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HH ' ' , sABA- $B-%BBFakeTensorModec#^# URnSUlSv Xlg!Xlf=f7f)NF) cache_enabled) fake_mode old_values rLdisable_fake_tensor_cachers,--I,"'  "+)s - "-*-c^U/nU(arUR5m[T5(dURT5 M:TR5up4UR U4Sj[ U555 U(aMrU$)Nc3<># UHn[TU5v M g7frH)getattr).0keycurrs rL $get_plain_tensors..sG2F3GD#&&2Fs)popr*append__tensor_flatten__extendreversed)subclassouttodo inner_keys_rs @rLget_plain_tensorsrsi :D xxz,T22 JJt  //1  G(:2FGG $ JrNc[U[5(ag[U[5=(a [RR U5$r) isinstance FakeTensorrrrrs_is_fake_tensorxs rLis_fake_tensorrs3!Z   a @UXX%=%=a%@@rNcSSKJn [U5(ag[U5(a[ U5R U5up#SnUHjn[ X5==[S`=b(un [U5nUcUnM/XG:wa [S5eMA =[S`=bu MS n[S[ U535e U=(d S$[X5(a[UR5$[U[5(am[R"U5(aR[RR!5n [RR"R%X 5n [U 5$[U[5(aD['U5(a4[RR"R)U5n [U 5$g)NrFunctionalTensorTrcz got mixed fake and real tensors!(expected Tensor or CustomClassBase, got F)#torch._subclasses.functional_tensorrrr*typerrris_fakeAssertionErrorrrelemrr_is_functional_tensorrs$_functionalization_reapply_views_tls _functorch_unwrap_functional_tensorr get_unwrapped) rrattrsrgot_fakeattrvfake unexpected reapply_views unwrappeds rLrrspDa$Q''7--a0 $D!""VX]"1:D'#'!),-OPP* # '_&'(B4 CSBTU 5 A ( (qvv Av  5#>#>q#A#AEEG HH''AA!S y!! 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BrNc## URn[RR5nX!:wa[ USU35e[RR 5 SUl[RR 5 [RRS5 Sv XlSSS5 SSS5 g!Xlf=f!,(df  N"=f!,(df  g=f7f)N, T)in_kernel_invocationrrrs_meta_in_tls_dispatch_includer_DisableTorchDispatch_PreserveDispatchKeyGuard!_set_meta_in_tls_dispatch_include)rprev_in_kernel meta_in_tlss rLin_kernel_invocation_managerrs 33N((88:K$ }B~.>?@@  ' ' ))- &XX / / 1 HH 6 6t < @1?. 2 * )2@. 2 1 * )sNAC0 &C C'C+C2C: C0C  C C C C-)C0c[RRUR5R S5SR S5S5$)Nz::.r)rrrs _should_allow_numbers_as_tensorsnamesplitrs rLshould_allow_numbers_as_tensorsrsB 88 4 4 $#))#.q1 rNcR\rSrSr\R R SS5S:HrSrg)FakeTensorConfigiTORCH_FAKE_TENSOR_DEBUG01rcN) rerfrgrhosenvironrKdebugrjrcrNrLrrs JJNN4c :c AErNrc\rSrSr%S\S'S\S'SS.SSjjrSS jrSS jrSS jrSS jr SSSjjr SSjr Sr g )SymNumberMemoDescriptorir_namer-_is_nested_intF is_nested_intcXlgrH)r)rrs rLr SymNumberMemoDescriptor.__init__s+rNcX lgrHr)rownerrs rL __set_name__$SymNumberMemoDescriptor.__set_name__s rNc SUR3$)Nrrrobjs rL_memoSymNumberMemoDescriptor._memo s4::,rNc"SURS3$)Nr_vcrrs rL_memo_vc SymNumberMemoDescriptor._memo_vc s4::,c""rNc"SURS3$)Nr_epochrrs rL _memo_epoch#SymNumberMemoDescriptor._memo_epochs4::,f%%rNNcH[XRU55=ncgUR(dZUR5(dE[XR U5S5UR :wa[ XRU5S5 g[U[R5(aURRbU$UR(dO[XRU5S5URR:wa[ XRU5S5 gU$rH)rrr is_inferencer_versionsetattrrrrrnoderdrrepoch)rrobjtypers rL__get__SymNumberMemoDescriptor.__get__sjjo. .A 7 ""3+;+;+=+=sMM#.5EZZ_d3 a ( (QVV[[-DH##--c2D9S]]=P=PP CC$ /rNcUcR[XRU5S5 [XRU5S5 [XRU5S5 g[XRU5U5 UR(d:UR 5(d%[XRU5UR 5 [XRU5URR5 grH) rrrrrrrrr)rrrs rL__set__SymNumberMemoDescriptor.__set__2s = CC$ / Cs+T 2 C))#. 5 CC% 0&&s/?/?/A/A]]3/> C))#. 0C0C DrN)rr)rr-rr)rrrrrr)rrrrrH)rrrztype[FakeTensor] | Nonerz$torch.SymInt | torch.SymFloat | None)rrrzBtorch.SymInt | torch.SymFloat | torch.SymBool | int | float | Nonerr) rerfrgrhrirrrrrrrrjrcrNrLrrsu J05, #&CG(? -8 E  ER E  ErNrc^\rSrSr%SrS\S'S\S'S\S'S\S '\"5rS \S '\"5r\"5r S \S '\"5r S \S '\"SS9r S\S'S\S'\ RRRr\S+Sj5r\S,Sj5rS-SS.S.Sjjjr\S/Sj5r\R,S0Sj5r\S/Sj5r\R,S1Sj5r\S2Sj5r\S3SSSSSS.S4S jjj5rS5U4S!jjr\S6S"j5r\\S#\"54S7S$jj55r \S8S%j5r!S&S'.S9S(jjr"S:S)jr#S*r$U=r%$);riBaT Meta tensors give you the ability to run PyTorch code without having to actually do computation through tensors allocated on a `meta` device. Because the device is `meta`, meta tensors do not model device propagation. FakeTensor extends MetaTensors to also carry an additional `fake_device` which tracks devices that would have been used. r _fake_devicerr Tensor | Noner rz$SymNumberMemoDescriptor | int | None nonzero_memo unique_memounique_consecutive_memoTrtype[Tensor] | NonerrrKc,[UR5$rH)rMrKr~s rLrkFakeTensor.is_mkldnnis)););<>== }}$$T4:66rNN) masked_gradcUR(a2[RRRR XUS9$[ R"XUS9$)Nrwr)rkrropsaten _to_densedefaultrto_dense)rrwrs rLrFakeTensor.to_denseusI >>99>>++33{4 tkJJrNc|URR(a[R"S5$UR$Nr)rrrrrrr~s rLrFakeTensor.devices, >> . .