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Also return the fake mode used to fakify those inputs. placeholderval example_value_dynamo_bytecode_flattenNrc>TRU5 [U[R5(aUnO [ 5n[ U5T;aTT[ U5'TS- mU$NrK)rrr{Tensorobjectid)rret fake_inpsidx positionss rs mark_inputs)_extract_fake_inputs..mark_inputs,sX   Q !U\\**h#wi'%( "S'" 1HCJrr)opz7Detected shape env does not match fake mode's shape envT)rexportcj>[U[[R45(aTTOUnTS- mU$r)rintr{r)rrcountrs rs lookup_fake)_extract_fake_inputs..lookup_fakeWs2",Qell0C"D"Di!   rr)rrrrrgetgetattrrtree_maptuplevalueszip find_nodesrr/rrrr4rG)rwrr fake_valsrdynamo_bytecode_flattenr dummy_args shuffled_args shuffled_argdetected_fake_modedetected_shape_envrr fake_args fake_kwargsrrrrs @@@@rs_extract_fake_inputsrs II 77m #   TYY]]51 2   TYY]]?; <  #*".H$"OOO   __[v}}9O2OP /< "% HH  =  1=# D,9,9=u9M )B|$456 # *)i*?@))i*?@ !)E)EE$M' "-?M "XZE E  2I//+6K 9 ,,rrc\URHFnUR[R[R4;dM3XR UlMH UR HFnUR[R[R4;dM3XR UlMH gr) input_specsrrN PARAMETERBUFFERr output_specsr>BUFFER_MUTATIONGRADIENT_TO_PARAMETER)param_buffer_tablerxspecs rs_replace_param_buffer_namesr cs 99        -[[9DK     99  & &  , ,  -[[9DK !rrc [U5[U5[U5-:wa0[S[U5S[U5S[U5S35eU[U5SVs/sHo2UPM nn/UQUQ7$s snf)Nz,Total number of arg names is expected to be z but got z positional args, z kwargs.)rr)orig_arg_namesrrkw_namereordered_kwargss rs_convert_to_positional_argsrrs >c$i#f+55:3~;N:OP4yk!3CK= J  8Fc$ik7RS7RGw7RS     Ts%A<c Sn[R"SSU5nUR5GHn[U[R R 5(dM/URRGHGnURS;aMSnURRS05=n(a[[UR555up[R "U 5(a5[#U [R$R&5(a X:XaXLaSnO,[U [(5(d[+S[-U 535eU(dMS n X2UR.S -UR0-40UEnUR35V VV s0sHun upX"U5U 4_M sn nn URS'GMJ GM gs sn nn f) N L['self']z [^a-zA-Z0-9]_routputTnn_module_stackFzexpected ty to be str, got c\US:XagURS5(aU[S5S$U$)Nrz L['self'].)rr)rs rsnormalize_path2_normalize_nn_module_stack..normalize_paths4{*!|44#C $5$788Krrr)resubmodulesrr{r|r}rrrrrnextiterrinspectisclass issubclassnnModulerprtypergrhitems) gm_torch_levelroot_clsrootroot_keyrwradd_rootrrtyrkeys rs_normalize_nn_module_stackr-s DvvosD1H$$&"ehh2233 HHNNDww33H"&))--0A2"FFF_%;%;%= >???2&&:b%((//+J+J|#(%b#..,/J4PR8*-UVVx X%8%83%>AVAV%VW#&#,;+@+@+B0+BZd..33+B0 +,;#'@0s G original_module traced_modulereturnc0n0nURSS9H/upEUR[U55bM"XB[U5'M1 URSS9HupFXC[U5'M 0nURSS9H;upX;a[ SU<S35e[U 5U;dM+U[U 5Xx'M= URSS9H;upX;a[ SU<S35e[U 5U;dM+U[U 5Xx'M= U$)z Returns a mapping of parameter/buffer names from the new module to the original model. This is to help with restoring the FQN for parameter/buffers of a traced module to what the original module contains. Fremove_duplicatez dynamo_name z% already exists in param_buffer_tablez0 already exists in param_buffer_table for buffer)named_parametersrr named_buffersr) r.r/ param_lookup buffer_lookuprparambufferr dynamo_name dynamo_param dynamo_buffers rs_get_param_buffer_mappingr=sO$&L$&M&777O    BuI & .&*E #P(55u5M $(bj!N*,%2%C%C&D&!   , {o-RS  l | +.:2l;K.L  +&'4&A&A'B'"   , {o-]^  m  -.;B}ryr?r placeholdersrr fake_argconstants rs_preserve_requires_grad_passrKsX&(XX^^P^Tww-7OD^LP 3??s<00!#coo"6!77[\_`l\m[n o   A,8  99        {{"$6L6L5MOP 2YY9//A A  + +I9 Qs KKorig_constant_attrsgraph_signaturec0nUR5HupEXP;dM XX4'M URHnUR[R[R 4;dM3UR nUc[SUR35eURXw/5nUSUlX'n X' UHn XU 'M M g)zXRewrite the graph signature and constants table to use the FQN from the original module.NrAr) r%rrrNrDrFrrr) rLrMry remap_tablervaluer  orig_targettargetsrJrs rs_remap_constantsrSs )+K (   ' 3 :K ) ++ 99  % %    ++K"$+B// 8 ,,,F #4d6I6I"J K  66 6 ,  )4099==' 'C 4!A#- "   .?II) * s'C. C.+C.)