tjL%ddlZddlmZddlmZddlmZmZddlmZm Z m Z m Z ddl m Z ddlmZGd d eZejGd d Zd e jdedefdZdedefdZdZdZdS)N)Callable) dataclass)AnyProtocol)_C_opsautogradTensor)_pytree)utilsc0eZdZUedzed<edzed<dS) InfoProtocolN _backward_fn_setup_context_fn__name__ __module__ __qualname__r__annotations__U/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/torch/_library/autograd.pyrr s2T/!!!$&&&&&rrc0eZdZUedzed<edzed<dS)InfoNrrrrrrrrs2T/!!!$&&&&&rropinforeturnc djdjdj}tjj t Gddfd fd}fd}t|tj ft|t|dj}td g|j |j RDrt fd }|S) NGeneratedBackwardFor__c>eZdZUejed<eeefed<dS)$make_autograd_impl..Metadatakeysetkeyword_only_argsN) rrrrDispatchKeySetrdictstrrrrrMetadatar#s5!!!!S>)))))rr)c|d}|dd}tj5|j}|j}j|tjzg|Ri|}|cdddS#1swxYwYdS)N)r_AutoDispatchBelowAutogradr$r% redispatch_after_autograd_keyset)argsmetadatar$kwargsresultrs rforward_no_gradz+make_autograd_impl..forward_no_grad"s8CRCy  * , ,  _F/F"R]6B,E#EWWWWPVWWF                   s.A""A&)A&c|d}|dd}tj5|j}|j}j|tjzg|Ri|}jrRtjj ||\}}r||||n||||cdddS#1swxYwYdS)Nr+)ctxinputskeyword_only_inputsoutput)r5r6r8) rr,r$r%r-r.rr fill_defaults_schema) r5r/r0r$r1r2has_kwarg_only_argsrrs rforwardz#make_autograd_impl..forward,sB8CRCy  * , ,  _F/F"R]6B,E#EWWWWPVWWF% P %22:tVLL f&P**&QW+**s4*OOO/                  sBB;;B?B?cjr^ |j}|jdd|_j|g|R}||_n #||_wxYwt|trg|dRS|dfSt dd)Nr+zTrying to backward through zQ but no autograd formula was registered. Please use register_autograd to add one.)rneeds_input_grad isinstancetuple RuntimeError)r5gradsprev_needs_input_gradr2rrs rbackwardz$make_autograd_impl..backwardIs    =(+(<%'*';CRC'@$**37777'<$$'<$<<<<&%(( '&&4<  8" 8 8 8   s ); A)r<rDc3HK|]}tj|jVdSN)r is_tensorlist_like_typetype).0as r z%make_autograd_impl..dsC    %af--      rcltjrOtjr(tj|i|rt jdg|||RStjr(tj|rjg|||R}ng|||R}|S)Nzu(): functions with out=... arguments don't support automatic differentiation, but one of the arguments requires grad.)r is_outris_grad_enabled_any_requires_gradrA_opnameapply)r$r/r%r2 Generatedr)r3rs r autograd_implz)make_autograd_impl..autograd_implls <   O!## (=)*)) #z%%% #?NDN((6;L*M*MNNN N    QB$94$@ Q$Y_PdPHHV=N,O,OPPPFF$_PdPHHV=N,O,OPPPF r) _namespacerP _overloadnamer r;r:rrHr Function staticmethodany argumentsreturnssupports_tensorlist) rrnamer<rDschemarSrRr)r3r;s `` @@@@rmake_autograd_implr^sW WW WWREUWWD3BJ??*******Y*:      "  #G,,$X..  IZF   56#5fn55   3( 22 $ rclsc|j|j|jtGddfd}fd}fd}||_||_||_|S)a4Allows a given autograd.Function class to support List[Tensor] inputs/outputs. Regular autograd.Function has a constraint that it only directly supports autograd for Tensors. Applying @supports_tensorlist enables an autograd.Function to support autograd for List[Tensor] inputs and outputs. cVeZdZUejed<dZejdzed<dZedzed<dS)/supports_tensorlist..TensorListMetadata input_specN output_specresult_is_tuple) rrrr TreeSpecrrdreboolrrrTensorListMetadatarbsM$$$$/3 W%,333'++++++rrhc|d}|dd}t|stdtjt ||j}|g|R}t|t |_|js|f}tj|t\}}||_ t|drtd||_ t |S)Nr+zNYI: calling supports_tensorlist autograd.Function.forward directly. You should probably be calling .apply instead. Please file an issue if not. _pt_metadataz@Please don't set ctx._pt_metadata; PyTorch uses it to store info)r?NotImplementedErrorr tree_unflattenlistrcr@re tree_flattennot_list_of_tensorrdhasattrrArj)r5r/r0r2 flat_resultrdrh orig_forwards r new_forwardz(supports_tensorlist..new_forwards8CRCy($677 %/  %d4jj(2EFFc)D)))#-fe#<#< ' YF#*#7@R#S#S [* 3 ' ' R $[!!!rc6t|dstd|j}tjt ||j}|j} tjt |jdd|j|_|g|R}||_n #||_wxYwt|ts|f}tj |t\}}||jkrtd|d|jdt|dgzS)NrjzNYI: calling supports_tensorlist autograd.Function.backward directly. This will automatically get called by PyTorch autograd. Please file an issue if you need this.r+zRExpected the return from backward to be of the same structure as the inputs. Got: z (return from backward), z (inputs))rprkrjr rlrmrdr>rcr?r@rnnot_list_of_optional_tensorrA)r5rBr0rC grad_inputsflat_grad_inputsgrad_inputs_spec orig_backwards r new_backwardz)supports_tensorlist..new_backwardsfsN++ %9  #&tE{{H4HII!$ 4 9#*#9S)#2#.//1D$$C (-4e444K#8C #8C 8 8 8 8+u-- )&.K .5-A 4. . ** x2 2 22'722&222  %.///s AB!! B*ctj|t\}}|}g||R}|jt dtjt ||j}|jsnt|tst dt|t|dkrt dt||dS|S)N)is_leafz%metadata.output_spec must not be Nonezresult must be tuple, got r z%result tuple must have length 1, got r) r rnrordAssertionErrorrlrmrer?r@rHlen)r/ flat_argsrcr0r2rh orig_applys r new_applyz&supports_tensorlist..new_applys ' 4TCU V V V :%%j111Y1111   ' !HII I'V h6JKK' fe,, R$%P$v,,%P%PQQQ6{{a$ICKKII!9  r)r<rDrQr)r_rsrzrrhrryrrs @@@@rr[r[s;LLMJ,,,,,,,Y, """"""2*0*0*0*0*0X"CKCLCI Jrct|trdSt|trtd|DSdS)NFc3BK|]}t|t VdSrFr?r rIls rrKz%not_list_of_tensor..s/;;z!V,,,;;;;;;rTr?r@rmrXtrees rrorosM$u$<;;d;;;;;; 4rct|trdSt|trtd|DSdS)NFc3JK|]}|duot|t VdSrFrrs rrKz.not_list_of_optional_tensor..s8MM11D=>Av)>)>%>MMMMMMrTrrs rrurusN$u$NMMMMMMMM 4r) dataclassescollections.abcrrtypingrrtorchrrr r torch.utilsr r rr OpOverloadr^r[rorurrrrs{$$$$$$!!!!!! ,,,,,,,,,,,,'''''8'''  '''''''' f4?f,f8ffffRjSjSjjjjZr