<<' '## #rNc[erH)NotImplementedError)rrs rLrrs!!rNcUR$rH)rr~s rLrFakeTensor.fake_devices   rNc0URU5UlgrH)_normalize_fake_devicer)rrs rLrrs 77?rNcURS;a [U5 [UR5(aURcURS:waz[ [ UR5R 5(aM[ R"URS[ [ UR5R535nU$[ R"URS35nU$)zFNormalize device by initializing GPU context and setting device index.)rmrorp:z:0) rrrvindexrrris_initializedrcurrent_devicers rLr!FakeTensor._normalize_fake_devices ;;/ ) V $ "6;; / /FLL4H{{e#v{{(C(R(R(T(T{{m1WUFKK%@%O%O%Q$RS   R&89 rNF)rrrrt _is_paramc ([[[[4U 5n[HnUR US5 M U(a#[ [U55n[SU<35e[U[5(aUbXLa [S5eUnOMUb<[U[5(d[S[U535eUb [S5eUnUc [S5eUc [S5eSU4SU 4S U 44VVs/sH6unnUcM U[R[R "U554PM8 nnnU(a7US unnUS SH#unnUU:wdM[#S US USUS U35e UnO [S5e[R$"UUU c UR&OU SUS9nUR((d [R*R-U5 O[R*R/U5 UR RS:wa"[1SUR R35eUR2(dURS:Xa [1S5eUUlUUlUUlUUlUUl[U[5(a [1S5eUUlSUl SUl!SUl"SUl#SUl$U (aU Ul%[LRN(a[PRR"5Ul*U$s snnf)Nz8FakeTensor.__new__() got an unexpected keyword argument z5FakeTensor.__new__() got conflicting fake_mode valueszTFakeTensor.__new__() expected a FakeTensorMode or Tensor as the first argument, got zYFakeTensor.__new__() expected either (fake_mode, elem, ...) or (elem, fake_mode=..., ...)z;FakeTensor.__new__() missing required argument: 'fake_mode'z6FakeTensor.__new__() missing required argument: 'elem'rrrrr5z4FakeTensor.__new__() got conflicting device values: =rzKFakeTensor.__new__() missing required argument: 'device' (or 'fake_device')T)dispatch_devicedevice_for_backend_keysrz%elem.device.type must be 'meta', got z7device.type must not be 'meta' when allow_meta is Falsez$real_tensor must not be a FakeTensor)+rrrrR,_FAKE_TENSOR_CONSTRUCTOR_IGNORED_STATE_ATTRSrnextiter TypeErrorrrrrrrrrr ValueError_make_subclassrt_allow_unsafe_data_ptr_accessrs_set_throw_on_mutable_data_ptr(_set_warn_deprecated_on_mutable_data_ptrr allow_metarrr rrKrrrrrnested_int_memor rrr4extractrb)clsfake_mode_or_elemrrr rrrKrrrrtr state state_dict attr_namerrrspecified_devices first_nameresolved_devicecandidate_devicers rL__new__FakeTensor.__new__sH$$sF{+U3 EI NN9d +F d:./JJ."  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".q/ ,Q xx=("&7O<< 3 !)O'M ! 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":5"  V K88-DL22<@ ((,,V4 G #&'BC C gLJ+ K ''?@d J  Ks H?(H?IIc P^SSKJnJn SSKJm UR X4U5 [ U[RR5(aXX8;aS[ U[5(aUOU4n [U4SjU 55=(d X7;n U (a[SUSUS35e[ U[[R[S545(a[!SSSUS 9n [#U 4S S 9$[ U[5(a UHn UR%UUUUUU 5 M OUR%UUUUUU5 [ U[5(a9UV s/sHn UR'UUUUUU 5PM nn [#[U5S S 9$UR'UUUUUU5n [#U 4S S 9$s sn f) z Make a cache entry object for the given 'output' Tensor. Raises _BypassDispatchCache if the output tensor has characteristics that prevent caching it. r)hops_that_skip_faketensor_cacherO)has_free_unbacked_symbolsc3># UH>n[U[R[R45=(a T"U5v M@ g7frH)rrrrr)rors rLr3FakeTensorMode._make_cache_entry..s@"q5<<">?51!45!sAA zunbacked symbol in HOP z output or z# in hops_that_skip_faketensor_cacheNr}FrT)rVrrOrirrhrrrr)r*rrPrrrrrrrzr)rrrrr.r/r7rrOouts non_cacheable output_info out_elementout_elemrrs @rLr3 FakeTensorMode._make_cache_entrys  T   V4 tUZZ;; < </'666VID"; : *-dV4v@B fsELL$t*= > >7 4$vK,)^U  fe $ $% 55  &  1 1   fe $ $!' !'H55 !'  ,"<0 $ ?? K,)^U 5 s F#c ^^^URcDURc7URc*UR[La [ S5eUR$URb0XRRn[ U[5(d [ S5eU$URnUcg[U5(a [ S5eS U4Sjjm[UU4SjUR55n[UU4SjUR55n T"URT5n URbT"URT5 [Rn UR bUR R"n [%U5 U "5 [&R("UU UR*UR,SUR.S9n SSS5 SSS5 UR0(a [&R2R5W S 5 UR6(a [&R2R9W S 5 [ U[&R:R<5(aUR>(aU[A[BUR5n [ U [5(d [ S 5eU RE5n[%U5 U "5 W RGXX5 SSS5 SSS5 [UW URH5$!,(df  GNM=f!,(df  GNW=f!,(df  NQ=f!,(df  NZ=f) Nz2entry.constant_value must not be SingletonConstantz inplace_arg must be a FakeTensorz)Sparse tensors are not supported in cachec>[U[5(a4URc [S5eUR TUR5$[U[ 5(a [S5eU$)Nz6state.shape_env must not be None for _SymIntOutputStubz Unexpected _PySymInputStub value)rr8r]rrr7)rrrs rL check_valueGFakeTensorMode._get_output_tensor_from_cache_entry..check_value# s`%!233??*(P}}S%//::e_55()KLL rNc36># UHnT"UT5v M g7frHrcrrrrs rLrEFakeTensorMode._get_output_tensor_from_cache_entry../ sD^k!U++^c36># UHnT"UT5v M g7frHrcrs rLrr0 sFo{1e,,orr)rwr!rrtTzview_arg must be a FakeTensor)rrrr6rr')%rrrrrrrrrrrrrr contextlib nullcontextr]suppress_guardsrrr empty_stridedrwr!rtrrs _set_conjr_set_negr)r@rdrrrset_r)rrr6rrr. inplace_argrrrrmaybe_suppressrview_argstoragers ` ` @rL#_get_output_tensor_from_cache_entry2FakeTensorMode._get_output_tensor_from_cache_entry sr    %&&##'88$H'' '    (001Kk:66$%GHH >>    " " !LM M DX^^DDFhooFF$X%<%> %!^^;;N )$ /1A''nn&44 E2B /    HH  ud + ?? HH  eT * dEJJ11 2 2t||Denn56Hh 33$%DEE..0G-d3^5E 7EB6F3$x7712B1A / /*6F5E33sH6L>8K<6L:L1L L1< L L L L. *L11 L?c UR(a8URVs/sHnURXX4U5PM nn[U5$URXRSX4U5$s snf)z/ Create a new FakeTensor from the cache entry. r)rrrr)rrr6rrr.routputss rLr1'FakeTensorMode._output_from_cache_entryU s  $)#5#5 $6K884$6  > !;;))!,c sA*c ^SU4SjjmURX#XE5nT"Xa5 g![an[SUSUSUSU35UeSnAff=f![an[SUSUSU35UeSnAff=f)zn Helper to validate that the output synthesized from the cache matches the output created by normal dispatch. c>[U[5(a[U[5(d[S[U535e[ U5[ U5:wa#[S[ U5S[ U535e[ X5H up#T"X#5 M g[U[ 5(a,[U[ 5(aX:wa[SUSU35egUcUb[SU35eg[U[5(aB[U5[U5LdURURLa[SUSU35eg[U[R5(aG[U[R5(d[S[U535e[[X5 g[S[U535e) NzExpected tuple, got zTuple length mismatch: z != zInt mismatch: zExpected None, got zSymType mismatch: Expected Tensor, got zUnsupported type )rrrrr6ziprr(rrrrrr RuntimeError)ablr assert_helpers rLr>FakeTensorMode._crosscheck_cache_output..assert_helper{ s!U##!!U++(+?Qy)IJJq6SV#(+B3q6($sSTvh)WXXIDA!!'&As##!!S))QV(>!D)DEE.4=(+>qc)BCC!A|,,7$q')QVV166-A(+=aSQC)HII.BAu||,,!!U\\22(+@a )JKK"9a3"%6tAwi#@AArNz*FakeTensor cache crosscheck failure: func=z, args=z , kwargs=z: Dispatch raised=N)rrrrrr)r, Exceptionr) rr7rr<r.r/ true_outputr4rs @rLr2'FakeTensorMode._crosscheck_cache_outputn s B0 --d4HK   + .  [U[[45(aTRc [ S5eUR R RTRRR5- TRRR5- (dhTRRTRUR R U5SS9TRRLa[SUSUS35egg[U[ ["[$45(aX:wa[SUSUS35egg)Nz3self.shape_env must not be None for symbolic valuesT) compute_hintmismatch between fake value  and real value r)rrrr]rrexpr free_symbolsbacked_var_to_valrpreal_tensor_prop_unbacked_vals_maybe_evaluate_staticEqStruerrfloatr-)rrealrsympys rL_check_fake_real_vals?FakeTensorMode._maybe_infer_fake.._check_fake_real_vals s9$ 233>>)(M 33nn66;;=>nnCCHHJK ==!HHTYY^^T:> %ww||, 4:4&@PQUPVVWX , KsE4(</6tf[T5TRS.$NoprrrexcrsrL2FakeTensorMode._maybe_infer_fake.. s"%d)&)jj-rN metadata_fnzFReal tensor propagation found a metadata mismatch between fake tensor z and real tensor z , at outputz , for func: c4>[T5TRS.$rrrsrLrr s&)$i*-**1rNzIReal tensor propagation found an output size mismatch between fake shape z and real shape z , at outputz.size(z ), for func: c,>[T5STST3S.