_prettify_placeholder_namesc n[R"XV45n [X5up[U5 [ UR 5[ UR 5-[ UR5-n [X U 5 [X0[U55n [X U5n U(a SSK J n SSKJn U"X 5up U "X 5up UR!5Hn[#U[$R&R(5(dM.UR*R,HMnUR.S;dMUR0R3SS5 UR0R3SS5 MO M U c [5S5eU(a[7UU UUUUU 5 [9X X|U 5 [;UU U UR<S 9$) a This is a helper function that is shared between export_to_aten_ir and export_to_aten_ir_make_fx to produce the aten artifact. (export compatible graph module + signature) It does: 1. Applies runtime assertion pass 2. Recompute unbacked_bindings pass 3. Populate meta val when missing 4. Lift constants as placeholders 5. Replace raw autograd and autocast ops with HOPs 6. Prettify names for placeholders 7. Preserve requires_grad value on node meta val r)replace_autocast_with_hop_pass)replace_set_grad_with_hop_passrrN stack_tracez'export_graph_signature must not be None)rz)r tree_leavesr!rfr parametersbuffers input_tokensset_missing_meta_valsrQ_get_non_persistent_buffersr3torch._export.passes.replace_autocast_with_hop_passri3torch._export.passes.replace_set_grad_with_hop_passrjrrr{r|r}rrrrrcrr"rKrur)rwmodconstant_attrsrM pre_dispatchrrr>rgr?total_non_user_inputsexport_graph_signatureryrirj_modrs rs_produce_aten_artifactrzNs6''(@AN6rKB r" O & &' o%% & ' o** + , ".CD@8= 0 NI  &D & "&D & "  $ 4 455 JJ$$Dww33 /6 mT2%%FGG"  "      ! $7N  )22  rrc^ URRVs1sHo"RiM snm U 4Sjn[[R n[[R n0nURHnUR[R :XdM#URRRU5(aMOURRRU5(a+U"XWRR[U5S-5nOU"XWRR-5nXURR'XRlM URHFnURRU;dMXgRRURlMH UR5Hn [U [R R"5(dM.U RRH/nURU;dMXbR=UlUlM1 U R'5 M gs snf)zT For strict mode, rename constants nodes that were previously annotated as buffers. c>UT;a%SnUSU3=nT;aUS- nUSU3=nT;aMUnTRU5 U$)NrKr)add)rndup_name node_namess rsrename_constant0_rename_constants_nodes..rename_constantsa : A"&q},8;Q#'q},8;Dt rrN)rrrr#rNrrDrrargrrrrrr{r|r}r recompile) rwrMrr buffer_prefix const_prefixbuffer_to_constantr c_namertrs @rs_rename_constants_nodesrs)+7))7J))9)9:M' (A(ABL++ 99 11 1$((--:R:R ; ; xx}}'' 66( 88==]1C1E#FF) )EF06txx}} -"HHM, ,, 88==. ..xx}}=DHHM- zz|#uxx3344 IIOODyy..*%_export_to_torch_ir..bs7 :: L4G4G!G%% rrrar0c@>[T=(d T=(d [T[RR5=(dX T=(dO [R R R=(d$ [RR R5$r) rkrr{r|r}rr"fake_tensor_propagate_real_tensors_exportuse_legacy_dynamo_graph_capture) constraintsrrrsrsr<_export_to_torch_ir..use_legacy_dynamo_graph_capturemsy  D D!UXX112 D. D&&II  D }}##CC   rrr) _dynamo_graph_capture_for_exportdynamo_graph_capture_for_export)rrF)rbrTsymbolic)rrr] tracing_moderrarrrNz5Consider annotating your code using torch._check*(). constrain_as_size_example) case_name)-r6rrr r INVALID_INPUTr$r tree_map_onlyrr<r:r9r=rmreplaceDEFAULT_EXPORT_DYNAMO_CONFIGrkr{_dynamorpatchasdictrrr|r}r%rruse_new_tracer_experimentaltorch._dynamo.functional_exportrrrrrDrJCONSTRAINT_VIOLATIONrprF ANTI_PATTERNr"r#r)rrrrrrrarrr combined_args dynamo_cfgrrctxrrdynamo_graph_capturer&rers` `` @rsrr6s$3,&:4%J6%JN '++K8). (<(<'5$/15%/2KDo*;'5)= ) )! )%NA@QN''(;>AG G* **GAxP5  o D Cst+L6-A K 9 J8C J'J8K ' J5 1J88 K K L6K  L3#K<< L3 %L..L33L66 M)_record_nn_module_stackcSSKJn SSKJn [ UUUUUUS9n U"U R U R 5up[U [RR5(d[S[U 535eU"U U U RU R[R "X#45[#UR%55U R&U R(SSSS9 n X4$)Nr)aot_stage2_export)create_graph_signature)rdecompositionsrz,expected gm to be torch.fx.GraphModule, got F)user_args_flatparams_and_buffers_flat param_names buffer_names trace_jointnum_user_fw_outs loss_index),torch._functorch._aot_autograd.graph_compiler4torch._functorch._aot_autograd.input_output_analysisrr. _aot_state_aot_graph_capturerr{r|r}rr$rrrrlrr params_spec buffers_spec) rrtrrrr>rrrjoint_with_descriptorsrw fw_metadatarMs rs"_aot_export_joint_with_descriptorsrsO?   % 7 ())11OB b%((.. / /KDQSH:VWW- &&''))4.9 $%8%?%?