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K  KrPc VP'd6\PPPP WVR7#\ P!WVR7#)rr$)rrzopsaten _to_densedefaultrto_dense)rrr$s&&$rNr,FakeTensor.to_denseusK >>>99>>++33{4 tkJJrPcV^8dQhRR/#rGrJrrL)rMs"rNrOrs$$ $rPc ~VPP'd\P!R4#VP#r)rrrzrrrs&rNrFakeTensor.devices/ >> . . .<<' '## #rPc V^8dQhRRRR/#)rGrrrJrrL)rMs"rNrOrs"" ""rPc \hrR)NotImplementedError)rrs&&rNrr2s!!rPcV^8dQhRR/#r/rL)rMs"rNrOrs!!\!rPc VP#rR)rrs&rNrFakeTensor.fake_devices   rPc V^8dQhRRRR/#rrL)rMs"rNrOrs@@,@4@rPc 2VPV4VnR#rR)_normalize_fake_devicer)rrs&&rNrr8s 77?rPc V^8dQhRRRR/#)rGrrrJrL)rMs"rNrOrs  |  rPc VPR9d \V4\VP4'dVPfVPR8wd|\ \ VP4P 4'dN\ P!VP R\ \ VP4P4 24pV#\ P!VP R24pV#)zFNormalize device by initializing GPU context and setting device index.rx:z:0)rurw) rrr}indexrrzis_initializedrcurrent_devicers&rNr;!FakeTensor._normalize_fake_devices ;;/ ) V $ "6;; / /FLL4H{{e#v{{(C(R(R(T(T{{m1WUFKK%@%O%O%Q$RS   R&89 rPrr _is_paramFcPV^8dQhRRRRRRRRRRR R R R R RRRRRRRRRRRRR/#)rGfake_mode_or_elemzFakeTensorMode | Tensor | Nonerrrztorch.device | str | NonerrrrrHrIrr rrrrrCrKstatez*Unpack[_FakeTensorConstructorIgnoredState]rJr rL)rMs"rNrOrs}}9}}* }  } # }$}3})}/}0}#}}<} !}rPc l\\\\3,V 4p\FpVP VR4K V'd$\ \V44p\RV: 24h\V\4'dVeWJd \R4hTpMQVe?\V\4'g\R\V4 24hVe \R4hTpVf \R4hVf \R4hRV3RV 3R V 33UUu.uF7wppVfK V\P\P !V443NK9 pppV'dAV^,wppVR ,F$wppVV8wgK\#R V R V R V R V 24h TpM \R4h\P$!TTV f VP&MT RVR7pVP('g!\P*P-V4M\P*P/V4VP PR8wd#\1RVP P 24hVP2'gVPR8Xd \1R4hVVnVVnVVnVVnVVn\V\4'd \1R4hVVnRVn RVn!RVn"RVn#RVn$V 'dV Vn%\LPN'd\PPR!4Vn*V#uuppi)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'rrr:rNNz4FakeTensor.__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)+rrrsrX,_FAKE_TENSOR_CONSTRUCTOR_IGNORED_STATE_ATTRSrnextiter TypeErrorrrrrrr;rzr ValueError_make_subclassr_allow_unsafe_data_ptr_accessr{_set_throw_on_mutable_data_ptr(_set_warn_deprecated_on_mutable_data_ptrr allow_metarrrrrHrrrrrnested_int_memorCrrr4extractrh)clsrErrrrrrHrrrrrCrF state_dict attr_namerrrspecified_devices first_nameresolved_devicecandidate_devicers&&&&&&&&$$$$$, rN__new__FakeTensor.__new__sR$$sF{+U3 EI NN9d +F d:./JJ."  ' 8 8$)K WXX)I!,!"3V<<#66:;L6M5NP##O) Q <TU U 6" ,.    e  KT:44U\\%5HI J    *;A*> 'J*;B*?*?&&"&66$N%,a'84&BRASU+@ %F.  $$  "/"7D  ] $*  666 HH 3 3D 9 HH = =d C ;;  v % 7 8H8H7IJ ###{{f$$M""   * k: . . !GH H& '+$# &DN  ! ! ! 1 9 9 ;D  O s  L0/L0c$V^8dQhRRRRRR/#)rGargsrXkwargsrJrrL)rMs"rNrOrEs&LLfLL4LrPc <\SV`4\PP 4'dN\P P P'd"\PPV4R#R#R#rR) rrrzcompiler is_exporting_exportconfig#detect_non_strict_fake_tensor_leaksfake_tensor_tlsradd)rrarbrs&*,rNrFakeTensor.__init__EsV  NN ' ' ) ) $$HHH  A A E Ed KI *rPc$V^8dQhRRRRRR/#)rGrrrrrJrrL)rMs"rNrOrNs!((v(.(Z(rPc $VPV4#rR) from_tensor)rrs&&rNrnFakeTensor.from_tensorMs$$Q''rPc ,V^8dQhRRRRRRRRR R /# rGrr?typesSequence[type]raSequence[object]rbMapping[str, object]rJrXrL)rMs"rNrOrSsCL)L)L)L) L) % L)  L)rPc V\PPPPJd\ V4^8wg\ V^,\4'g \R4hV^,PP'd\P!R4#V^,P#\PV4;p'd V!V4#VUu.uF)p\V\4'dKV\JgK'VNK+ ppV'd\ P#RV4\$#Rp\&P(!V/VBF'p \ V \4'gKV PpM Vf \R4h\P*P-\P*P.P04p V 'd\ P#RVV 4\$#VP'd \R4hV;_uu_4V!V/VBuuRRR4#uupi +'giR#;i)rz@Expected exactly one FakeTensor argument for prim.device.defaultrz(FakeTensor unrecognized subclass(es): %sNz,Could not find a FakeTensor in the argumentsz(FakeTensor mode already active: %s in %sz,fake_mode.in_kernel_invocation must be False)rzr(primrr+lenrrrrrr_DISPATCH_META_HANDLERSrj issubclassrnot_implemented_logrrr4arg_tree_leavesr{_get_dispatch_moderr) rWrrrrarbhandlerrunrecognized_typesrargmaybe_cur_fake_modes &&&&& rN__torch_dispatch__FakeTensor.__torch_dispatch__Qs 599>>((00 04yA~ZQ%D%D$VAw  555||F++Aw***.11$7 77 74=  !Jq*$=A!6/AAu     % %:.__annotate__s ( (, (4 (rPc VPR8H#)r_rrs&rN is_device_cpu5FakeTensor._find_common_device..is_device_cpus;;%' 'rPc V^8dQhRRRR/#rrL)rMs"rNrOrs ) )< )D )rPc VPR8H#r1rrs&rNis_device_meta6FakeTensor._find_common_device..is_device_metas;;&( (rPc V^8dQhRRRR/#rGrrrJrKrL)rMs"rNrOrs < .cpu_zero_dims$ *;;quuw!