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" ""s+*E- A E-0E-E-:E-AE--E9c |j|j5|jD]}t|tj j s)i}i}t|jjD]}|jdk(r|jtjur|j\}}||d|} | |vrc|j|| |D].} | j | j j||| 0|jj#|||| <| ||<|j$||< dddy#1swYyxYw)NrQ.)rRrSmodulesrrrrr]rrr}roperatorgetitemrhrXrerZrQ) rrmodule_call_graphrnode_idgetitemsr$rLidxnew_identrys rW _common_getitem_elimination_passrgIsG  o>>@ A.jjl .Ffehh&:&:;02G13HV\\//0 .77o-$++AQAQ2Q"&))KFC '0#7F)228F3CD%6"E$: % E E$((6*:!""  //5+/((. $(IIGDM! .  ....sC E.AEEold_gmold_graph_signaturerold_module_call_graphchtj|}|jjDcic]}|j|}}ij j i|j |j }i} d} |jjDcgc]}|jdk(s|j } }ttfd| } |jjDcgc]}|jdk(s|j } }|jjD]}|jjdgx} r|j| | dj<?|jdk(sO|j|vr^|j|jvrw|j| vst|jts!t!dt#|j| | }t|tst!dt#||j| |<| dz } t%t}|j'D]X\}}|j)d s |vs|| |<"d j+|j-d dd}||j/|Z|D]x}|j0}|g|j2|j4D]H}|j|vrt7d |jd |j| vr| |j|_N|j|vs]||j}|jd k(s||jt8j:j<j>j@t8j:j<j>jBt8j:j<j>jDfvs|jFdj}|| vrt7d |d | ||_K{|Scc}wcc}wcc}w)Nrrc,|vxr|jvSrP) input_tokens)xold_graph_params_buffersris rWz0_get_updated_module_call_graph..s$a77:,999rY from_nodez"expected node.name to be str, got z!expected old_name to be str, got r7zparametrizations.r]zIt looks like z is a tensor subclass. Preserving submodule that takes subclass parameter is not supported in inference IR because we desugar them, resulting in more tensorsrQ)$rdeepcopyrrrQrrr}rr]filterrrrmrrarrrrrjoinsplitrrerJrK ValueErrorrrXrto dtype_layoutdevicedtyperh)rhrirrrjnew_module_call_graphr$ old_nodesnew_graph_params_buffers provenanceuser_input_counterold_user_input_namesnew_user_input_nameshistoryold_nameold_param_to_desugaredrQr old_targetrfrernrMros ` @rW_get_updated_module_call_graphrfs!MM*?@-3\\-?-?@TD@I@   2 2   / /    . .   + + "$J & 2 2dgg6N   :  !#$'']2J ,iimmK4 47 4+/99Jwr{'' ( WW % 77;;/">">>;;"66%dii5,@dii@QR 44FGH%h4,?X?OP,099Jx(&!+&/,8).0668< f  !45//#' 4 &,,s"3Ab"9:J ": . 5 5d ;<''4OO   89##8i&7&78# 4Avv// $QVVH-Z[ vv##AFF+9$$QVV,;;/1hooIINN%%22IINN%%,,IINN%%++J7 "*q!1!6!6J!3(,ZL9bc ( 3AFG# 4 '4R ! _A sP%P*+P*,P/P/rc tt|||||\}}}t|j|j|||j}|j j |jj t||j} t||j||| ||j|j} | S)Nrrrr)rootrrrrange_constraintsrarr) rOrrrrarr_get_updated_range_constraintsrrErrr) rrrrrrr/rr|new_range_constraintsexported_programs rW_decompose_exported_programrs ; #/)$?    ;     GGNN2??''(:   ' hh+//((,,  rYc eZdZUdZej j ed< eed< e e e fed< ded< e e ed< eee dfe e e ffd zed < e e efed < e eeed < e e ed < dMd ddej$j&e e e fzdej j(dede e ej*ej$j,zfddde e deee dfe e e ffd zde e efd zde eed zfdZeeddZej6eddZeeddZej6eddZeedd Zej6edd!Zeedd"Zej6edd#Zedd$eej$j,fd%Z edd$eee ej$j,ffd&Z!edd$eej*fd'Z"edd$eee ej*ffd(Z#eedd)Z$e$j6edd*Z$eedd+Z%e%j6edd,Z%eedd-Z&e&j6edd.Z&eedd/Z'e'j6edd0Z'eedd$e fd1Z(e(j6edd2Z(eedd$e fd3Z)e)j6edd4Z)eedd5Z*e*j6edd6Z*eedd7Z+e+j6edd8Z+eedd9Z,e,j6edd:Z,d;Z-dZ.dd d d dK dPdLZ?y )QrEa Package of a program from :func:`export`. It contains an :class:`torch.fx.Graph` that represents Tensor computation, a state_dict containing tensor values of all lifted parameters and buffers, and various metadata. You can call an ExportedProgram like the original