%A B*66+88 O  rrcU$rrers rsrrrr) transformrv decomp_tablergrrurgrc U (a[O[n [5n U R[R R RRUUSSSS95 U R[55 U R[55 U RU "55 U R[R"55 U"[5"U UUUUUSS9upSSS5 SnU"UW 5 U(a U"U 5 ['U UUWUUUUU S9 $!,(df  N;=f![[4a(n[[ R"[%U55eSnAff=f)NT tie_weightsstrict stack_weights)rrr>rc`[U[RR5(Ga[ US5(a%UR R UR 5 [URR5Sn[URR5SnURS:wdURS:wa'[SUR<SUR<35eSUR ;a UR S UR R UR 5 gg)Nrrrz8expected both output nodes to have op='output', got old=z, new=desc) rr{r|r}hasattrrupdaterrrrr)old_gmnew_gmold_output_nodenew_output_nodes rs$_maybe_fixup_gm_and_output_node_meta@_export_to_aten_ir.._maybe_fixup_gm_and_output_node_metas fehh22 3 3vv&& ""6;;/"6<<#5#56r:O"6<<#5#56r:O!!X-1C1Cx1O$NOaOaNddjkzk}k}kAB---#((0  ' '(<(< = 4rr) rwrtrurMrvrrr>rg)rrr enter_contextr{r"utils stateless_reparametrize_modulerrno_gradrrDrJr rrrprz)rtrrr>ruproduce_guards_callbackrrvrrgr#custom_triton_ops_decomposition_ctxrrwrMrrs rs_export_to_aten_irrs[ '  ?(   HHNN $ $ : :# " ;   356 467 ?AB EMMO,'(JK   ' 3$(  2 >$)b1 H #B ' " %'!/$?  s l)/: HM>>AG G Hs$C DD- D*-E%=#E  E%c 4[R"UR5nUR"U6Rn/nUR 5HupgUR UR[RR:Xa6UR[U5VV s/sH upUSU3PM sn n5 MpURU5 M U(a4URUR 5V V s/sHupU PM sn n 5 U$s sn nfs sn n f)a Gets the argument names to forward that are used, for restoring the original signature when unlifting the exported program module. - Positional args: retain the original argument names, and enumerate *args as args_0, args_1, ... - Keyword args: retain the original kwarg names in the order specified by the user. This order seems to matter for the current state of export lifted modules. r) rrforward bind_partial argumentsr%rmr_ParameterKindVAR_POSITIONALextendrr) rtrrrx_argsnamesrrPrrkwargs rs_get_forward_arg_namesrHs   CKK (C   d # - -EE{{}  >>$  $ $(>(>(M(M M LLIe4DE4DDATF!A3-4DE F LL  % FLLN;NeN;< LF # UH nTSU3v M g7f)rNre).0brs rs ._get_non_persistent_buffers..nsO1NATF!A3-1Ns)rorr_non_persistent_buffers_set)rtresultrrs @rsrqrqgs\uF$$e$<a  MMO1N1NO O MM!77 8 = Mrrorig_mod_bufferstraced_mod_buffersc URHsnUR[R:XdM#URc [ S5eXRnXP;dMP[R UlXSUR'Mu g)zh Dynamo erroneously marks tensor attributes on modules as buffers. Rewrite them to be tensor constants. Nz,spec.target must not be None for BUFFER kind)rrrNrrrrD)rrrMryr rPs rs _rewrite_dynamo_tensor_constantsrtsi ++ 99 (( ({{"$%STT&{{3E,&55 ).$++&,rrorig_modcbURHnUR[R:XdM#UR(aM6UR c [ S5eUR U;a[ SUR <S35eURUR 5X#R 'M g)z3 Moves non-persistent buffers to tensor constants. Nz;spec.target must not be None for non-persistent BUFFER kindz spec.target z# should not already be in constants)rrrNr persistentrr get_buffer)rrMryr s rs0_move_non_persistent_buffers_to_tensor_constantsr"s ++ 99 (( ({{"$Q{{i'$"4;;/1TU&.%8%8%EIkk ",rrrc [U/[UR55-5GH6up[U[R R 5(dM1URRHnURS;aUS:XaURRSS5=nc[SUSURS35e[SUR555(d[SUSURS U35eMMURS ;dMURRSS5(dM[SUSURS 35e GM9 g) af Perform nn_module_stack checks on the graph. Current constraints: For the top level graph: - populated for 'call_function', 'get_attr' - None for 'placeholder', 'output' For submodule graphs: - None for 'placeholder', output' TODO(pianpwk): make this a consistent node-level check once nn_module_stack is populated for cond submodules. rrrrNNode of type z$ is missing nn_module_stack metadatac3# UH\up[U[5=(a> [U[5=(a' [U5S:H=(a [ SU55v M^ g7f)c3B# UHn[U[5v M g7fr)rrp)rrs rsr4_verify_nn_module_stack...s>Aq 1c 2 2AsN)rrprrall)rrrs rsr*_verify_nn_module_stack..s] %A>>?% rzPlaceholder node name z does not follow spec for z, name should have prefix: N)rrrrrrr{r|r}rrrr#rr$)rwrxr  name_to_kindrtr node_kindprefixs rs_verify_placeholder_namesr4s:=IHHMM499,LIzz|#uxx3344 IIOODww-'99L0(3 -i8yy++F33,0 ;UV_U``{}C|DE$Js*DepcrSn[5nURR5GH n[U[R R 5(dM/URRHnURS:waMUS- n[URS5(d[SURS35e[URS5(d[SURS35eURURRS URR35 M GM XS .$) NrrrKrgz node.target z must have __module__ attributerfz must have __name__ attributer)op_countop_set)rorrrr{r|r}rrrrrrr}rgrf)r5r7r8rrs rs get_ep_statsr9sH UF __ $ $ &!UXX1122 GGMMDww/) MH4;; 55$"4;;-/NO4;; 33$"4;;-/LM JJ$++0014;;3G3G2HI J"' ! 