| ;rPc V^8dQhRRRR/#)rGrrXrJrrL)rMs"rNrOrs= O= OV= O= OrPc< \V\4'gR#SfVPoS!V4o R#S!V4pVPS8Xd S 'dVo R#S S9pV'd V'gR#S 'dV'gVPoVo R#S S9d*\\ S SVP344'dR#S S 9d*\\ S SVP344'dR#\ P PPpVeZVSP9pW0PP9pV'gV'dVPoVo R#V'd V'gR#\S SVP4hrR) rrranymaprzrrgfake_tensor_prefer_device_typerr)rt_is_cpu_zero_dim&is_bypass_zero_dim_cpu_tensor_check_opprefer_device_typecommon_has_preferredt_has_preferred$bypass_zero_dim_cpu_tensor_check_opsrrris_cpu_zero_dimrrmeta_rhs_mixed_device_fnsmixed_device_fnss& rN merge_devices5FakeTensor._find_common_device..merge_devicessIa,,$ ! ".q/ ,Q xx=("&7O<< 3 !)O'M ! "3 ''s==!((*CDEE00s>M188+DEFF"'!1!1!8!8!W!W !-'9]=O=O'O$"4 "E+$%HHM&7O)/0mQXXN NrPTr_z!Could not find common device for ) rr) _foreach_copyr+add_r nextafterrrzrr) rrhas_scalar_only_inputsrrrrrrrrrrs f& @@@@@@@@rN_find_common_deviceFakeTensor._find_common_devices !&'    & &  %0 II  % ! 0; NN " "0 , ( ) < <= O= O= O~C #  +4 0 0]5J%) "!LL/M   #DTF!KL L444rPcoeffc V^8dQhRRRR/#)rGrzint | torch.SymIntrJz torch.SymIntrL)rMs"rNrOrs , ," ,  ,rPc VPf"VPPRR7Vn\VP\P 4'g"\ R\VP4 24hVPV,#)N) nt_tensor_idz1Expected nested_int_memo to be torch.SymInt, got )rUrcreate_symbolic_nested_intrrzrrr)rrs&$rNget_nested_intFakeTensor.get_nested_ints    '#'>>#L#L!$M$D $.. == CDI]I]D^C_` ##e++rPcV^8dQhRR/#)rGrJrrL)rMs"rNrOr&s444rPc VP4^8XdVP4#VP4^8Xd VUu.uFqP4NK up#VUu.uFqP4NK up#uupiuupir)rrtolist)rrs& rNrFakeTensor.tolist&sb 88:?99;  XXZ1_,01DDIIKD1 1.23ddKKMd3 323s A9A>)rhrrCrrHrrrrUrrrrrrR)NNNNNNNrL)&rjrkrlrm__doc__rnrrrrrrUrzr{rr _mode_keyrrr:r,rsetterr staticmethodr;r^rrn classmethodr3r#rrrrrorrs@rNrrBs :Q9RL6R')I8O8QK5Q!A.DAO ....33I ==77 K$( K K$$  ]]""!!@@$  },0}26}37}&*} }}bLL(( "$'5'7 L) L)\r5r5h ,%& , 44rPrr6r7T)slotsc]tRtRt$RtR]R&R]R&R]R&R]R &R ]R &R ]R &R]R&R]R&R]R&R]R&R]R&R]R&R]R&R]R&R]R&R]R&R]R&RRltR tR!#)"TensorMetadatai2zC The Tensor metadata relevant to hashing FakeTensors when caching. z torch.dtyperztuple[_MetadataIntLike, ...]shapestriderrr r:ztorch.memory_format | None memory_format_MetadataIntLikestorage_offsetz_MetadataIntLike | None storage_bytesrKrris_conjis_negrr<r is_coalesced int | None dense_dim sparse_dimc(V^8dQhRRRRRRRR/#) rGresult list[object]r rrFr5rJrrL)rMs"rNrOTensorMetadata.__annotate__Js2%%%% %  %rPc \P!V4Fp\WP4p\ V\ \ \P34'd'.pVPWW64VP4Ki\ V\4'dVPW4KVPV4K R#rR) dataclassesfieldsrrrtupler`rzSize_prep_args_for_hashclearrconvert_sym_intr)rrr rFfieldrid_hashed_objectss&&&& rN _flatten_intoTensorMetadata._flatten_intoJs!''-ED**-E%%uzz!:;;35!((Q!'')E6**%%f4 e$.rPrLN)rjrkrlrmrrnrrorLrPrNrr2sv  '' ((  --$$** M LO%%rPrc V^8dQhRRRR/#)rGrrrJrrL)rMs"rNrOrO`s((v(.(rPcVPp\V4pVP'g V'dRpM%\V4pVP VR7'gRpVP 4p\ VPVPV\P8XdVP4MRVPTTTV'gVP4P4MRVPVP VP#4VP%4VP'4VP(VP('dVP+4MRV'dVP-4MRV'dVP/44#R4#)z) Extract the TensorMetadata of a tensor. N)rrL)r:r_has_symbolic_sizes_stridesr is_contiguousrrrrrzr;rruntyped_storagenbytesrrrrrr<rrr)rr:_is_sparse_anyrrs& rNextract_tensor_metadatar`s  XXF(+N  $$$ -a0 ];; M%%'N    - 2 ,:""$       KKKT' T( % $/3% rPc`]tRtRt$RtR]R&R]R&RRltR R ltR R ltR Rlt Rt R#)_DispatchCacheKeyiz( Key for the FakeTensor dispatch cache. tuple[object, ...]rint hashvaluec V^8dQhRRRR/#)rGtuprrJrrL)rMs"rNrO_DispatchCacheKey.__annotate__s##.#4#rPc 2Wn\V4VnR#rR)rhashr)rrs&&rNr_DispatchCacheKey.__init__scrPc V^8dQhRRRR/#)rGotherrXrJrKrL)rMs"rNrOrsNNFNtNrPc d\V\4;'dVPVP8H#rR)rrr)rrs&&rN__eq___DispatchCacheKey.__eq__s%%!23MMEII8MMrPcV^8dQhRR/#)rGrJrrL)rMs"rNrOrs#rPc VP#rR)rrs&rN__hash___DispatchCacheKey.__hash__s ~~rPcV^8dQhRR/#rrL)rMs"rNrOrs$$$rPc |VPF+p\V\4'gKVP4K- R#rR)rrr6strip_shape_env)rrs& rNr!_DispatchCacheKey.strip_shape_envs+A!_--!!#rP)rrN) rjrkrlrmrrnrrrrrorLrPrNrrs. N#N$$rPrc]tRtRtRtR#)SingletonConstantirLN)rjrkrlrmrorLrPrNrrsrPr)frozenrcH]tRtRt$RtR]R&R]R&R]R&]tR]R &R tR #) _DispatchCacheEntryOutputInfoia Entry type for the FakeTensor dispatch cache for an output. Accounts for three possibilities: 1) The op is inplace, and a hit means we need to alias the argument at a given index. 