$)Nrrrr)rrrsrLrr s"!$i$@FVW[V\"])rNzQReal tensor propagation found an output value mismatch between fake output value z and real output value )rrrrrr)rtorch._subclasses.fake_utilsrrrrrrrr**generate_fake_kernels_from_real_mismatchesr_infer_fake_from_real_tensorr.rrr) rrpathrrrrjs_fakes_realrrs `` `` @@rL_maybe_infer_fake FakeTensorMode._maybe_infer_fake s I  < dELL ) ) (;!#'"'2(1TYY[$))+1N'O##F)&9(PTU{1\d.&&QQ!,!4D$EtKK'#f$5dV<#D\N,tf>   %dD1U{u) ##**UU%0%8dDI4OO+##'&(9$@!!'l4&B  &-''..YY)4) s-vO B) +))-.EdVL &t ~\$A  sa D F ? H FAFF"!FF H AHH #$HH  H?!H::H?c ^^^^SSKJn SmTR(a[TRR5mS UU4Sjjn[ R U5up[ RU5upU"SXSXB5 [[X5V V Vs/sHuupnTR!TXU5PM snn n 6unn[#U5(aT(aU"5 [ R%X5$![aom[RRR(a,[SUU4SjS9 U"5 [UU4S jU5sSm@$[S US US T35TeSm@ff=fs snn n f)z Helper to cross-check fake/real output properties & values, and create new fake vals if mismatched, but at the kernel level. Means this handles pytree outputs & checks aliasing. r)_check_alias_infoNc>[[TRR5R T55TRlgrH)rCsetr]pending_fresh_unbacked_symbols difference)pending_unbackedrsrL_clear_pending_unbackedXFakeTensorMode._maybe_infer_fake_kernel_from_pytree_out.._clear_pending_unbackedH s4<@DNNAABMM$=DNN 9rNrrc:>[T5STR3S.$)Nz>Mismatched aliasing spec between fake kernel and real kernel: rrrsrLrIFakeTensorMode._maybe_infer_fake_kernel_from_pytree_out..[ s!!$i\]`]g]g\hi)rNrc>[TTU5$rH)r)rrrs rLrrg s:4qIrNzGReal tensor propagation found an aliasing mismatch between fake output z and real output z , for func: r)rrr]rCrrtree_flatten_with_path tree_flattenrrrrr*rrr0rrrPtree_unflatten)rrfake_inreal_infake_outreal_outrrfake_paths_leaves fake_spec real_leavesr _fake_path _fake_out _real_out fake_leaves overridesrrs`` @@rL(_maybe_infer_fake_kernel_from_pytree_out7FakeTensorMode._maybe_infer_fake_kernel_from_pytree_out4 st C  >>#DNN$Q$QR   (.'D'DX'N$,,X6   /H >"%;>%;;6+ZY&&tZIN;"  Y  NN/ # %$$[<[vR"T5(d#[TTT85n&[S$U4S%jS&9 U"U&5$[RRRRTR55RRn'U'(a~[RRRTT5m1[RRRU14S'j5 T U'"T0TD6n&U"U&5sSSS5 sSSS5 $[H5un)n*U)"T5(dMU*"TT/TQ70TD6n!U![LdM-U"U!5s $ S.S/UU.U2UU4UU4S)jjjn+[T5(dU+"5n,U"U,5$[T5 T"T0TD6n$SSS5 U"TRW$TT2TRS5S+95$s snfs sn fs snf!,(df  G N=fs snf!,(df  GNP=fs sn f!,(df  O=fSSS5 GM=!,(df  GNL=fs snf![|a"n[tRSTU5 SnAGN~SnAff=f!,(df  GN=f!,(df  GNy=f!,(df  GN,=f!,(df  O=fSSS5 GM!,(df  GN=f![amn(TRr(aUT8T5LaP[vRx"T5(d5TR`b([TTT85n&[S$U4S(jS&9 U"U&5sSn(A($U(eSn(A(ff=f!,(df  GN=f![an-U+"U-5sSn-A-$Sn-A-f[a [tRS*T5 ef=f)0NrrNz,FakeTensorMode unrecognized subclass(es): %sc38# UHoRv M g7frH)r)rrs rLr0FakeTensorMode._dispatch_impl.. s! 3Ha ) )3Hc3B# UHn[U[5v M g7frH)rr)rrs rLrr s: 1Av&& FrrBTrc3<# UHoRSLv M g7frHrYrrs rLrr sM7L!zz-7Lz. should not have fake inputs without constantsrr5z1Expected exactly one arg for lift func, got args=z kwargs=c3<# UHoRSLv M g7frHrYrr4s rLrr Q;Pa::T1;Pr!c3F># UHnTRU5v M g7frH)may_turn_const)rrrs rLrr s!P?O!t22155?Orc&>TRTUSS9$)NTr")r)r converterrs rLr/FakeTensorMode._dispatch_impl.. si88qPT8UrNc>[U[5(a UR$[U[5(aTRc [ S5eUR RUR RRTRR5RTRR55$[U[5(a UR$U$)Nz2self.shape_env must not be None for symbolic types)rrrr(r]rrrrxreplacerrrreal_obj)rrs rLmaybe_to_real_tensor;FakeTensorMode._dispatch_impl..maybe_to_real_tensor< s!Z((}}$A|,,>>)(Lvv}}FFKK(()I)IJSSEE A/00zz!rN)compute_unbacked_bindingsfree_unbacked_symbolsc3<# UHoRSLv M g7frH)rr$s rLrrZ sM7L!MM-7Lr!c3># UHWn[U[5=(a; T"U5=m=(a* TRSL=(a [U4SjT55v MY g7f)Nc3V># UHnUTRR;v M g7frH)r]r)rsrs rLr:FakeTensorMode._dispatch_impl...` s'!%A!N!NN!%s&))rr(r]rP)rrr1rsymss rLrr[ sg #Aq,/!6q!99d2!