33rr _EXPORT_FLAGSrcF^[R"T5U4Sj5nU$)Nc`>[R"5nT "U0UD6n[R"5n[S SXB- [S.[U5D6 SqSqU$![an[ U5nUR S-UR-n[U5nUb8[R[U55 [SU[U5[S9 O[SU[U5[S9 [US5(a"[UR[ R"S9 UeSnAff=f!SqSqf=f) Nz export.time)rmetricsrrzexport.error.classified)rr$messagerzexport.error.unclassifiedpartial_fx_graph)filere)timer6r:r9 Exceptionr$rgrhrlogerrorrrprprintr?sysstderrr) rrstartr5endrt error_typerfns rswrapper$_log_export_wrapper..wrappers*' ,IIKET$V$B))+C  # # r"  D!M'+ $ ? QA+annELL$#788 ((*#!  //rrc[URSS95n[URSS95nX-n[U5nUHnUR US5 M U$r)r~r4r5rqrc)rtr4r5original_state_dictnon_persistent_buffersrs rs_get_original_state_dictrY[skC00%0HI**E*BCM*:8= #4($ rrc [U[5(d&[[RS[ U535eUbUO0n[ R"U5(a [U5n[ R"X45upE[U[RR5(aURnURXU5nOASn[U[RR5(aURXU5nOUnXXWU4$)a Process and validate export inputs for the torch.export API. This function validates the input arguments, normalizes kwargs, computes input tree specs, and handles special dynamic shapes cases like AdditionalInputs and ShapesCollection. Args: mod: The PyTorch module to be exported. args: Tuple of example positional inputs for the module. kwargs: Optional dictionary of example keyword inputs. dynamic_shapes: Optional specification for dynamic shapes. Can be: - dict mapping argument names to dynamic shape specifications - tuple/list specifying dynamic shapes for each input in order - torch.export.AdditionalInputs object with verification callback - torch.export.ShapesCollection object Returns: A tuple containing: - args: Validated tuple of positional inputs - kwargs: Normalized dictionary of keyword inputs (empty dict if None was passed) - original_in_spec: TreeSpec representing the flattened input structure - dynamic_shapes: Processed dynamic shapes specification - verify_additional_inputs: Callback function for additional input verification Raises: UserError: If args is not a tuple. rcgrrer5s rsr(_process_export_inputs..sdrr)rrr rrr$ris_namedtuple_instance tree_flattenr{rAdditionalInputsverifyrShapesCollection)rtrrrroriginal_in_specverify_additional_inputsout_dynamic_shapess rs_process_export_inputsrfisT dE " "  ' 'OPTUYPZ| \  )VrF $$T**T{ --tn=A.%,,"?"?@@#1#8#8 +::3fM#2 nell&C&C D D!/!>!>s&!Q !/  )?W WWrrexport_artifactstrict_mode_exportc URRnURRnURnURnUR n0n UR 5H.upU(d [U 5OU n [//U SU SSS9X'M0 [U5S:a=U(d [U5 [X5"U5n U c [S5eU Rn[c [S5e[UUU U5nXN4$)zt In-place modify the graph module in export_artifact, remove _export_tracepoint nodes and return module_call_graph. rrNrrz$CollectTracepointsPass returned Nonez)_EXPORT_MODULE_HIERARCHY must not be None)rrwrxrrrr%rrPrrrrrrr)rgrrhrrwrxrrrrrspecsmod_fqnresmodule_call_graphs rs_get_module_call_graphrns /3366B3B3G3G3K3K))(//G(11H>@'--/ *<+c"#*=)$:&" + '0 )*Q.! $R ($%;TUWX ; !GH H   'HII/    rrcpURRnURRnURn[ S[ UR 55[UR 55n[XU5n 0n U Hn X;dM XX'M UH n X<X'M U n [UUU UU5n U $)Nc3j# UH)upUR[R:XdM%Uv M+ g7fr)rrNrC)rrss rsr)_get_range_constraints..s- Evv--- AEs$3 3) rrwrxrrrrrr:r)rtrgrrrrwrxr num_liftedrcombined_args_traced_orderrr,range_constraintss rs_get_range_constraintsrvs /3366B3B3G3G3K3K / 9 9I !"8"D"DE " . ./ J"#V4M "$  .;.@ & +*0+"'/M(   rrrcURc [S5eURRR5VVs0sHup[ U5(dMX_M snn$s snnf)Nz$fake_mode.shape_env must not be None)rrr_r%rE)rrrs rs_get_inline_constraintsrx sd"CDD''44::<   --n=--n=s>B A% B %!BB  orig_in_spec _to_aten_funcc v [UUUUUSUSS9n[XU5un n n [X5n URRHn U R S:XdMSU R ;dM'[XR5n[U[RR5(aMgU c [S5eU RUSS9U R S'M Sn[URR[R RR"5(aURRR$R&=nnURRR$R(nUc [S 5eUR*[,[.4;a[0R2"U/5nSn[5UUR6U5URRlO[URR[R8R:R<5(aAURRR>nS=nnS=oRRl O"[CS URR35eURE5 [GU[+U55 [IU5n[KU5n[MX5n[OU5nURQ5VVs0sH unnUU_M nnnUVs1sHnUU;dM UUiM snUl)[UU 5nU  [WU5 [XRZR]U S S5 U"U[_UX50U U5nSSS5 SSS5 SSS5 WR`nURbnURdn[gUUU5 [i[kURm55[oURq55UUS 9 [sUU5 [uUUU5 [wUUU5 [yUU5 Uc'URznU(aUR}5S nOUn[UUUU UR SS9$s snnfs snf!,(df  GN =f!,(df  GN=f!,(df  GN!