2) We need to synthesize a new FakeTensor given tensor metadata. For view ops, we further capture the index of the arg to alias. 3) if the tensor related fields are None, then it is a constant value (e.g. None or integer) r inplace_idxzTensorMetadata | Nonemetadataview_idxz Any | Noneconstant_valuerLN) rjrkrlrmrrnrrrorLrPrNrrs% ##!2NJ2rPrc4]tRtRt$RtR]R&RtR]R&RtR #) _DispatchCacheValidEntryiz Entry type for the FakeTensor dispatch cache. It supports two types of outputs 1) tensor 2) tuple of tensors is_output_tuple flag helps in differentiating the return type z$tuple[_DispatchCacheEntryOutputInfo] output_infosFrKis_output_tuplerLN)rjrkrlrmrrnr rorLrPrNrrs76!OT!rPrc&]tRtRt$RtR]R&RtR#)_DispatchCacheBypassEntryiz( Entry type for a negative cache entry. rsrrLNrjrkrlrmrrnrorLrPrNr r  KrPr c&]tRtRt$RtR]R&RtR#)_BypassDispatchCacheiz4 Signals cases that should skip FakeTensor caching. rsrrLNr rLrPrNrrr rPrcD]tRtRt$RtR]R&R]R&R]R&R]R&R tR #) DispatchCacheInfoiz? Information about the state of the FakeTensor dispatch cache. rhitsmissesdict[str, int]bypassessizerLNr rLrPrNrrs I K IrPrca]tRtRt$/tR]R&^tR]R&^tR]R&]!] 4t R]R&^t R]R &R t R ]R &R ]R &R]R&R]R&R ]R&Rit R]R&RitR]R&RRRR RRR RRR /RV3RllltRRltRRlt]R R!l4t]R"R#l4t]Rj]!43R$R%ll4tR&V3R'lltR(V3R)llt]R*R+l4t]R,R-l4t]R.R/l4tR0R1ltR2R3ltR4R5lt R6R7lt!R8R9lt"R:R;lt#R<R=lt$R>R?lt%R@RAlt&RBRClt'Rj]!43RDREllt(RFRGlt)RHRIlt*RJRKlt+],!RLRMRNRORPRQRRRS4t-RTRUlt.RVRWlt/RXRYlt0RZR/R[R\llt1],!]2PfPh]2PjPl]2PnPl]2PpPl]2PrPl]2PtPl]2PvPl]2PxPl]2PzPl]2P|P~]2PPl]2P(Pl4 tA],!]2PPl]2PPl]2PP4tFR]R^ltG],!]2PPl]2PPl4tJR_R`ltKRaRbltLR RRcRRdRReR/RfRglltMRhtNV;tO#)kri,dict[_DispatchCacheKey, _DispatchCacheEntry]cacher cache_hits cache_missesrcache_bypassesr FrKr static_shapesryrxz str | None_stackrTnt_tensor_id_counternt_tensor_id_initial_countallow_fallback_kernelsTallow_non_fake_inputsNrHc 0V^8dQhRRRRRRRRRRR R /#) rGr!rKr"rxryrrrHrJrrL)rMs"rNrOFakeTensorMode.__annotate__sX[D[D!%[D $ [D # [D # [D ![D" #[DrPc <\PR\V44\SV`4Wn^RIp^RIpVPPPVn \VPVR7Vn VeW@nM VRJVnRVnVPPP VnVPPP$VnVP(PP*;'dVP'*VnVP(PP.VnW nRVn.VnW0n\:P<!4VnRVn VPBPDPFVn$^RI%pVPLPNPPPRVn*VPTVn+R#)zcreate_mode 0x%xN)rIrHF),logridrrr!torch._dynamo.configtorch._functorch.configrrg"fake_tensor_propagate_real_tensorspropagate_real_tensorsr@fake_tensor_converterrallow_scalar_outputs(fake_tensor_allow_unsafe_data_ptr_accessrQfake_tensor_allow_metarT_dynamofake_tensor_cache_enabledr$fake_tensor_cache_crosscheck_enabledcache_crosscheck_enabledr"r enter_stackrx traceback extract_stack _stack_tracerr{rrr$torch.nested._internal.nested_tensornested _internal nested_tensor_tensor_id_counterr r)rr!r"rxrrHrzrs&$$$$$ rNrFakeTensorMode.__init__s$ $bh/ &<##&    # # F F #&911& "  $!. !*d!2D %*!    # # L L * **11HH MM : : 0 0///  MM E E % &;"%*!VX"%335 77<<3 LL " " 0 0 C C '%)$C$C!rPcV^8dQhRR/#rrL)rMs"rNrOr$msDDDDrPc (VPVnR#rR)r rrs&rNreset_nt_tensor_id_counter)FakeTensorMode.reset_nt_tensor_id_counterms$($C$C!rPc V^8dQhRRRR/#)rGrrXrJzTypeGuard[FakeTensor]rL)rMs"rNrOr$|s  V (= rPc N\V\4;'dVPVJ#rR)rrrrrs&&rN is_our_fakeFakeTensorMode.is_our_fake|s, :  $ $ t#  rPcV^8dQhRR/#rrL)rMs"rNrOr$s   4  rPc \PP4'dS\PP4'd \ R4h\PP 4'*#\PP 4;'gI\ \R4;'d'\PP 4;'g \4'*#)z&Cannot have both xpu and cuda compiledrv) rzrw _is_compiledrur is_availablehasattrrvr!rs&rNavoid_device_init FakeTensorMode.avoid_device_inits 99 ! ! # #zz&&(($%MNNyy--// / JJ # # % 3 3u%BB%))*@*@*B 3 302  rPcV^8dQhRR/#)rGrJrsrL)rMs"rNrOr$ssrPc VPf5RP\P!VP44VnVP#)N)rjoinr5 format_listr7rs&rNstackFakeTensorMode.stacks7 ;; '')"7"78I8I"JKDK{{rPc ,V^8dQhRRRRRRRRR R /#rqrL)rMs"rNrOr$s<  %   rPc \PP\PPP4e\ RV 24hVP WW44# \d\PR4hi;i)Nz2FakeTensorMode should not be set when dispatching zfake tensor raised TypeError) rzr{r}rrrdispatchrNr& exception)rrrrrarbs&&&&&rNr!FakeTensorMode.