%#sAA"zpropagate_real_tensors %sz9real-tensor fallback failed for %s: %s; silently ignoringz,SKIPPED propagate_real_tensors %s(%s, %s) %sc f> ^^SSKm[RST5 SUUU U4SjjmT TLGa[RR R (dT RTTT4T T 4UT 5 OT RTTT4T T 4UT 5n[U[5(dr[T [5(d][U5[T 5LaF[T[[RU55[[RT 555 O [TUT 5 T"T RUSS9 U$)Nrzmaybe_propagate_real_tensors %sc2>[U[5(a[RS[ U5[ U55 Xl[ UR5UR55H up#T"X#5 M [ UR5UR55H up#T"X#5 M T"UR5UR55 g[U[5(Ga$T"U5(Ga[URRTR5(aITRc [S5eTRR!URRU5 g[URR=nTR"5(ak[UR$TR5(aEUR&S:Xa4TRc [S5eTRR!X!5 gggggg)Nz%maybe_propagate_real_tensors %s -> %sz3self.shape_env must not be None for symbolic Symbolr5z/self.shape_env must not be None for symbolic Eq)rrrrrrrrrrr(rrSymbolr]r"set_real_tensor_prop_unbacked_valsrlhsrhs)rreal_tr5real_sr1gorrs rLr@OFakeTensorMode._dispatch_impl..maybe_propagate_real_tensors..go sa,,II?A6 %+M%(6;;=%A 1 &B%(V]]_%E 1 &Fq'')6+@+@+BC<005J15M5M!!&&++u||<<>>1"0 U#IIFFKK# #31UXX>>&quuell;;EEQJ>>1"0 Q#II!T'<?6N0rNT)peek)rrRr>rrr)rrrrrrr*rrrrrr1rrr r]) r r@rr.r0r1rr/nil real_args real_kwargsrrs @@rLmaybe_propagate_real_tensorsCFakeTensorMode._dispatch_impl..maybe_propagate_real_tensors s  II7 > U UBs"''..YYAAv"K0   $LLv"K0   H#8V44&x88Xd8n<f11(;<f11(;< b(H5 *$..(NOrNrwrr) meta_tablerc3B# UHn[U5(+v M g7frH)rr$s rLrr sP:OQ a 000:Orzprims::prim_meta_implmissing_fake_kernelc>S[T50$NrrrsrLrr*9 sc$i)rNrc>T$rHrc)ctxsrLrr*G sSrNc>S[T50$rMrrsrLrr*X s #d)-rNcF>[RRRT5(a.[RRR"T/TQ70TD6$T(dTR T5(d [ T5eUc [ T5n[TTTTU5$rH)rrrarbcan_generate_trivial_fake_implgenerate_trivial_fake_implcan_run_unsafe_fallbackrrun_fallback_kernel)errorr. args_specrbrhas_symbolic_sizesr/rs rLmaybe_run_unsafe_fallback@FakeTensorMode._dispatch_impl..maybe_run_unsafe_fallbackk s~~##BB4HH~~++FF#)")E)Ed)K)K2488}4T:&tT9iO OrNz*failed while attempting to run meta for %sr)rrErz)T | Tensor | torch._C.ScriptObject | None)r rErrErH)rVzRuntimeError | Nonerr)mrVrOrr _check_for_subclass_check_for_subclass_argrr9rrprrPrr_rrrrr_to_copyrr] device_putrrrrallrr r r'r)clonerr6%validate_and_convert_non_fake_tensorsr)r@rWnondeterministic_seededrYr[detach__nested_tensor_from_tensor_listr tree_map_onlyr?r*r]rrignore_fresh_unbacked_symbolsinvalidate_written_to_constantsrir0r1rRrr library_utilsrcMutationCheckerZeroDivisionErrorcheckcheck_aliasing_constraintrrget_fast_op_implsrKrmaybe_to_dense_mkldnnrrrrHcpp_meta_supports_symint#_unbacked_special_fake_handling_opsrr decomposer rrstride_incorrect_oprJrr*_custom_ops_profiledatageneric_fake_kernelhas_fake_kernel"inferred_fake_kernel_from_real_outrrasimple_registry singletonfind fake_implkernel FakeImplCtxset_ctx_getterrop_implementations_checkshas_metarrrr +wrap_meta_outputs_with_default_device_logic):rrr<r.r/rOhas_unrecognized_typesrr>rflat_arg_fake_tensors is_lift_funcavoiding_device_init!device_conversion_skip_const_proprconst_flat_args const_args const_kwargsr all_constantflat_outflat_out_tensorsr>#maybe_ignore_fresh_unbacked_symbolsr.real_flat_argsrcmutation_checkerrrF fast_implrwr op_impl_outrHrrprofilesrmaybe_fake_implr4run_impl_checkop_implrYfallbacknot_implemented_errorrWr0r)rOrbr1rXrCrDrErr7s:`` `` @@@@@@@@@@@@rLr,FakeTensorMode._dispatch_impl s  J%22D&>B 9"5Y!? !!*"!*A.Ea.HQ " % %>@R " !,5 MIq9I9I!9LI M ! 3H!  ; : : : .. t}},  %  ! ! //777&8$))U2'+$uyy11999'+$ EIINN++33 3 .47ELL1 .Q##v--"" * !6 +D 1 1&)5M7LMMM$fJKCLBKQd..q11 q8) (.'<'<_i'X $J  3l3CCyF"t':':3'?'? !]))+C# 11$41PP 6{a3t9>$GvXV\U]^DG}& 11$Q@@.2-W-W )Y . *) &Q;PQQ tUZZ22 3 3 11B &&dii744<>)&&^^AA 0 :<.t4dEfE=< ,,T3H$PVW   6 ( h  ' 'M7LMMM #    II14 8?HIy!215yNI%+%:%:>9%U "I{&11$7J#0#@#@.)$  :k: &&(77 IxX  ( ( II>%>>== O O O d )+//5I$3Id4TT4TV4TUU 599>>**22 2 #4y1}DG&**W2EE **]3K/d1gU K.03D[4QRR -  "11$77"tt/W/W'W :**"055P:OPPP7+D14B6BT NND3F3N*7: + ** *.