=f)R _to_aten_func can either be `_export_to_aten_ir_make_fx` or `_export_to_aten_ir` F)rrrarrrNzbCannot find dynamo_fake_mode. This could be due to the exported graph module have no placeholders.T) static_shapesout_spec must not be NonezUnknown codegen type: allow_non_fake_inputs)rrrMryrrrrrrr)@rrrrrrrrrrr{r"r#r from_tensor_codegenr|_PyTreeCodeGen pytree_infor orig_argsr$rrrtreespec_tuplerH_in_specrfunctional_export_DynamoBytecodeCodeGenr  wrap_tuple RuntimeErrorrr-rrr=rqr%rr1r0r rrrrwrxryrrrornr~r5r r"rSrrzchildrenr) rtrrrrrrarr&rrdynamo_fake_moder>rattrrr orig_out_specr params_buffers_to_node_metarurrXtracedorigreverse_name_lookuprtxaten_export_artifactrwrxrys rs_strict_exportr0sX)  'E4_ N" ^6: 11AR $$** 77j U$))%;>;;7DdEHHOO44#+(|$4#?#?$@$ % +J.&&//1N1NOO#1#7#7#@#@#L#L#U#UU='--66BBLL   !<= = ==u -,,hZ8HJ4?   # # 5 %%1 %% ''>>   (--66EE#''=@DD ))22=3N4H4H4Q4Q3RSTT~tCy9"@"P,C0N)B3)W 9=?.  24JK5 #Y ^%;YGB 67'99 ((*1-H   !"(--.AB  yX2 KJ   sN7Q: R R: R)"R(R?RR) R R R& !R)) R8cU$rrers rsrrrrrc Sn[5nUR[RRR R UUSSSS95 UR[55 UR[55 U"U5"UUUSUS9upU RRHQn U RS:XdM[U R5S:XdM0SU R;dMBSU RS'MS [U[R R"5(a6[%US 5(a%U RR'UR5 SSS5 U(a U"W 5 [5W UUW SUUUS 9$!,(df  N.=f![([*4a(n [-[.R0[3U 55eSn A ff=f) Nc^&^'U=(d 0n[URSS95n[URSS95n0UEUEn[R"U5up[ U5n[ U5n [ U5n [ U5n [XU SS9n /nURU5 URU5 [XU5um'n[R"X45unn[R"T'5U'4Sj5n[5 [5n[USS5nUb[U5n0n[!UU5nSm&["U&4Sj5n["S 5nU U"U5 U"5 [%USSS 9"U6nSSS5 SSS5 SSS5 UGb9['W5n[)UR*R-55VVVs0sHununnUcMUUU U-_M nnnn[/UR0R25S nWR-5Hunn[5UUU5n [5UU5n!UR0R7U5 UR0R9S [:R<R>R@RBU U!4S 9n"U!RDU"l"SSS5 M WRG5 Sn#WR0RIU#5 SSS5 URJc [MS5e['W5n[OU5n$[Q[/U5[/U5UU SU$[[SUSU U55[[SUXU -U55000UURJS//S9n%UU%4$!,(df  GN=f!,(df  GN!=f!,(df  GN+=fs snnnf!,(df  GM=f!,(df  N=f)NFr2T)store_orig_modc >[T"U65$r)r)rflat_fns rs wrapped_fnG_export_to_aten_ir_make_fx.._make_fx_helper..wrapped_fns$( (rrrcU"X5nX;a[RR5(a[U[R5(a[R R 5nUHn[U[5(dMURn[X5RnURS[RRRRX405n [!XISUS9 M U$)z The idea here is that we override subclass getattr methods to proxy inner tensors and metadata. Because of infinite loop shenanigans, we have to manually construct the getattr proxy nodes without relying on torch function system. rN)rJtracer)r{r_is_torch_function_mode_enabledrr overrides _get_current_function_mode_stackrBrr@proxy create_proxyrraccess_subclass_inner_tensordefaultrC) selfroriginal_getattrattrs_to_proxyouttorch_function_mode_stackmoderr inner_proxys rscustom_getattributeP_export_to_aten_ir_make_fx.._make_fx_helper..custom_getattributes't2)xx??AA%c5<<88!& P P R6)B#-d4P#Q#Q-1[[F,:4,H,N,NE282E2E(7(- (8(8(U(U(](]). (* 3&K %6(+4PV%&)B rrc3D># 0nUHn[U5nUHxnXA;dM [X45S:Xa[SUS35eX4Sn[[ U55[[ [ R 55- nURU4X'Mz M UR5H%ununn[R"T UUS9n XlM' Sv UR5HunupXlM g!UR5HunupXlM f=f7f)z~ Context manager that temporarily monkey patches tensor.__getattribute__ so that we can intercept it at torch_function layer. rzsubclass_types_to_instances[z] must not be empty)rrN) r*rrrodirr{r__getattribute__r%rO partialmethod) rtensor_type_to_old_getattributersubclass_types_to_instances subclass_typeinstancerr old_getattrcustomrrs rs$override_getattribute_for_subclassesa_export_to_aten_ir_make_fx.._make_fx_helper..override_getattribute_for_subclasses5sK0 C6c:0*E (O"#>#MNRSS&4&B=/Qd$e'"!"(C'QRS'TH-0X-?#c%,,FWBX-XN - > > .N;J*E  $99>>@#&!*!8!8/-8+9" .4* A/N/T/T/V++K-8*0W/N/T/T/V++K-8*0Ws#D A6D =C9#D 9$DD c3# [R"5nSv [RRU5 g![RRU5 f=f7f)z When pre-dispatch export accidentally change grad state, we restore it back. This can happen when we are calling torch._C._set_grad_enabled directly in the forward. N)r{is_grad_enabledr_set_grad_enabled) old_states rs_maybe_restore_grad_stateV_export_to_aten_ir_make_fx.._make_fx_helper.._maybe_restore_grad_statedsA"113 :HH..y9EHH..y9sA!