__torch_dispatch__su 88 & &uxx'E'E'J'J K W DTFK  ==d; ;  MM8 9  s A%%"BcV^8dQhRR/#)rGrJr rL)rMs"rNrOr$s4rPc <^RIpRpVP'dPVPP4pVPP R4VPP 4VPP VP4pWJd,VPPRW234\SV`-4#VPPV4VPPRRV34V#)rNTF) r8rLr{_only_lift_cpu_tensors_set_only_lift_cpu_tensors_ensureCUDADeviceGuardSetrrr4rr __enter__r)rrzprev_only_lift_cpu_tensorsmaybe_prev_fake_moders& rNr_FakeTensorMode.__enter__s3%)"  ! ! !).)H)H)J & HH / / 5 HH . . 0$xx<TP4R8Xd)\PRT^,TP4\PTP;;,^, uu&Rp?ELZRp?ii;i +'giT #;i \dp\ T\ P P4'd>TP4R8Xd)\PRT^,TP4\PTP;;,^, uu&T !Y\-TP44T uRp?#Rp?ii;i)z Lookup a cache entry for the given arguments. If none exists, dispatch and cache the result (if the result is eligible for caching). 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Raises _BypassDispatchCache if the output tensor has characteristics that prevent caching it. )hops_that_skip_faketensor_cacher)has_free_unbacked_symbolsc3<"TF?p\V\P\P34;'d S!V4xKA R#5irR)rrzrr)rors& rNr3FakeTensorMode._make_cache_entry..sE"q5<<">?551!45!s 5A A TFzunbacked symbol in HOP z output or z# in hops_that_skip_faketensor_cacheNrr)rrrrrrrrzr}r~rrrrrrrrrr)rrFrrrarbrrrouts non_cacheable output_info out_elementout_elemrrs&&&&&&& @rNr 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 sGc 0V^8dQhRRRRRRRRR R R R /#) rGrFr5rrrrrr?rartrJrfrL)rMs"rNrOr$ sNQ8Q8Q8-Q8 Q8  Q8  Q8 Q8rPc  aaaVPfHVPf:VPf,VP\Jd \ R4hVP#VPe6WRP,p\ V\4'g \ R4hV#VPpVfR#\V4'd \ R4hRV3Rllo\;QJd".VV3RlVP4FNK 5M!VV3RlVP44p\;QJd".VV3RlVP4FNK 5M!VV3RlVP44p S!VPS4p VPeS!VPS4\Pp VP eVP P"p \%V4;_uu_4V !4;_uu_4\&P(!VV VP*VP,RVP.R 7p RRR4RRR4VP0'd!\&P2P5X R 4VP6'd!\&P2P9X R 4\ V\&P:P<4'dVP>'dV\A\BVP4,p \ V \4'g \ R 4hV PE4p\%V4;_uu_4V !4;_uu_4X PGWW4RRR4RRR4\VX VPH4# +'giELh;i +'giELt;i +'giLW;i +'giLb;i) Nz2entry.constant_value must not be SingletonConstantz inplace_arg must be a FakeTensorz)Sparse tensors are not supported in cachec$V^8dQhRRRRRR/#)rGrrrFr5rJr'rL)rMs"rNrOHFakeTensorMode._get_output_tensor_from_cache_entry..__annotate__# s"  /  ; rPc<\V\4'd6VPf \R4hVP SVP4#\V\ 4'd \R4hV#)Nz6state.shape_env must not be None for _SymIntOutputStubz Unexpected _PySymInputStub value)rr7rxrrVr6)rrFrs&&rN check_valueGFakeTensorMode._get_output_tensor_from_cache_entry..check_value# s`%!233??*(P}}S%//::e_55()KLL rPc36<"TFpS!VS4xK R#5irRrLrrrrFs& rNrEFakeTensorMode._get_output_tensor_from_cache_entry../ sD^k!U++^c36<"TFpS!VS4xK R#5irRrLrs& rNrr0 sFo{1e,,orr)rr:rrTzview_arg must be a FakeTensor)%rrrrrrrrrrrrrr contextlib nullcontextrxsuppress_guardsrrz empty_stridedrr:rrr{ _set_conjr_set_negr}r?rrrrset_r)rrFrrrra inplace_argrrrrmaybe_suppressrview_argstoragers&f&f&& @rN#_get_output_tensor_from_cache_entry2FakeTensorMode._get_output_tensor_from_cache_entry s    %&&##'88$H'' '    (001Kk:66$%GHH >>    " " !LM M  DX^^DDX^^DDFhooFFhooFF$X%<%> %!^^;;N )$ / /1A1A''nn&44 E2B /     HH  ud + ??? HH  eT * dEJJ11 2 2t|||Denn56Hh 33$%DEE..0G-d33^5E5E 7EB6F3$x7712B1A1A / / /*6F5E33sHN.;N )N>ON0 !O N  N N- 0 O ;O O c 0V^8dQhRRRRRRRRR R R R /#) rGrFr5rrrrrr?rartrJ1FakeTensor | None | tuple[FakeTensor | None, ...]rL)rMs"rNrOr$U sF(      ;rPc  VP'd8VPUu.uFpVPWW4V4NK pp\V4#VPWP^,W4V4#uupi)z/ Create a new FakeTensor from the cache entry. )r rrr)rrFrrrraroutputss&&&&&& rNr'FakeTensorMode._output_from_cache_entryU s  $)#5#5 $6K884$6  > !;;))!,c sA.c 0V^8dQhRRRRRRRRR R R R /#) rGrrrr?rrrsrartrbrurJrrL)rMs"rNrOr$n sF22A22 2  2 % 2 2rPc  aRV3RlloVPW#WE4pS!Ya4R# \dp\RT RT RT RT 24ThRp?ii;i \dp\RT RT RT 24ThRp?ii;i)zn Helper to validate that the output synthesized from the cache matches the output created by normal dispatch. c$V^8dQhRRRRRR/#)rGarbrJrrL)rMs"rNrO=FakeTensorMode._crosscheck_cache_output..