//'--3''88 =='';;  x}}$33D$PPPP  ' '#!,,T22*!0066;D$Q!)! 4F;; ..88BBGG IIK )FF   nn..::4F^^--<<[I4,d=f=F7?LP4II8(A #NGd##%dDB4B6B n47 DD (A*. P& P  P P(~~02H/9 9  -d3$)&)4,  < <46::h+? =   u"!Nb#]j N<=<dJ%  O  rT "HLP4IIII$ // +)44T::2?dHUF%-% 8??G' x43" D,-BC C  MMF M  sLppp.p*.p -p.p$ p)p;p;9q q q1q.q37r"#r4sAt's4*s: s4 t v vv p!) p8 q q q+3 r=rr" r14 s s s& "s4)t4 t>tt u=A u80u=6u88u= v vv wv)#w)%w debugprimsr]rxlavision torchtext torchaudio quantizedcUR(dgURUR;=(d UR5S:H$)NFz fbgemm::gmm)r namespace+_can_run_unsafe_fallback_allowed_namespacesrrrs rLrT&FakeTensorMode.can_run_unsafe_fallback s:** NNdNN N ,yy{m+ rNcl^^^^^^/mSUUUUUU4SjjnTVs/sH oe"U5PM nnUT4$s snf)z Checks if the list of tensors are fake tensors. If not, try to convert them to fake tensors. Returns the original args, kwargs, and a flattened list of (args, kwargs) that are fake tensors. c>[U[5(dU$T RU5(Gd[T S5(aX[R R T R;a0[RT T5up[S[T X535e[Rc T RO[RnU(dg[U[5(a"UR nUT La[SUST 35e[RT T5up[S[T X535eTR#T U5nOUnTR%U5 U$)NrYzECan't call metadata mutating ops on non-Fake Tensor inputs. Found in z"Mixing fake modes NYI x.fake_mode=z vs self=zuPlease convert all Tensors to FakeTensors first or instantiate FakeTensorMode with 'allow_non_fake_inputs'. Found in )rrrrrrrWr[rYrr rr"r,rrrrrr) rr.r/r x_fake_moderrWr)rrbrrs rLvalidateFFakeTensorMode.validate_and_convert_non_fake_tensors..validate sZa((##A&&4((UYY-C-Ctyy-P#)#8#8I#NLD(_`klprv``AB 'EEM..(GG& -!!Z00&'kk &d2"0"D[MQZ[_Z` a#$*#8#8I#NLD(BBMdTXBaAbd  00q9 ! ( ( -JrN)rrErT | FakeTensorrc) rrr)rbrWrrvalidated_argsrs ````` @rLra4FakeTensorMode.validate_and_convert_non_fake_tensors sA35# # J099y!(1+y9444:s1c Z^^^^^^^^ ^ TRmSmSmSm Sm T[RRLdT[RRLa:[ T5S:Xa+[ TS[5(aTSRm T SLm SUUUUUUU U U4 Sjjn[XQ5$)NFr5rc> ^[T[5(dT$Tc[RTT5ummT R T5nU(aG[ R "TRT:HUU4Sj5 T (aT Tl[[T5$TbFT(aTRT T5nOTRT TT=(d T5nT (aT UlU$T$)Nc(>STRST3$)Nz-FakeTensor is wrapped to wrong device, found z , expected r)rr4srLrZFakeTensorMode.wrap_meta_outputs_with_default_device_logic..wrap.. sKAHH:U`an`oprN) rrrrdrrr_checkrrKrrErr) r4rrrr)rrbrrcinput_dispatch_keyspreserve_dispatch_keysrs ` rLwrapHFakeTensorMode.wrap_meta_outputs_with_default_device_logic..wrap sa(($224C!***1-K HH -p*&9AOAqz!&)$44T1=C#88a!8=C*(;C% rNr4rErr) rraliasrdetachr6rrrKr0) rrrrbrrrr)rcrrs ` ``` @@@@@rLr:FakeTensorMode.wrap_meta_outputs_with_default_device_logic s..  !&!&" TZZ'' '44;;3F3F+FI!#9Q<44"+A,"<"< %8%D "% % N  rNrhcSSKnSSKJn Uc=URnUR(d [ S5eU=RS- slUR "U"US55nURRRS5nURc [ S5eURRURRUUS9UUS9nU$) Nr) NestedIntNodez4should only be called while FakeTensorMode is activer5intermediate_offsets_or_lengthszself.shape_env must not be None)valrS)symrdrS) r!torch.nested._internal.nested_intrrrrrrrSEphemeralSourcer]r create_symbol)rrirrrrdsrcrets rLrj)FakeTensorMode.create_symbolic_nested_int% s 4C  44L##$J  % % * %||M,:;mm""223TU >> ! !BC Cnn..,,- /  rNcp[RRUR;agXR;$r)rrrW view_copyrY_cpp_meta_supports_symintrs rLro'FakeTensorMode.cpp_meta_supports_symintX s* 99  $)) +5555rNcUR5[:*=(aM [U5(+=(a6 URU5(+=(a URR S:g$r)numelCONSTANT_NUMEL_LIMITrrrrrs rLr'FakeTensorMode.may_turn_const_ sS GGI- - (!!$$ ($$Q'' ( '  rNc[SU55n[U5nU(aUR5(a[UUUSS9upxUR 5HupU S:wdUR U 5(aU OSn UR U 5(dM=URU 5(dMUU RcMdURRU R5 M ggg)Nc3<# UHoRSLv M g7frHrYr$s rLrAFakeTensorMode.invalidate_written_to_constants..n r%r!TrPinputr) rPr is_mutabler$r has_argumentrr rr?) rrrr.r/ any_constant schema_inforrgkrs rLrg.FakeTensorMode.invalidate_written_to_constantsg sQ;PQQ %d+ K2244.-1 MA #((*w,+*B*B1*E*EAF$$Q''#..q11 ...JJ1::V+5  3/  4545'45$ 45  45 / 45l=! =!