= A!!AA!)record_module_stackrvrr)rcURS:XaUR[RRR R [RRRR [RRRR[RRRR [RRRR 4;agg)NrFT)rrr{rprofiler_record_function_enterr_record_function_enter_new_record_function_exit_RecordFunctionrdetachrr)rs rs _is_impureG_export_to_aten_ir_make_fx.._make_fx_helper.._is_impures77o-$++ II&&==EEII&&AAIIII&&<<LLIINN))11II$$AAIIB3!rrzout_spec.spec is None!r)rmrn user_inputs user_outputsinputs_to_parametersinputs_to_buffersbuffers_to_mutateparameters_to_mutateuser_inputs_to_mutaterrbackward_signaturero output_tokens)*r~r4r5rr_rrr&r r+rOrPr rrr-r,rrAr'r_buffersr%rrr _find_noderrr{rrcopy_rrremoveeliminate_dead_coder rr(r)r)(rrtrrrr4r5params_and_buffersrr param_len buffer_len params_lenfunctional_callparams_buffers_argsr flat_argsrrrnon_strict_rootassigned_buffershookrrrw input_namesrrbufbuffer_input_names output_nodebuf_node name_noderr output_namesrxrrs( @@rs_make_fx_helper3_export_to_aten_ir_make_fx.._make_fx_helpers2 4 4e 4 LMS...FG B 0BMB/5/B/BCU/V,"'(?"@() ' +, 0 j *,""#:;""4(4 & $002E1NO 7  ! ) " )& '-C%c>4@O*2?C46 6#%5" H, 9, 9\ : :4Y?)+(,!% ,@*04 +4O4L4L4R4R4T*U&*U;D#5D+i!m44*U#& #288>>226 !1!7!7!9IC)".@.EFH *2t 4I22;?#%88#7#7+!IINN0088"*I!6$8$ )2 @?":  & HH ( ( 4C(H ==  !9: :(, *2. ,-'#JK0%!%c+a *BDT&U!V"K ,BC]S!!#"$]]#' *3w[,+@?&@?I( 's AO N1&N.N =NN1 >O O  O )A2OAO 6:O N N N. )N11 O ;O O  O O+TrF)rrrrrr)rwrtrurMrvrrr>)rrr{r"rrrrrrrrrusersrrr|r}rrrDrJr rrrprz) rtrrr>rurrrrrwrMrrs rs_export_to_aten_ir_make_fxrs\B   HHNN $ $ : :# " ;   356 467'8     HHNND?* Oq(*#' % # c588// 0 0WS&5I5I GGNN388 $I N H #B ' " %'/  [ T)/: HM>>AG G Hs7B0F F F /A2F 1F FG*#G  GcSnURRHSnURS:XdMX2:a4XU- n[U[R 5(dXTR S'US- nMU g)NrrrrK)rrrrr{rr)rwrnum_params_buffersindexruser_args rsrprpsa E 77m #*$-?%?@!(ELL99'/IIe$ QJE rrch^[[U4SjURR555$)Nc3J># UHoRT:XdMUv M g7fr)r)rrrs rsr_find_node..sJnd T8ITTns# #)rrrr)rwrs `rsrrs! JbhhnnJJ KKrrc"^^^^^^^^SmSm0mUUUU4Sjn[RRR(a [ 5O [ 5n U  [ UUUTUS9umn n mmm[TU5n SSS5 UUUU4Sjn [T5n[R"[5nSUS'T [5 [U5 [RRRU5 [!UW W T5unnnnn[#XT5 [%5 U"UUUW UU US9nUR&R)5VVs0sH#unnU[+U[,5(aUUOU_M% snnUlSSS5 SSS5 SSS5 SSS5 SSS5 SSS5 SSS5 [/UWR0UR&5 Tc [3S5eTc [3S 5e[5UTTTTS 9$!,(df  GN=fs snnf!,(df  N=f!,(df  N=f!,(df  N=f!,(df  N=f!,(df  N=f!,(df  N=f!,(df  N=f) rNc&>^SS.UUUUU4SjjnU$)N)rc>U=(d 0n"UU4SjS[RR5nU"U5nTVs/sHnSU-PM nn[5n [ U[R R 5(d [XhT5n U  T"XU4SU0UD6upSSS5 [RSW 5 [R"[W R5U l [R"[U R5U l[R"[U R5U l[R"[U R 5U l[R"[U R"5U l[R"[U R$5U lU R&R(Hyn SU R*;dMU R*Sn [R"[U 5R-5VVs0sHup[/U5U_M snnU R*S'M{ X4$s snf!,(df  GN=fs snnf)Nc8>^\rSrSrU4SjrUU4SjrSrU=r$)]_non_strict_export.._tuplify_outputs.._aot_export_non_strict..Wrapperi+c.>[TU]5 Xlgr)super__init__r)rrtr|s rsr f_non_strict_export.._tuplify_outputs.._aot_export_non_strict..Wrapper.__init__,sG$&(+%rrc^>URn[R"X45unm[U[R R 5(a[URR5;a [X1U5 [R RR5 /UQUR5Q7n[R RU5R"U6nSSS5 OU"U0UD6n[R"W5unm[U5$!,(df  N2=fr)rrr_rr{r|r}r8_forward_pre_hooksr tracebackpreserve_node_meta Interpreterrunr) rrrrtrtree_out flat_outsrrs rsre_non_strict_export.._tuplify_outputs.._aot_export_non_strict..Wrapper.forward0s++C!'!4!4d^!DJAw!#uxx';';<<>"55<<>?>cP"XX//BBD#._tuplify_outputs.._aot_export_non_strict(s\rF , ,%((// ,:"#,K.L--K!#-K *--Cc588#7#788&@Q$UVfVPUV II> C#__[#..ICN //+s{{CCK$*OOKAVAV$WC !'-S55(C $%+OOKAVAV$WC !'-S55(C $$ 1&*ii0A&BO)/')%')"4)"HC#3,)"4DII/0'7NC-$4sII!I( I%re)rrrrrrs` rs_tuplify_outputs,_non_strict_export.._tuplify_outputs's?CD D L&%rrrc>[TUTTTS9$)N)rrwrequalities_inputsoriginal_signature)r)rwrr!rr"s rs_produce_guards_callback4_non_strict_export.._produce_guards_callbacks3)/1   rrFrZ)rrrzin_spec must not be Noner)r{rr#detect_non_strict_fake_tensor_leaksrrrrr1rmrrrr0rrrrrryr%rr2r"rxrr)rtrrrrrrarr _fakify_ctxrrr>r#r dynamo_config patched_mod new_fake_argsnew_fake_kwargsnew_fake_constant_attrsmap_fake_to_realrrryr!rrrr"rs `` @@@@@@rs_non_strict_exportr-sn!