__annotate__{ s& B BS BS BT BrPc<\V\4'd\V\4'g\R\V4 24h\ V4\ V48wd$\R\ V4 R\ V4 24h\ W4F wr#S!W#4K R#\V\ 4'd0\V\ 4'dW8wd\RV RV 24hR#VfVe\RV 24hR#\V\4'dF\V4\V4JgVPVPJd\RV RV 24hR#\V\P4'dJ\V\P4'g\R\V4 24h\\W4R#\R\V4 24h) zExpected tuple, got zTuple length mismatch: z != zInt mismatch: NzExpected None, got zSymType mismatch: Expected Tensor, got zUnsupported type )rrrrrxziprr(r rzrrr RuntimeError)rrlr  assert_helpers&& rNr">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#@AArPz*FakeTensor cache crosscheck failure: func=z, args=z , kwargs=z: Dispatch raised=N)r Exceptionr ) rrrrrrarb true_outputrr"s &&&&&& @rNr'FakeTensorMode._crosscheck_cache_outputn s B B0 --d4HK   + .   #\ R S R S R\T4 RS 24S hRo > ii;i \ d|o \PPP'd)\R T T3RlR 7\SSS4R3uRo > u#\ RT RT R\T4 RT RS 2 4S hRo > ii;i \ d'o \ RS RS R\T4 RS 24S hRo > ii;i)z Helper to cross-check fake/real output properties & values, and create new fake vals if mismatched. Returns tuple of object & boolean, for whether or not it was overwrriten N)_check_fake_real_tensorsc$V^8dQhRRRRRR/#)rGrrr2rJrrL)rMs"rNrO6FakeTensorMode._maybe_infer_fake..__annotate__ s!   3 4 rPc<\V\\34'EdSPf \ R4hVP P PSPPP4, SPPP4, 'gnSPPSPVP P V4RR7SPPJd\RV RV R24hR#R#\V\ \"\$34'dW8wd\RV RV R24hR#R#)Nz3self.shape_env must not be None for symbolic valuesT) compute_hintmismatch between fake value  and real value r))rrrrxrr expr free_symbolsbacked_var_to_valrreal_tensor_prop_unbacked_vals_maybe_evaluate_staticEqStruerrfloatrK)rr2rsympys&&rN_check_fake_real_vals?FakeTensorMode._maybe_infer_fake.._check_fake_real_vals s?$ 233>>)(M 33nn66;;=>nnCCHHJKK ==!HHTYY^^T:> %ww||, 4:4&@PQUPVVWX , KsE4(</6tf2FakeTensorMode._maybe_infer_fake.. s #d)$cjj-rP metadata_fnzFReal tensor propagation found a metadata mismatch between fake tensor z and real tensor z , at outputz , for func: c6<R\S4RSP/#rMrOrPsrNrRrS s $c$i (#**1rPzIReal tensor propagation found an output size mismatch between fake shape z and real shape z , at outputz.size(z ), for func: c.<R\S4RRS RS 2/#)rNrr9r:rs)rrr2srNrRrS s'c$i $@FVW[V\"])rPzQReal tensor propagation found an output value mismatch between fake output value z and real output value )rDtorch._subclasses.fake_utilsr4rrzrrrrg*generate_fake_kernels_from_real_mismatchesr_infer_fake_from_real_tensorr.rrr) rrr1rr2r4rEjs_fakes_realrQrDs ff&ff @@rN_maybe_infer_fake FakeTensorMode._maybe_infer_fake s I  < dELL ) ) (;!#'"'2(1TYY[$))+1N'O##F)&9(PTU{1\d.&&QQQ!,!4D$EtKK'#f$5dV<#D\N,tf>   %dD1U{u) ##**UUU%0%8dDI4OO+##'&(9$@!!'l4&B  &-''..YYY)4) s-vO B) +))-.EdVL &t ~\$A  saDF H$ F"A F,F2!FF H!&A H0H!8$HH!$ I/!IIc 0V^8dQhRRRRRRRRRRRR /#) rGrr?fake_inrXreal_infake_outreal_outrJz object | NonerL)rMs"rNrOr$4 sNJ=J=J=J= J=  J=  J= J=rPc  aaaa^RIHpRoSP'd \SPP4oRVV3Rllp\ P V4wr\ PV4wrV!RWSWB4\\Y4U U Uu.uFwwrpSP!SYT4NK upp p !wpp\#T4'dS'dT!4\ P%Y4# \dto\PPP'd0\RTT3RlR7T!4\TT3R lT4uRo>#\R T R T R S 24ShRo>ii;iuupp p i) z Helper to cross-check fake/real output properties & values, and create new fake vals if mismatched, but at the kernel level. Means this handles pytree outputs & checks aliasing. )_check_alias_infoNcV^8dQhRR/#rrL)rMs"rNrOMFakeTensorMode._maybe_infer_fake_kernel_from_pytree_out..__annotate__H s   rPc<\\SPP4P S44SPnR#rR)r`setrxpending_fresh_unbacked_symbols difference)pending_unbackedrsrN_clear_pending_unbackedXFakeTensorMode._maybe_infer_fake_kernel_from_pytree_out.._clear_pending_unbackedH s4<@DNNAABMM$=DNN 9rPrGrKc<<R\S4RRSP 2/#)rNrz>Mismatched aliasing spec between fake kernel and real kernel: rOrPsrNrRIFakeTensorMode._maybe_infer_fake_kernel_from_pytree_out..[ s&c$i \]`]g]g\hi)rPrTc<\SSV4#rR)r[)rrrs&rNrRrrg s:4qIrPzGReal tensor propagation found an aliasing mismatch between fake output z and real output z , for func: )rYrgrxr`rlr4tree_flatten_with_path tree_flattenrrzrrgrZrr0rr_rtree_unflatten)rrrbrcrdrergrofake_paths_leaves fake_spec real_leavesr _fake_path _fake_out _real_out fake_leaves overridesrQrnsff&&&& @@rN(_maybe_infer_fake_kernel_from_pytree_out7FakeTensorMode._maybe_infer_fake_kernel_from_pytree_out4 sy C  >>>#DNN$Q$QR   (.'D'DX'N$,,X6   /H >"%;>%;;6+ZY&&tZIN;"  Y  NN/ # %$$[<>\4;QJdRV 4F 'dK RM RM !RV 44p\-S\PHPJ4'Ed\PLPNSPP9Ed\PLPRSPP9g S\"PTP&JEdvV'Edm\EV 4^8wEd\S4'EgSV 'EgJS\"PVP&JEd+S2Uu.uF(pSPV4'd VP8MTNK* pp\P;VS.4wpp\?4;_uu_4S!V/VBpR R R 4\PYX4pVU u.uFp \-V \.4'gKV NK pp \4;QJdV3RlV4F 'dK RM RM!V3RlV44pV'd!