=!$ =!  =!  =!@-1) <!,    "" ''       !! $$ // 55==  !+6  !! +' 6 4??22D4H4H4P4PQH WW 4W W % W  W:&* $37" " # "  " 1 " "  " " rNc4SSKJnJn [RR R R5SLnU(aU"U5H n[S5e gU"U5H0nURHnXpR;dM[S5e M2 g)a Validate symbolic content in output and raise _BypassDispatchCache if caching should be bypassed. Args: state: Cache key state containing known symbols output: Output to validate proxy_mode_active: Whether PROXY dispatch mode is currently active Raises: _BypassDispatchCache: If output contains symbolic content that prevents caching Details: If our output contains any symbols that didn't appear in the input then we need to bypass. Usually this will be unbacked symbols which can't be properly reconstructed but there could be "weird" cases where backed symbols spontaneously appear (from non-input state)? If we're proxy (symbol) tracing and the output contains ANY symbols then we need to bypass. The problem is that ProxyTorchDispatchMode relies on SymNode object identity and being able to see the construction of SymNodes. We could improve the proxy tracing case in a few ways: 1. If the output SymNodes are directly copied from inputs then this is actually fine - they're already tracked. This would probably be the biggest bang/buck. 2. If the output (tensors) are all direct copies of the inputs then this is also fine - since they're inputs they must be tracked. We already compute this we just don't plumb it around enough. 3. If the output SymNodes are already tracked by the proxy then this is also actually fine - they're properly tracked. This probably wouldn't be common since for most outputs we use torch.empty_strided() and recompute strides. 4. We could use the proxy to track "how" the SymNodes were computed and when using the cache we could "replay" them properly to teach the proxy how to build them. r)_iterate_exprs_iterate_nodesNzProxy mode with SymNode outputzunrepresented symbol in output) rirrrrr<r=r>r?rrrD)rr7rrrIrr5rs rLrxrx sZU&&33BBDDPJ 'A&'GH H( 'A..!4!44./OPP)(rNc>^^^ ^ [RRUR;aTe0m [ 5 SUU 4SjjnUVs/sH oe"U5PM nn[ R X#5upxU"U0UD6n SSS5 [5m UHUn [U [5(dM[U 5(aM,T RU R5R5 MW SUU UU 4Sjjn [ RU W 5$s snf!,(df  N=f)Nc>TRU5(a^[R"XRS9nUR(aUR UR 55 UT[U5'U$U$)Nr)rrr zeros_likerr# _coalesced_rr)r4rr inp_implss rLto_real_tensor+run_fallback_kernel..to_real_tensor sZ$$Q''&&q?;;OOANN$45%& "S'" HrNcL>[U5T;aE[U[5(a0[U5(d UR 5R T;aTe[U[5(a9[U5T;aT[U5$TR RTU5$U$rH)rrrrr4_cdatarr)r4rrorig_not_implemented_exceptionstoragess rLmap_out$run_fallback_kernel..map_outs a5 ! q& ! !!!$$  "))X50 0 a !u ! A'' 66GG STUUHrN)r4rErz T | Tensorr)rrrWr[rYr)rr rrrrr-r4rr0)rrrbrWrrrr.r/rr4rrrs` ` @@rLrUrU s yy*,,I   1:: 1^A& :,,YB  $ !& !  &)UH  a  ## Q--/667 ??7A &&C; sD D !D D Dc,UR5 X U'grH)rrrr6s rLr/r/'s #JrNc X U'grHrcrs rLr0r00s #JrNcB\rSrSrSSjrSSSjjrSrg) FakeCopyModei:cXlgrHr)rrs rLrFakeCopyMode.__init__;s"rNNc0U(aUO0nU[RRRLaV[ US[ 5(d[ S[US535eU"URRUSSS940UD6$U[ RLa[U5S:wd[U5S:wa$[ S[U5S[U5S35e[[ US5n[[[[4US 5n[!U5U;aU[!U5$URRUSS9nXv[!U5'U$[RR#5 U"U0UD6sSSS5 $!,(df  g=f) NrrT)rz3Expected 2 args and 0 kwargs for __deepcopy__, got z args and z kwargsr5)rrrs TensorBaser`rrrrrr2 __deepcopy__r6rrrrrDisableTorchFunctionSubclass)rrr<r.r/r<memors rL__torch_function__FakeCopyMode.__torch_function__>so"r 588&&,, ,d1gv..$'.