%H#G?AG&G&` ==   C C !" ]      8c        5YD! $    "B &&'CDM /0 &(  ""=1 #3 ; JO' !)) D ! #$1#'(@*$ !5 > > D D F. FHCj>N.O.O%c*UXX F. * $ E K 2  ) B5 ! % %';'E'E899788  !+  _ B. $ # E D K J 21   )(  s!H5 J I/ *I6I H<  H+ #*H *H7 HH+ H< I I I/(J HH H($H+ + H95H< < I I I I I, (I// I= 9J Jrrrarc [U5q[XX#5unnnnn[U5n Sn U(d:[R "X45up[ RRU 5SLn U(a[O[n U(dI[ RRR(a SSKJn UR R#5 U "UUUUUUU[$S9nU(dU (dUR&R(R+5Hunn[-U[ R.R0R25(dM;[5U5(dMMSUS3n[ RRR6(a [9U5e[:R<"USS9 M UR&R>n[AXU5n[CURD5nUUR&RFRHS '[KUUUUU5n[MUUUU5unn[OU5 [QU5 [SUU5 [UUU5 SS K+J,n [[UUR\UU UUX4UR&R(U/S 9 nU"U5 U(Gd[ RRR(GawSSKJn SS K/J0n UR n[cU5n/n[eU5S:GaBUGHn[gU5U;aUU5n U RHRiS 5n!U Rjn"U!cEU RlH5n#U#RHRiS 5n$U$cM#SU#RjSU$3n! O U!cSOU!n!SURnSURp3n%SU%SU"SU!3n&URsU&5 MSURnSURp3n%SU%S3n&URsU&5 GM SRuU5n'[:R<"S[eU5SU'S3SS9 AU$)NFr)fake_tensor_tlsrtrrrrrrarzWe found a fake tensor in the exported program constant's list. This typically means our tracing system encountered an op that we can't trace through. For the potential source, you can refer to following model attribute: z". Please file an issue on github. r() stacklevelinline_constraints)TrainingIRVerifier r(rrM state_dictrurmrSry verifiers)'_FAKE_TENSOR_ID_TO_PROXY_MAP_FOR_EXPORTrkz Used by 'z': zzshape=z, dtype=z FakeTensor(z ) from node 'z): z z Detected z fake tensors that are still alive after export. This is likely result of torch.export.export not being able to track side effects that is happening outside of model scope. Leaked tensors: zU Alternatively, please file a bug report to PyTorch team for further debugging help.);rrrfrYrr_r{_guardsr/rr-rrr%torch._subclasses.fake_tensorr0%non_strict_export_fake_tensor_trackerclearrrryr%r _subclasses fake_tensor FakeTensorr error_on_lifted_constant_tensorsrwarningsrcrxrrxrrwrrvrnr-r/r4r torch._export.verifierr4rMr"torch.fx.experimental.proxy_tensorr8r7rrrrrshapedtyperjoin)(rtrrrrrrarrdrWhas_ambient_moderr export_funcr0rgconstr error_msgrxrr3rurwrmr4exported_programr8 active_fakes legit_leak leak_sourcesfake_valrrk node_nameuser user_stack shape_info leak_info leak_detailss( rs_export_for_trainingrVs 5S9 s&A   337 **D>:  ==99)DDP%+.0BK emm**NNA==CCE!  %'E!4_0 O *)..88>>@JE3U&&22==&u--238978==''HH&y11MM):A -1155.s&A01J1JK:LO  !56.   3& BBb"89C(9& hh.&++~!&&00%& -. emm**NNNA 'LL &El&S "$ z?Q &h<#JJB2h<PD"&))-- ">K $ I#*$(JJD)-})EJ)509$))D .U % %/'.5( $*(..)9(..AQ!RJ"-j\ykQUVaUb cI '' 2$*(..)9(..AQ!RJ"-j\9T UI '' 29'>";;|4L MMC O,-&'3^4fg    rrr) phase_name)rrrvrarvc$^^SSKJn [U5q[ 5n U R U(aSOS5 U R U(aSOS5 U q[S[ S9 [S S S 9 U(a+U"5(a[UUUUUUUS 9m[S U4SjS 9 T$[XX#5unnn nn [U5n U(a[O[n U "UUUUUU U[R"[ US9S9nUR"R$n['XU5n[)UR*5nUUR"R,R.S'[1UUUUU5n[3UUUU5unn[5U5 [7U5 [9UU5 [:R<R>RAU SS9 SSK!J"n [GUU5 [IUURJUU UUX4UR"RLU/S9 m[S U4SjS 9 U "T5 T$)a Traces either an nn.Module's forward function or just a callable with PyTorch operations inside and produce a ExportedProgram. Args: mod: the `nn.Module` to trace. args: example positional inputs. kwargs: optional example keyword inputs. dynamic_shapes: An optional argument where the type should either be: 1) a dict from argument names of ``f`` to their dynamic shape specifications, 2) a tuple that specifies dynamic shape specifications for each input in original order. If you are specifying dynamism on keyword args, you will need to pass them in the order that is defined in the original function signature. The dynamic shape of a tensor argument can be specified as either (1) a dict from