\P[\.V0V3RlV4#VFpS0P]V4K \P;S2S.4woo\-S\PHP^4'dzSV9dsSP`f\bPdMSP`PfpS;_uu_4V!4;_uu_4VS,!S/SBuuR R R 4uuR R R 4#SPiSV SS4RV3Rllp^RI5H6o/H7o3\q4o5S5o8SPr'Ed@\4;QJdRV 4F 'dK RM RM !RV 44'Ed\;QJd!V3VV93RlS24F 'gK RM RM!V3VV93RlS244'g\tPRS4S2Uu.uF pV!V4NK pp\P;VS.4wo6o7\vPx!S4pV'g\vPz!SVS.4pS!S6/S7Bo8V'g3XP4\vP!SPS2S84MSSPr'dB\tPRST S2SP`'dSP`PMR 4RVV/V3VVV5V6V7V8V3 RllpS4'd0\4PS4pVeV!V!S.SO5/SB4#S\P P"PP&Jdr\ES4^8d S^,MSPR4pSPR4p \SS^,VV R7p!V!\JdV!\\V!44#^R IIHJp"SV"9dSPS4'gS4'dSSP9g^R!IIHMp#SV#9d~S4'gL\S4'de\4;QJdR"V 4F 'dK RM RM !R"V 44'd+S;_uu_4V!V#S,!S/SB4uuR R R 4#S;_uu_4SP!S/SBp$V$\JdV!V$4uuR R R 4#R R R 4R#SPP9dQ\SR$4'd?\S4'g.S;_uu_4V!SP!S/SB4uuR R R 4#\PPPp%V%e)SV%P9dV%P!SS.SO5/SB#SPr'dsS8S5Jdm\vPx!S4'gQSP`eC\vP!S4'g'\SSS84p&\R%V3R&lR'7V!V&4#\PPPPSP44PPp'V''d\PPPSS4o1\PPPV13R(l4;_uu_4S;_uu_4V'!S/SBp&V!V&4uuR R R 4uuR R R 4#\F7wp)p*V)!S4'gKV*!SS.SO5/SBp!V!\JgK/V!V!4u# R.R*VV.V2VV4VV3R+lllp+\S4'gV+!4p,V!V,4#\S4;_uu_4S!S/SBp$R R R 4T!SPX$SS2SPR4R-74#uupiuup iuupi +'giE Ls;iuupi +'giELg;iuup i +'giM;iR R R 4EK +'giEL(;iuupi \|d#p\tPRST4R p?ELR p?ii;i +'giEL;i +'giEL;i +'giELc;i +'giM;iR R R 4EK +'giEL;i \dup(SPr'd\S8S5JdV\vPx!S4'g:SP`e,\SSS84p&\R%T3R)lR'7T!T&4uR p(?(#T(hR p(?(ii;i +'giEL;i \dp-T+!T-4uR p-?-#R p-?-i\d\tPR,S4hi;i)/rrz,FakeTensorMode unrecognized subclass(es): %sc38"TFqPxK R#5irR)r)rrs& rNr0FakeTensorMode._dispatch_impl.. s! 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3H! SSS! 3H!  ;; S: :SSS: : : .. t}},  %  ! ! ! //777&8$))U2'+$uyy11999'+$ EIINN++33 3 . .47ELL1 . .Q##v--"-"" * !6 +D 1 1&&))553M7LM333M7LMMM$fJKCLBKQd..q11 q8) (.'<'<_i'X $J  3l3CCyF"t':':3'?'? !]]))+C# 11$41PP 6{a3t9>$GvXV\U]^DG}& 11$Q@@.2-W-W )Y . *) &sQ;PQsssQ;PQQ tUZZ22 3 3 11B &&dii744<>)&&^^AA 0 :<<.t4dEfE=< ,,T3H$PVW  ( h  ' ' 'M7LMM7LMMMC # CCC #    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:OPP:OPPPT7+D14B6BT NND3F3N*7: + ** *.//'--3''88 =='';;  x}}$33D$PPPP  ' ' '#!,,T22*!0066;D$Q!)! 4F;; ..88BBGG IIK )FF   nn..::4F^^--<<[II44,d=f=F7?LP4II8(A #NGd##%dDB4B6B n47 DD (A P P P(~~02H/9 9  -d33$)&)4,  < <46::h+? =   u"!Nb#]]j N<=<dJ%  O  rTT "HLP4IIII$ /// +)44T::2?dHUF%-% 8??G' x433" D,-BC C  MMF M  scw* w*w//w/1w4 w4>w9x ,x + xx&2x&>y x+  y y2y"z$z&z:A|9 {,{  {, |~/ ~8~9 x  x# + x; 6y  y " z-z  z z# & z7 : {  { {,!|, {= 7|=| }? 3}:?3}:2}?8}::}? ~ ~~ !~.(. ; debugprimsrr)xlavision torchtext torchaudio quantizedc V^8dQhRRRR/#r&rL)rMs"rNrOr$ s   J  4  rPc VP'gR#VPVP9;'gVP4R8H#)Fz fbgemm::gmm)r! namespace+_can_run_unsafe_fallback_allowed_namespacesrrrs&&rNr&FakeTensorMode.can_run_unsafe_fallback sB*** NNdNN N , ,yy{m+ rPc ,V^8dQhRRRRRRRRR R /#) rGrr?rr@rrtrr2rJz%tuple[list[object], list[FakeTensor]]rL)rMs"rNrOr$ s<454545'45$ 45  45 / 45rPc laaaaaa.oRVVVVVV3RllpSUu.uF qe!V4NK ppVS3#uupi)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 V^8dQhRRRR/#)rGrrDrJT | FakeTensorrL)rMs"rNrOJFakeTensorMode.validate_and_convert_non_fake_tensors..__annotate__ s# # # n# rPc<\V\4'gV#S PV4'Eg\S R4'dZ\P P S P9d1\PS S4wr\R\S W4 24h\Pf S PM\PpV'gj\V\4'd$VP pVS Jd\RV RS 24h\PS S4wr\R\S W4 24hSP#S V4pMTpSP%V4V#)rzECan'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 )rrrErKrzrrrr4rvrr"rirr"rrrr) rrarbr" x_fake_moderrrrrrrs & rNvalidateFFakeTensorMode.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 ! ( ( -JrPrL) rrrrrrrvalidated_argsrs fffff @rNr4FakeTensorMode.validate_and_convert_non_fake_tensors sA35# # J099y!(1+y9444:s1c ,V^8dQhRRRRRRRRR R /#) rGr rXrr?rrtrrrJr/rL)rMs"rNrOr$ s<=!=! =!=!$ =!  =!  =!rPc  taaaaaaaa a SPoRoRoRo Ro S\PPJgS\PPJdE\ S4^8Xd5\ S^,\4'dS^,Po S RJo RVVVVVVV V V3 Rllp\WQ4#)NFc V^8dQhRRRR/#rGrrDrJrrL)rMs"rNrOPFakeTensorMode.wrap_meta_outputs_with_default_device_logic..__annotate__ s% % A% .% rPc< a\S\4'gS#Sf\PSS4wooS P S4pV'dI\ P !SPS8HVV3Rl4S 'dS Sn\\S4#SeJS'dSPS S4pMSPS SS;'gS4pS 'dS VnV#S#)Nc(<RSP RS 2#)z-FakeTensor is wrapped to wrong device, found z , expected r)rrsrNrRZFakeTensorMode.wrap_meta_outputs_with_default_device_logic..wrap.. sKAHH:U`an`oprP) rrrrrErz_checkrrHrrDrr) rrErrrrrrrinput_dispatch_keyspreserve_dispatch_keysrs f rNwrapHFakeTensorMode.wrap_meta_outputs_with_default_device_logic..wrap sa(($224C!***1-K HH -p*&9AOAqz!&)$44T1=C#88a!8!8=C*(;C% rP) r,r)aliasr+detachrxrrrHr0) rr rrrr*rrrr(r)s f&fff @@@@@rNr:FakeTensorMode.wrap_meta_outputs_with_default_device_logic s..  !&!&" TZZ'' '44;;3F3F+FI!#9Q<44"+A,"<"< %8%D "% % % N  rPrc V^8dQhRRRR/#)rGrrrJr'rL)rMs"rNrOr$% s) rPc ^RIp^RIHpVfCVPpVP'g \ R4hV;P^, unVP !V!V^44pVPPPR4pVPf \ R4hVPPVPPVVR7VVR7pV#)rN) NestedIntNodez4should only be called while FakeTensorMode is activeintermediate_offsets_or_lengthszself.shape_env must not be None)valrs)symrrs) r8!torch.nested._internal.nested_intr1rr4rrr0rsEphemeralSourcerxr create_symbol)rrrzr1rsrcrets&$ rNr)FakeTensorMode.create_symbolic_nested_int% s 4C  44L###$J  % % * %||M,:;mm""223TU >> ! !BC Cnn..,,- /  rPc V^8dQhRRRR/#r&rL)rMs"rNrOr$X s66Z6D6rPc t\PPVP9dR#WP9#r)rzr view_copyr_cpp_meta_supports_symintrs&&rNr'FakeTensorMode.cpp_meta_supports_symintX s* 99  $)) +5555rPc V^8dQhRRRR/#rrL)rMs"rNrOr$_ s   4 rPc VP4\8*;'dP\V4'*;'d8VPV4'*;'dVPP R8g#r1)numelCONSTANT_NUMEL_LIMITrrErrrDs&&rNrFakeTensorMode.may_turn_const_ sb GGI- - ( (!!$$ ( ($$Q'' ( ( '  rPc ,V^8dQhRRRRRRRRR R /#) rGrr?rzSequence[FakeTensor]rartrbrurJrrL)rMs"rNrOr$g sCWWW 4W W % W  WrPc .\;QJdRV4F 'gK RM RM !RV44p\V4pV'dVP4'd\VVVRR7wrxVP 4FwrV R8wgVP V 4'dT MRp VP V 4'gK@VPV 4'gKYV PfKiVPPV P4K R#R#R#)c3<"TFqPRJxK R#5irRrrs& rNrAFakeTensorMode.invalidate_written_to_constants..n rrTFrinputrN) rr$ is_mutabler$r has_argumentrErr,r[) rrrrarb any_constant schema_inforrkrs &&&&& rNr.FakeTensorMode.invalidate_written_to_constantsg ssQ;PQsssQ;PQQ %d+ K2244.-1 MA #((*w,+*B*B1*E*EAF$$Q''#..q11 ...JJ1::V+5viewrslicerrr lift_freshlift_fresh_copyrrrrnrorrs@rNrrsd:  3/  45l=!~,0<!,    "" ''       !! $$ // 55==  !+6  !! +' 6 4??22D4H4H4P4PQH W2" &* " !% " 48 " " " rPrc$V^8dQhRRRRRR/#)rGrFr5rrrJrrL)rMs"rNrOrO s):Q:Q :Q#-:Q :QrPc<^RIHpHp\PP P P4RJpV'dV!V4F p\R4h R#V!V4F1pVPFpWpP9gK\R4h K3 R#)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. )_iterate_exprs_iterate_nodesNzProxy mode with SymNode outputzunrepresented symbol in output) rr_r`rzrrrrrr<r)rFrr_r`rrrrs&& rNrr sZU&&33BBDDPJ 'A&'GH H( 'A..!4!44./OPP)(rPc 0V^8dQhRRRRRRRRR R R R /#) rGrrrr?rrtrr/orig_not_implemented_exceptionr rJrrL)rMs"rNrOrO sD>'>'>' >' >' >' %1 >'  >'rPcZaaa a \PPVP9dSh/o \ 4;_uu_4RVV 3RllpVUu.uF qe!V4NK pp\ P W#4wrxV!V/VBp RRR4\4o VFWp \V \4'gK\V 4'dK.S PV P4P4KY RVV VV 3Rllp \ PV X 4#uupi +'giL;i)c V^8dQhRRRR/#)rGrrDrJz T | TensorrL)rMs"rNrO)run_fallback_kernel..__annotate__ s  a J rPc<SPV4'dc\P!WPR7pVP'd VP VP 44VS\V4&V#V#)r)rErz zeros_likerr< _coalesced_rr')rrr inp_implss& rNto_real_tensor+run_fallback_kernel..to_real_tensor s\$$Q''&&q?;;;OOANN$45%& "S'" HrPNc V^8dQhRRRR/#r"rL)rMs"rNrOres1rPc`<\V4S9dI\V\4'd3\V4'g"VP 4P S9dSh\V\4'd?\V4S9dS\V4,#SP PSV4#V#rR)r'rrrrP_cdatar,r)rrrirbstoragess&rNmap_out$run_fallback_kernel..map_outs a5 ! q& ! !!!$$  "))X50 0 a !u ! A'' 66GG STUUHrP)rzrrrr)r4rvrkrrrrjrPrnr0)rrrrrbrjrrarbr rrprirosf&&&f @@rNrr s yy*,,I   1:: 1^A& :,,YB  $ !& !  &)UH  a  ## Q--/667 ??7A &&C; sDD#!DD D* c(V^8dQhRRRRRRRR/# rGrrrrr_DispatchCacheEntryrJrrL)rMs"rNrOrO's0 7   rPc.VP4W V&R#rR)rrrrs&&&rNrr's #JrPc(V^8dQhRRRRRRRR/#rsrL)rMs"rNrOrO0s0 7   rPcW V&R#rRrLrvs&&&rNrr0s #JrPc2]tRtRtRRltRRRlltRtR#) FakeCopyModei:c V^8dQhRRRR/#)rGrrrJrrL)rMs"rNrOFakeCopyMode.