t|ttfs|d|dt|d t|t|kr.|d|d t|d t|tt||D]w\} \} } |  t| tjs!|d|d t| d | t!| tjs|d|d| d| d|xL|Pt|tjs|dt|d|dt!|tjs|d|d|d|ddS)Nchd}tdd|jd|)Nrz%In the backward function defined for r z using the CustomOp API, )r rr )whatr forward_ops rerrorz(validate_grad_inputs_dict..errors]'' 33 BJ B B  B B;? B B   rzBexpected the output of the backward function to be a dict but got cNh|]"}|j|j#Sr,)r6is_tensor_likerirls r z,validate_grad_inputs_dict..s>  8 " " $ $ rz3expected the returned grad_input dict to have keys z but got z. The backward function must return a gradient (can be None) for each arg to the CustomOp that may be a Tensor or Sequence[Tensor]. Args declared to be non-Tensor-like types should not appear in the grad_input dictz for input 'zR' expected the grad_input dict to hold a list of gradients but got object of type .z1' expected the grad_input dict to hold a list of z gradients but got z\' expected the grad_input dict to hold a list of None or Tensor gradients but got object of z at index z(', got a Tensor as the gradient for the z(-th value but expected None because the z(-th value was not a Tensor (it was type zgot object of type z as the gradient for input 'z:', but expected the gradient to be either None or a Tensorz(got a Tensor as the gradient for input 'z3' but expected None as the gradient because input 'z ' was not a Tensor (it was type z).)r dictr6_schemarqrrkeysitemsgetattrr4r.r/r1r2r!r" issubclass) r^r{rJr| expected_keys actual_keysrigradarg_infor=ginfos ` rrXrXs      & - -   ,()) , ,   %/8M #''))K ##  & & &'2 & & &   ',,..// d9d++ h % % dUDM22 %$%%Dzz%%% 4yyCMM))#$##&)(mm##4yy## #,Ch,?,?"@"@  Ya9!!U\22E>d>>%)!WW>>8;>> "$ 55E+d++#&++"++!)++  < $ --  EKd4jjKKKKK    (EL11  E>4>>@D>>19>>>   W//rc2g}|D]N\}}||vr*|tjd|3|||Ot tj|S)NcdSrr,r$s rr&z0grad_inputs_dict_to_flat_tuple..sDr)_asdictrr3r(rFr. tree_leaves)r^rJresultrirs rrYrYs F#++--3355..h ' ' ' MM&/..(CC D D D  &t,---- #F++ , ,,rc@tj|\}}t|}dt|D}dt|D}d|D}d|D}||_||_|j|||_||_||_ dS)NcLg|]!\}}t|tj|"Sr,r r!r"rmr=things rroz,save_pytree_for_backward..s=Uz%7V7V rcLg|]!\}}t|tj|"Sr,rrs rroz,save_pytree_for_backward.."s> C%.. rcFg|]}t|tj|Sr,rrmrs rroz,save_pytree_for_backward..'s)PPP 5%,0O0OPuPPPrcFg|]}t|tj|Sr,rrs rroz,save_pytree_for_backward..(s)XXXU 5%,8W8WX5XXXr) r(rHr/r1rRnum_eltsr tensor_idxssaved_non_tensorsnon_tensor_idxs) r8stuff flat_stuffrRrrrtensors non_tensorss rrGrGs*511J:H' 33K#J//O QP*PPPGXXjXXXKCHCLC7##!CO'C)Crcdg|jz}t|j|jD] \}}|||< t|j|jD] \}}|||< t j||j}|Sr) rr2 saved_tensorsrrrr(rDrR)r8rtensorr= non_tensorrs rrVrV3s#,&J3,co>>!!  3s4c6IJJ%% C$ 3  !*ch 7 7E Lr) functools collectionsrr!torch.utils._pytreeutils_pytreer(rrr7rera lru_cachervrErXrYrGrVr,rrrs"""""" $$$$$$$$$@   $E$E$EN999x    MMM`---***.r