}s=9a&q))9r)rP)rbs rLr[r[|s =9= ==rNc$[U[5(ag[U[5(dg[U5nU[Lag[ U[ R R5=(a UR[RLnU(agg)NFT) rrrrr8rrrnrorA)rx_type#is_metadata_only_parameter_subclasss rLr\r\sv!Z   a  !WF  6588--. C  % %)B)B B(+ rNcd[S[[US5R555$)Nc38# UHn[U5v M g7frHrrr5s rLr..s441A4rr)rrrrrs rLrrs*e4VT!W-2244/rNcd[S[[US5R555$)Nc38# UHn[U5v M g7frHrrs rLrrs661A6rr)rrrrrs rLrrs*6VT!W-44661rNcV[[[US5R55$rL)rrrrrs rLrrs  VT!W,,.9rN) _device_not_kwarg_ops_is_tensor_constructor_like_tensor_constructorscontains_tensor_typesrmrrnrrrclU[R;a [RRU5 ggrH)rrrr;s rLrHrHs) n"""  %#rNc[RS5 [RS[R5 [RS[R5 [R nU(ah[RS5 [ SU55n[UR5SS9H#up#[RSUS -US 3U5 M% gg) NzFakeTensor cache stats:z cache_hits: %sz cache_misses: %sz cache_bypasses:c38# UHn[U5v M g7frH)r6)rrs rLr#dump_cache_stats..s-HqCFFHrcUS*$r{rc)rs rLr"dump_cache_stats..s AaD5rNr;z %-*s %sr5r) rinforrrrmaxsortedr)rwidthrrs rLdump_cache_statsr#sHH &'HH !:!:;HH !>#>#>?,,H $%-H--8>>+ADA HH]EAI!Aw :BrNc 0^S U4SjjnUR5S:waU"SUR535 [UR55Vs/sH6n[RR R UR5PM8 nnS/UR5-n[UR55VVs/sHupxX4PM n nnU RSS9 Sn U n U HMupX:wa'U"SURS UR5S 35 XU'XRU-n XU-n MO U [R"UUURURURS 9sSSS5 $s snfs snnf!,(df  g=f) Nc<>[STRSUS35e)NzQpropagate_real_tensors: we cannot infer a Fake kernel (meta kernel) for operator z because z>. Please use torch.library.register_fake to add a Fake kernel.)rr)rrs rL unsupported1_infer_fake_from_real_tensor..unsupporteds1**,((9VHEK L  rNrz'a return has a non-zero storage offset rcUSUS*4$rnrcrs rLr._infer_fake_from_real_tensor..s!qte}rNr;r5z(a return was not dense in memory (sizes z strides ))rrwr!)rrrr)rrryrrrar{ allocate_sizer]rrsortrrrrwr!) rrrr&r fake_shape fake_stridesrr5rexpected fake_strides ` rLrrs{  A%5h6M6M6O5P Q x||~&&A   ..t~~>&4(,,.(L&/0A&BC&BFCx&BGC LL,L-HK = :8>>:J)T\TcTcTeSffgh (SnnS11!sO3  ""  ??..??   5D s=E<F<6F Fc*URc [S5e[RU5up4[ SU55(d[ SUR 35eUVs/sHn[XU5PM nn[RXd5$s snf)Nzmode.shape_env must not be Nonec3V# UHn[U[R5v M! g7frH)rrrrr s rLr5inferred_fake_kernel_from_real_out..sBMqz!U\\**Ms')zPpropagate_real_tensors: we don't support operators that return non-Tensors. Got ) r]rrr r_rr rr )rrr real_flat_outspecr fake_flat_outs rLrwrw s ~~>?? !--h7M BMB B B " | -  IVV 11$A> MV   55Ws#B)rKrrr-)rurrr-)rrErzdict[T, Literal[True]])rz/Generator[TorchDispatchMode | None, None, None])rrrzGenerator[None, None, None])rz!Tensor | TraceableWrapperSubclassr-list[Tensor | int | SymInt | CustomClassBase]rr7)rrRrzTypeGuard[Tensor])rrRrru)rrRrr)rrRrztorch.device | None)rr@rztorch._C._SchemaInfor)rztype[T]rr/rzlist[T])rrRrr-rs)rrrr)rr6r7rrr) rrrr@rbrxrWr/rrrr)rrrrr6_DispatchCacheEntryrr)r.rxrr)rbrxrr-)rrRrr-)rrrrr)rrrtorch._ops.OpOverloadr torch.Tensorrr:)rrrr9rrrr) __future__ratexitrrrFrrr threadingrr<typingr collectionsrrrrrr r r r typing_extensionsr rrrrrtorch._library.utilsrarbrhrrrrtorch._C._functorchrrtorch._custom_class_baser"torch._library.fake_class_registryrtorch._library.fake_profilertorch._loggingrtorch._prims_commonrtorch._subclasses.meta_utilsrrrrr torch._utilsr!r"torch.fx.immutable_collectionsr#torch.fx.operator_schemasr$ torch.multiprocessing.reductionsr%torch.overridesr& torch.typesr'r(torch.utils._mode_utilsr)torch.utils._python_dispatchr*r+r,torch.utils._pytreer-r.r/r0r1r2torch.utils._statsr3torch.utils._tracebackr4_fake_tensor_utilsr6r7r8collections.abcr9r:r;r<r=r> torch._guardsr? torch._opsr@rirArB getLoggerrer_logginggetArtifactLoggerr+r9rr4rrCDimList_pytreerrEr)rrrr}rs_dispatch_key_parserJrMrP frozensetrirrrvrxrrrrrrrrlocalrr,rcontextmanagerrrrrrrrrr rrrr%r'rrrrrrrrrrrrrrr8rrrrrR_StoragePointerrxrUr/r0rrr[r\r5rrrrrr7rrrprofiler_record_function_exit_RecordFunctionrtorch._subclasses.fake_implsrrrrrmrrnrrrrHregisterr#rrwrcrNrLrgs9"   #!OOO55! ,,33T4?8,5H98;-1/ WV$4RRPP#$%O !  ) )(4J K..::8EVW     CL zz~~xx33K@Q%*09&660,   \   L   ,  <  <  <  L GIOOG /& -- ,,/ 73 &A F F    ..  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