dynamic dimension indices to :func:`Dim` types, where it is not required to include static dimension indices in this dict, but when they are, they should be mapped to None; or (2) a tuple / list of :func:`Dim` types or None, where the :func:`Dim` types correspond to dynamic dimensions, and static dimensions are denoted by None. Arguments that are dicts or tuples / lists of tensors are recursively specified by using mappings or sequences of contained specifications. preserve_module_call_signature: A list of submodule paths for which the original calling conventions are preserved as metadata. prefer_deferred_runtime_asserts_over_guards: With the current dynamic shapes language for dims and derived dims, we can run into constraints that are not expressible with the language. For example, flattening a matrix and adding to a vector, both fully dynamic (i.e. x.reshape([-1]) + y) emits a guard s0 * s1 = s2, which is not expressible. By default, we either raise a constraint violation error or specialize to static values. If this flag is set to True, we avoid erroring out and instead allow complex constraints to exist as runtime assertions in the graph. The sympy interpreter (torch/utils/_sympy/interp.py) will produce the math ops required to compute and assert the value of the guard (e.g. sym_size_int, eq, _assert_scalar). Additionally, if TORCH_DYNAMO_DO_NOT_EMIT_RUNTIME_ASSERTS=1 is specified, we will allow complex constraints while not emitting runtime asserts, returning a cleaner graph with lesser guarantees around dynamic shapes. Returns: An ExportedProgram containing the traced module. r) export_training_ir_rollout_checkr non_strictrv aot_dispatchz export.enterrrcg)Nzstart!rererrrsr_export.. s8rr) payload_fnr.rKc>[T5$rrpr\srsrr] s Rrr)rvr1r3T)in_place)Verifierr5c>[T5$rr`)rKsrsrr] s SAQ=Rrr)'torch._utils_internalrYrrror}r:r6r3rVrfrYrr-rOpartialrrrxrrxrrwrrvrnr-r/r4r{rrremove_proxy_from_state_dictrBrbr rMrry)rtrrrrrrvrarYrrcrdrWrHrgrxrr3rurwrmrbr5rKs @@rsrr| s0tG 5S9 EE II&hl3 II n.AM>?h+;<8:: !    +I8c  ,I  s&A   337%+.0BK!  %'E%4_'' %  O4C3G3G3K3K.s&A01J1JK:LO  !56.   3& BBb"89 MM445HSW4X/C(& hh.&++~!&&00* (5RS-. rrr)NN)rmrOrloggingrrFrArAcollections.abcr contextlibrrr itertoolsrtypingrr r unittestr weakrefr{ torch._dynamotorch.fxtorch.utils._pytreer_pytreertorch._dispatch.pythonr torch._dynamo.excr rtorch._export.db.loggingrrtorch._export.non_strict_utilsrrrrrrrr-torch._export.passes.collect_tracepoints_passr(torch._export.passes.lift_constants_passrrr\rrrrr r!r"r#rBr$torch._export.wrappersr%5torch._functorch._aot_autograd.graph_capture_wrappersr&rr'r(&torch._functorch._aot_autograd.schemasr)-torch._functorch._aot_autograd.subclass_utilsr*$torch._functorch._aot_autograd.utilsr+r,torch._functorch.aot_autogradr-r. torch._guardsr/r0r1"torch._library.fake_class_registryr2torch._loggingr3r:r4rdr5r6%torch.export._leakage_detection_utilsr7torch.export._unliftr8torch.export.dynamic_shapesr9r:r;r<r=torch.export.exported_programr>torch.fx._symbolic_tracer?rCr@rArBrCr]rDrErFrGtorch.fx.graphrHrItorch.utils._sympy.value_rangesrJrKrLrMrNrOrPrMrQrR getLoggerrfrCr~rprrrSrl dataclassrUrurrcriticalrrD exceptioninfowarningrErcrYrrrrrrr|r}rrrr rr-r"r#r=rrKrSrfrzrrrrrrkrrrrrorqrr"r-r/r4r9r:rrQrUrYrrr`rbrfrnrvrxrrrrrpNoderr-rVrrerrrsrs  $==00 $$;6   Q   63XBWDC?,8QQB5;  '(;V!!%S#XsCx @49 LIL ,,,2     d#==$= 23  MM MM  LL KK OO  MM >: 9 9BBC( :s:.!5!5.0S*Q-h : 'T(XX__(88??( #s(^(V1, 1, 1,c5<</01,C//0 1, I 1,h-(-)-C//0- -<%?588#7#7%?D%?d!%j jjZ/ /)/ /dXX__5:XX5I5I Duxx4S>+/ $ $$!&9!9:$Cy4' $  / $: 4 %)EI B 79&+8="BB S/B cNT !BcNU3Z/$s);dB B %*#s(O B $B26BBBB XXBZ!.n! 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