__annotate__;s##.#T#rPc WnR#rRr)rrs&&rNrFakeCopyMode.__init__;s"rPNc ,V^8dQhRRRRRRRRR R /#) rGrr?rrrsrartrbzMapping[str, object] | NonerJrrL)rMs"rNrOr|>s< - - - - - , -  -rPc V'dTM/pV\PPPJdg\ V^,\ 4'g\ R\V^,4 24hV!VPPV^,RR73/VB#V\ PJd\V4^8wg\V4^8wd%\ R\V4 R\V4 R24h\\ V^,4p\\\\3,V^,4p\!V4V9dV\!V4,#VPPVRR7pWv\!V4&V#\PP#4;_uu_4V!V/VBuuRRR4# +'giR#;i)rrT)rz3Expected 2 args and 0 kwargs for __deepcopy__, got z args and z kwargsN)rzr{ TensorBaserrrrrrrn __deepcopy__rxrrrrr'DisableTorchFunctionSubclass)rrrrrarbrVmemors&&&&& rN__torch_function__FakeCopyMode.__torch_function__>su"r 588&&,, ,d1gv..$'>#3>>rPcj\;QJdRV4F 'gK R# R#!RV44#)c38"TFp\V4xK R#5irR)r)rrs& rNr&_check_for_subclass..}s=9a&q))9rTF)r)rs&rNrr|s+ 3=9=33=3=3=9= ==rPc V^8dQhRRRR/#)rGrrXrJrKrL)rMs"rNrOrOsv$rPc8\V\4'dR#\V\4'gR#\V4pV\JdR#\ V\ P P4;'dVP\PJpV'dR#R#)FT) rrrrrzrzrrr)rx_type#is_metadata_only_parameter_subclasss& rNrrs|!Z   a  !WF  6588--. C C  % %)B)B B(+ rPc\;QJd7.R\\V^,4P44FNK 5#!R\\V^,4P444#)c38"TFp\V4xK R#5irRrrrs& rNr..s441A4r)rrrrrs&rNrRrRsVee4VT!W-2244e/e4VT!W-2244/rPc\;QJd7.R\\V^,4P44FNK 5#!R\\V^,4P444#)c38"TFp\V4xK R#5irRrrs& rNrrs661A6r)rrrrrs&rNrRrRsV6VT!W-446616VT!W-44661rPc^\\\V^,4P44#r)rrrrrs&rNrRrRs  VT!W,,.9rP) _device_not_kwarg_ops_is_tensor_constructor_like_tensor_constructorscontains_tensor_typesrrrrrc V^8dQhRRRR/#)rGrrrJrrL)rMs"rNrOrOs&&%6&4&rPcrV\P9d"\PPV4R#R#rR)rrrrs&rNrrs) n"""  %#rPcV^8dQhRR/#rrL)rMs"rNrOrOs ; ;$ ;rPc\PR4\PR\P4\PR\P4\P pV'dq\PR4\ RV44p\VP4RR7F'wr#\PRV^,V R2V4K) R #R #) zFakeTensor cache stats:z cache_hits: %sz cache_misses: %sz cache_bypasses:c38"TFp\V4xK R#5irR)rx)rrNs& rNr#dump_cache_stats..s-HqCFFHrcV^,)#)rrL)rs&rNrR"dump_cache_stats..s AaD5rPrz %-*s %sr>N) r&inforrrrmaxsortedr)rwidthrNrs rNdump_cache_statsrsHH &'HH !:!:;HH !>#>#>?,,H $%-H--8>>+ADA HH]EAI!Aw :BrPc(V^8dQhRRRRRRRR/#)rGr rrNtorch._ops.OpOverloadrez torch.TensorrJrL)rMs"rNrOrOs,9 9 9 39 ?K9 9 rPc ~aRV3RllpVP4^8wdV!RVP4 24\VP44Uu.uF6p\PP P VP4NK8 ppR .VP4,p\VP44UUu.uFwrxW3NK p ppV PRR7^p T p V F^wrW8wd(V!RVP RVP4 R24WV&WPV,,p WV,,p K` V;_uu_4\P!VVVPVPVPR7uuR R R 4#uupiuuppi +'giR #;i) c V^8dQhRRRR/#)rGrrsrJrrL)rMs"rNrO2_infer_fake_from_real_tensor..__annotate__s  C D rPc<<\RSP RV R24h)zQpropagate_real_tensors: we cannot infer a Fake kernel (meta kernel) for operator z because z>. Please use torch.library.register_fake to add a Fake kernel.)r r)rrNs&rN unsupported1_infer_fake_from_real_tensor..unsupporteds1**,((9VHEK L  rPz'a return has a non-zero storage offset c(V^,V^,)3#rrLrs&rNrR._infer_fake_from_real_tensor..s!qte}rPrz(a return was not dense in memory (sizes z strides ))rrr:Nr)rrrrzrr allocate_sizerxrrsortrrrrr:) r rNrerr fake_shape fake_stridesrrrJexpected fake_strides &f& rNr[r[s   A%5h6M6M6O5P Q x||~&&A   ..t~~>&4(,,.(L&/0A&BC&BFCx&BGC LL,L-HK = :8>>:J)T\TcTcTeSffgh (SnnS11!sO3  ""  ??..??   5D s.sBMqz!U\\**Ms')FTzPpropagate_real_tensors: we don't support operators that return non-Tensors. Got ) rxrr4rurr r"r[rv)r rNre real_flat_outspecr fake_flat_outs&&& rNrr s ~~>?? !--h7M 3BMB333BMB B B " | -  IVV 11$A> MV   55WsB3) __future__ratexitrrrr+rr threadingr5rrtypingr collectionsrrrrrr r r r typing_extensionsr rrrrztorch._library.utilsrrrrrrrtorch._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_utilsr5r6r7collections.abcr8r9r:r;r<r= torch._guardsr> torch._opsr?rr@rA getLoggerrjr&_logginggetArtifactLoggerrr{rOrrsr`DimList_pytreer4rDr}r(r)rCrr{_dispatch_key_parserTrUrW frozensetrnrKrr}rr rrrrrrrlocalrrircontextmanagerrrrrrr rrrr$r/r7r>r@rrrrrrrrrrrrrr rtr$rrrrX_StoragePointerrrrrrzrrrrwrr+rrrryrrrprofiler_record_function_exit_RecordFunctionr-torch._subclasses.fake_implsrrrrrrrrrrregisterrr[rrLrPrNrs0"   #!OOO55! ,,33T4?8,5H98;-1/ WV$4RRPP#$%O !  ) )(4J K..::8EVW     CL zz~~xx33K@Q%*09&660,   \   L   ,  <  <  <  L GIOOG /& -- ,,&A F F    ..  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