callable traced by :func:`export` with the same calling convention. To perform transformations on the graph, use ``.module`` property to access an :class:`torch.fx.GraphModule`. You can then use `FX transformation `_ to rewrite the graph. Afterwards, you can simply use :func:`export` again to construct a correct ExportedProgram. _graph_module_graph_signature _state_dictzdict[sympy.Symbol, ValueRanges]_range_constraints_module_call_graph.N_example_inputs _constants _verifiers _guards_code) verifiersrrrrrdict[sympy.Symbol, Any]rarrrc tjjj|_t |||_t|tjjr/|j jj|jt|j ||||_ ||_ ||_| td||_||_|xsi|_| xst&g} t)d| Dstd| | |_|j-t/|j |_y)Nz"module_call_graph must not be Nonec3<K|]}t|tywrP)rur+).0rNs rW z+ExportedProgram.__init__..cs>q:a*>sz2all verifiers must be subclasses of Verifier, got )rrrCodeGenr_create_graph_module_for_exportrrrrrrgrrrrrrrr+allrvalidate_convert_guards_to_coder) rRrrrrrrarrrs rW__init__zExportedProgram.__init__Bs//1I>> DYKP $ 3D4F4FGrYF)is_backward_compatiblec|jSrP)rrRs rWrzExportedProgram.graph_modulems!!!rYctd)Nz7Unable to set ExportedProgram's graph_module attribute.rrRvalues rWrzExportedProgram.graph_modulersTUUrYc.|jjSrP)rrrs rWrzExportedProgram.graphws  &&&rYctd)Nz0Unable to set ExportedProgram's graph attribute.rrs rWrzExportedProgram.graph|sMNNrYc|jSrP)rrs rWrzExportedProgram.graph_signatures$$$rYctd)Nz:Unable to set ExportedProgram's graph_signature attribute.rrs rWrzExportedProgram.graph_signaturesWXXrYc|jSrP)rrs rWrzExportedProgram.state_dictsrYctd)Nz5Unable to set ExportedProgram's state_dict attribute.rrs rWrzExportedProgram.state_dictsRSSrYrsc#DK|jD] \}}| yw)zH Returns an iterator over original module's parameters. N)r)rRr4params rW parameterszExportedProgram.parameterss) --/ HAuK  c#hK|jjD]}||j|fyw)z Returns an iterator over original module parameters, yielding both the name of the parameter as well as the parameter itself. N)rrr)rR param_names rWrz ExportedProgram.named_parameterss7 ..99 :Jdooj99 9 :s02c#DK|jD] \}}| yw)zC Returns an iterator over original module buffers. N)r)rRr4bufs rWbufferszExportedProgram.bufferss) ((* FAsI rc#Kt|jj}|jjD]-}||vr||j|f||j |f/yw)z Returns an iterator over original module buffers, yielding both the name of the buffer as well as the buffer itself. N)rrrrrr)rRr buffer_names rWrzExportedProgram.named_bufferssm "%T%9%9%P%P!Q//77 @K44!4>>+#>>>!4??;#???  @sA'A)c|jSrP)rrs rWrz!ExportedProgram.range_constraints&&&rYctd)Nz.CallSpecNrLrM)rZr[r\r_r`r^rbrYrWCallSpecrs __t+ +oo, ,rYrr)rLrMz=expected first module_call_graph fqn to be empty string, got )r rrardrrerLrM)rRrs rWrzExportedProgram.call_specs -z - t%% &! +D48 8  ! !! $ ( (B . OPTPfPfghPiPmPmOpq **1-77??++A.88AA  rYctd)Nz4Unable to set ExportedProgram's call_spec attribute.rrs rWrzExportedProgram.call_specQRRrYc |jdS)Nrrrs rWverifierzExportedProgram.verifier sq!!rYctd)Nz3Unable to set ExportedProgram's verifier attribute.rrs rWrzExportedProgram.verifiersPQQrYcb|j td|jdjS)Nz_verifiers must not be Noner)rrdialectrs rWrzExportedProgram.dialects/ ?? " !>? ?q!)))rYctd)Nz2Unable to set ExportedProgram's dialect attribute.rrs rWrzExportedProgram.dialectsOPPrYc|jSrPrrs rWrzExportedProgram.verifiers rYctd)Nz4Unable to set ExportedProgram's verifiers attribute.rrs rWrzExportedProgram.verifiers%rrYc|jSrPrrs rWtensor_constantsz ExportedProgram.tensor_constants*rrYctd)Nz;Unable to set ExportedProgram's tensor_constants attribute.rrs rWrz ExportedProgram.tensor_constants/s I  rYc|jSrPrrs rWrzExportedProgram.constants6rrYctd)Nz4Unable to set ExportedProgram's constants attribute.rrs rWrzExportedProgram.constants;rrYc|jj}| t||}tj||f\}}|j |t d|D}||fS)aFlatten args, kwargs using pytree, then, check specs. Args: args: List[Any] original args passed to __call__ kwargs: Dict[str, Any] original kwargs passed to __call Returns: A tuple of (flat_args, received_spec) flat_args is flattened args / kwargs received_spec is the pytree spec produced while flattening the tuple (args, kwargs) c3&K|] }|d yw)r7Nrb)rrns rWrz.Ts<1!A$Trying to flatten user inputs with exported input tree spec: z- but actually got inputs with tree spec of: F)rrLrr0rwrwrrrr<rrrr rrrrCONSTANT_TENSOR CUSTOM_OBJr)rRrhrirLrradditional_inputsinput_s rW_graph_module_flat_inputsz)ExportedProgram._graph_module_flat_inputsWsf..((#'#A#A$#O =  } 7$A( Q)@ /# **66 HF{{i222##  !$$-&,,T^^FMM-JK%,,T__V]]-KL))$$!"(( )FG# H$""34!9,,rYctd)Nz\Unable to call ExportedProgram directly. You should use `exported_program.module()` instead.r)rRrhris rW__call__zExportedProgram.__call__s B  rYc|jjddjdd}t|jjdd}d|d|d|j d}|S)NF) print_outputcolored z zExportedProgram: z Graph signature: z Range constraints: )rprint_readablereplacerarr)rRrrstrings rW__str__zExportedProgram.__str__s((778 '$ ! d223;;D(K .! /01""&"8"8!9 =   rYcddlm}|||}ddtfd}ddtfd}tj|||_tj|||_|S)a Returns a self contained GraphModule with all the parameters/buffers inlined. - When `check_guards=True` (default), a `_guards_fn` submodule is generated and a call to a `_guards_fn` submodule is inserted right after placeholders in the graph. This module checks guards on inputs. - When `check_guards=False`, a subset of these checks are performed by a forward pre-hook on the graph module. No `_guards_fn` submodule is generated. r7)&_unlift_exported_program_lifted_states) check_guardsmodectd)Nz%Calling train() is not supported yet.NotImplementedErrorrRrs rW_trainz&ExportedProgram.module.._trains%&MN NrYctd)Nz$Calling eval() is not supported yet.rrs rW_evalz%ExportedProgram.module.._evals%&LM MrYT)rrbooltypes MethodTypetraineval)rRrrrrrs rWrzExportedProgram.modules_ D7<X Ot O Nd N''7 &&uf5  rYctdt|jjDt |jjS)Nc3`K|]&\}}|jtjk(r|(ywrP)rr<r)rrUss rWrz=ExportedProgram._num_lifted_params_buffers..s. Aq66Y111 s,.)nextr rrrrs rW_num_lifted_params_buffersz*ExportedProgram._num_lifted_params_bufferssC %d&;&;&G&GH  %%11 2   rYrrc| tn t|}t|tr|j }t |\}}t |||d|S)a Run a set of decompositions on the exported program and returns a new exported program. By default we will run the Core ATen decompositions to get operators in the `Core ATen Operator Set `_. For now, we do not decompose joint graphs. Args: decomp_table: An optional argument that specifies decomp behaviour for Aten ops (1) If None, we decompose to core aten decompositions (2) If empty, we don't decompose any operator Some examples: If you don't want to decompose anything .. code-block:: python ep = torch.export.export(model, ...) ep = ep.run_decompositions(decomp_table={}) If you want to get a core aten operator set except for certain operator, you can do following: .. code-block:: python ep = torch.export.export(model, ...) decomp_table = torch.export.default_decompositions() decomp_table[your_op] = your_custom_decomp ep = ep.run_decompositions(decomp_table=decomp_table) Nr)rHrvrr3 materializerr)rRrr _decomp_tablerrs rWrun_decompositionsz"ExportedProgram.run_decompositionsskP)5(< " $$|BT  m%6 7)557M" 9 G  + ' 3!(C   rYpassesc ftt|}ddlm}|5||j}ddd |jn |j}| t d||jur|j s|Sdtdtjjdtfd}t||j||j||jt||j t#j$|j&|j(|j*|j, }|jj.j1|jj.|jj.j1|jj.|S#1swYsxYw) Nr)rztransformed_gm must not be None old_signaturenew_gmrsc g}t|jjD]\}}|jdk7rn|t |j k\r%t d|dt |j d|j |}t|jttfr |jn$t|j|j}|jt|j||j |j"t%|jjd}|jdk7rt d|jg}t|j&dD]\}}|t |j(k\r%t d |dt |j(d |j(|} t| jttfr | jn$t| j|j}|jt+| j|| j t-|| } | S) zO Update the graph signature's user_input/user_outputs. rz9Number of inputs changed after transformation: got index z but only z input_specsrrr@z,expected last node to have op='output', got rz:Number of outputs changed after transformation: got index z output_specsr)r rrr}rrrrrr9r:rrQrr=rrr r]rhrr?r;) rrnew_input_specsrUr$old_input_specrrnew_output_specsold_output_spec new_signatures rW_get_updated_graph_signaturezKExportedProgram._transform_do_not_use.._get_updated_graph_signaturesb!O$V\\%7%78 477m+M5566(STUSVW$$' (A(A$B#C<Q"/!:!:1!="&**-=?P,Q#&&2n001$))<  &&&++&--&11 # 4v||11226K~~)$B;>>BTU " $[%5%5a%89 4M6677(TUVTWX$$' (B(B$C#DMS#0"<"@Q-R$''3o112499= !''33S/:P:PQ $1+:JM! rY rrrrrrarrr)r6r]rrrrmodifiedr;rrrrErrrrrrrsrrrrrr)rRrpmrrestransformed_gmrtransformed_eps rW_transform_do_not_usez%ExportedProgram._transform_do_not_usesw f & @ $ & (T&&'C (-0_))$BSBS  ! !BC C T.. .s||K> !/> !HH((> !"> !@) &&8$$n<&&#mmD,C,CD..nnnn  ##((//0A0A0F0FG##((//0@0@0E0EF} ( (s F&&F0cRddlm}|jjDcgc]}|jdk(s|}}t ||j jDcgc]$\}}|jtjk(r|&}}}||||jycc}wcc}}w)Nr)"_check_input_constraints_for_graphr) torch._export.utilsr&rrr}rrrrr<rr)rRrr&r0 placeholdersr input_placeholderss rWrz(ExportedProgram._check_input_constraintshsJ#'::#3#3Maqtt}7LM ML$*>*>*J*JK 1vv---   +  3T5K5K N sBB)B#c$|jyrP) _validaters rWrzExportedProgram.validateus  rYct|jdk(r td|jD]}|j|y)Nrz0ExportedProgram must have at least one verifier.)rrrcheck)rRrNs rWr+zExportedProgram._validatezs? t~~ ! # !ST T A CIIdO rY)rrrc $t||j|||n |jtj|j tj|j |j||n |j|| S|j S)Nr) rErrrrsrrrrr)rRrrrrrs rW_updatezExportedProgram._updates$$+%/%;z"mmD,B,BC"mmD,C,CD..#,#8idnn#,#8i  ?Cnn  rY)NNr)NF)rsrE)@rZr[r\__doc__rrrr^r;rvrarr]rFrrrr+rModuleGraphrrrpropertyr4rsetterrrrrrrrrrrarrrrrrrrrrrrrrn_ops OperatorBaserrrPassTyper$rrrr+r/rbrYrWrErEsE 88'''O**Mc3hU99E_--J5c?DcN:;dBBLS0011:T(^$$Is)IM>B)H26)HhhooS#X.)Hxx~~)H. )H ellUXX-?-???@ )H 5 )H 0)HeCHotCH~=>E)H334t;)HX'$.)HV%0"1"%0V1V%0'1' \\%0O1O%0%1%%0Y1Y%0 1 %0T1T%0HUXX%7%781%0:(5ehh6H6H1H+I"J:1:%0%,,/1%0 @xc5<<.?(@A @1 @%0'1'%0 1 %0'1'%0 1 %0$1$%0%1%2%0 1 %0S1S%0"#"1"__%0R1R%0**1*  ^^%0Q1Q%01%0S1S%01%0 1 %01%0S1S(.,-c,-3,-3,-\ c S S  588+?+?2 $HL,1D 5::22H<=DD &*D   D $D LdXd:KdL  %01     rYcP|jjDcgc]-}|jjdd|jd/}}ddlm}||}| |j S|D]4}t|tjs|jj cSycc}w)Nrrr,) rrrr torch._guardsr-rrrSymIntr$)rr$valsr-rrNs rWr r sHHNN   99== % 1 % D  / &I""" $ a &66## #$ s2B#old_range_constraintszdict[sympy.Symbol, Any] | NonercN| tdt|}|iStj|}|jDcic]\}}||jvs||}}}|j jD]\}}||jvs||vs|||< |Scc}}w)Nz&old_range_constraints must not be None)rr rr replacements var_to_range)rr<rrrrNs rWrrs$EFFr"I  "78*002Aay?U?U6U1 &&,,.%1 I** *q8I/I#$ a % s B!B!c tjj||}|S#t$r^t j ddtjj|tjj }||_Y|SwxYw)NzUnable to execute the generated python source code from the graph. The graph module will no longer be directly callable, but you can still run the ExportedProgram, and if needed, you can run the graph module eagerly using torch.fx.Interpreter.r) stacklevel)rrr SyntaxErrorwarningswarnr2_graph)rrrs rWrrs} XX ! !$ ." I!    G  XX ! !$(8 9 I!s $A#B  B c(t|}|gS|jjDchc]\}}td|Dr|}}}tj j jj|jd|j}|jDcgc]B}|jjj|r|j|jD}}|Dcgc] }d|vs| c}Scc}}wcc}wcc}w)Nc3zK|]3}t|tjjj 5ywrP)rrrrLConstantSource)rrLs rWrz*_convert_guards_to_code..s2 65==#7#7#F#FG G s9;c|jSrPr)r s rWrpz)_convert_guards_to_code..s AFFrYz L['self'])r var_to_sourcesrrrr experimentalsymbolic_shapesShapeGuardPythonPrinterguardsexpr free_symbolsissubsetdoprint)rrvarsources local_vars py_printerguardrets rWrrs |,I &44::< C  !   J&&66NN  "2I4L4LJ %%   :: " " + +J 7 5::& C  # ?ek&>E ??%  @sD&AD 3 D=D)rsr3rP)rr dataclassesrlr_rrC collectionsrcollections.abcrrrtypingrrr r r9r r torch._higher_order_ops.utilsr "torch._library.fake_class_registryrtorch._subclasses.fake_implsrrrtorch._subclasses.fake_tensorrtorch.fx._symbolic_tracertorch.fx._utilsrtorch.fx.graphrrtorch.fx.immutable_collectionsrrtorch.fx.passes.runtime_assertrsympytorch.utils._sympy.value_rangesrrtorch.utils._pytreeutils_pytreer_r'rrrrrr r!r"r#r$r%r&r'r(r)r*torch._export.verifierr+r-r/torch.export._tree_utilsr0r1torch.export.decomp_utilsr3torch.fx._compatibilityr4torch.fx.passes.infra.pass_baser5"torch.fx.passes.infra.pass_managerr6rr8r9r:r;r<r=r>r?r@rArBrCrD__all__rrr7 dataclassrGrFrnrContextrrwrr AutogradCPU AutogradCUDA AutogradMeta AutogradXLA AutogradLazy AutogradIPU AutogradXPU AutogradMPS AutogradHPUAutogradPrivateUse1AutogradPrivateUse2AutogradPrivateUse3rCPUCUDAMetaXLALazyIPUXPUMPSHPUrrrvr5r6rrrHrrOrrgr]rrrEr rrrrbrYrWrs  #.%881B? 9;?6IJ ; $$$,*@B716:"  UXX))*J,== >  ' ' '  111 Gt G>>Gt G>> G  G: HH$$ HH%% HH%% HH$$ HH%% HH$$ HH$$ HH$$ HH$$ HH,, HH,, HH,, ,(, HH HH HH HH HH HH HH HH HH P$P$f,-uzz..89,- 4 ''1 2C 78,-^b2b2 //9:b2ejj55x?@ b2 Dj b2J# #3G# 588  !5 56#2. .:x! HH x!-x! x!* x!  0 x!v4 //9:4ejj55x?@ 4 Dj 4 "& 4n}  }  @ $$?C ;0,@rY