[Th%SSKrSSKrSSKrSSKrSSKrSSKJrJr SSKJ r J r J r J r J r Jr SSKrSSKJrJrJr SSKJrJrJr SSKJr SS KJr \ (aSS KJr /S Qr\R>"\ 5r!\\"\#\$\%\&\RN\RP\RR\RT\RV\R0RX\RZ\R\\R^4r0\0Rbr2\\ S \ 4\"4r3\ \\4S \S\\"S4\5\6S\04r7\ "S\7S9r8\9Ru/SQ5r;\RxRz\R|R~\R|R/rA\B\ \CS'\R\R\RRR\RRR\RRR\RRR\RRR\RR\RR\RR\RRR\R1 \T"\A5-rU\T\ \CS'\V"\RS5(a/\UR\RRR5 \"SS9S\ S\ 4Sj5rYS\ S \ 4S\"4SjrZS\[S\"4Sjr\S\ S \ 4S\"4S jr]\$"S!54S"\[S#\$S\"4S$jjr^\"S%S9"S&S\55r_\"S%S9S'\8S\ \_/\74S\84S(j5r`\"S%S9S'\8S\ \7/\74S\84S)j5rag)*N)MappingSequence)AnyCallableOptional TYPE_CHECKINGTypeVarUnion)_fx_map_aggregate _fx_map_arg _NodeBase)ArgsKwargsPairnormalize_functionnormalize_module)ops) compatibility)Graph)Nodemap_arg map_aggregatehas_side_effect.Argument.rr ArgumentT)bound) placeholder call_method call_module call_functionget_attroutputroot1_side_effectful_need_to_be_preserved_pre_dispatch_side_effectful_functionsresize_storage_bytes_Fis_backward_compatiblefnreturnc0[RU5 U$N)r&add)r*s E/var/www/auris/envauris/lib/python3.13/site-packages/torch/fx/node.pyrrhs!!"% I orig_methodcURnURnUbU$[[RR4H n[ X1S5ULdMURs $ [ SU35e)Nzcannot find module for )__name__ __module__torchnn functionalgetattr RuntimeError)r1namemoduleguesss r/_find_module_of_methodr=osj   D  # #F  ,,- 5 % 4>> !. 0 > ??r0objcP[U[5(aV[U[R5(d7URS:Xa UR $URSUR 3$USLag[U[R 5(a UR$[U5$)a&Return the repr() of an object, special-casing types (internal helper). 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For everything else, we fall back on repr(obj). builtins..z...) isinstancetypetypes GenericAliasr4 __qualname__ FunctionTyper3repr)r>s r/ _type_reprrI|s#tZU5G5G%H%H >>Z '## #..!3#3#3"455 cz#u))**|| 9r0funccZ[[URS5ULa UR$[U[R [R 45(a7U[[RURS5LaSUR3$URnUS:Xa7[R"U5RS5SR5n[U5nUR!SS5nUS:Xa US :XaS U-nUS U3$![an[S5UeSnAff=f) Nz torch.Tensor.z=rzUnable to represent lambdaz torch._opsz torch.opsr5segment_reduce_rA)r8r@r3rBrDMethodDescriptorTypeWrapperDescriptorTyper5Tensorinspect getsourcesplitstrip Exceptionr9r=replace)rJr:er;s r/_get_qualified_namerYsx-5}} u))5+F+FG '%,, t< <t}}o.. ==D z D$$T*005a8>>@D$D )F ^^kFT%55TzXQtf  D;# UHupUT:dM [U5v M g7fr- _format_arg.0idxar\s r/ _format_arg..% )7vs3;MNKNN %%rz, ...[total_len=][c3N># UHupUT:dM [U5v M g7fr-r`rbs r/rfrgrhri,()c3F# UHupUS[U53v M g7f): Nr`)rckvs r/rfrgs"O;412k!n%56;s!{}%) hasattrr^rBlistjoin enumeratelentupledictitemsrstr)r[r\r maybe_len maybe_comma items_strs ` r/rarases())%%'' C    )23  c(\A--B5Ec#hZq3Q 5')A&& C    )23  c(\A--B5Ec#hZq3Q !X]c 5'+yk33 C  IIO399;OO I;b!!#tSX~3xr0Tcl^\rSrSr%Sr\S\S'\\S4\S'S\S'\\S '\\S 'S \S '\S \S'\S \S'\ \ \S'\ \S'\ \ S/\4\S'\\\ 4\S'\ "SS9SRSSS \S \S S S\SS\\S4S\ \ SS4U4Sjjj5r S\\\ 44SjrS\\\ 4SS4Sjr\SSSj5r\SSS j5r\ "SS9STS!j5rS"SS\4S#jrS"SS\4S$jrS"SS\4S%jrS"SS\4S&jr\ "SS9STS'j5rSUS(jr\S\\S)44S*j5r\R:S+\\S)4SS4S,j5r\S\\\44S-j5r\R:S.\\\4SS4S/j5r\S\S4S0j5r \ "SS9S1\!S2\SS4S3j5r"\ "SS9S1\!S2\SS4S4j5r#\ "SS9S5\S2\SS4S6j5r$\S\ \4S7j5r%\%R:S8\ \SS4S9j5r%S\4S:jr&\'S \(S\4S;j5r)\ "SS9SVS<\ \\S=\ \\S\ \4S>jj5r*\ "SS9S?4S@SA.SBSSC\ S/\4SD\S\S4SEjjj5r+\ "S@S9S\4SFj5r,\ "S@S9SWSG\-R\R^SH\ \\ SI\ \\\ 4SJ\S\ \04 SKjj5r1\ "SS9SXSLj5r2SM\SS4SNjr3S \SO\ SS4SPjr4SQr5U=r6$)Yra ``Node`` is the data structure that represents individual operations within a ``Graph``. For the most part, Nodes represent callsites to various entities, such as operators, methods, and Modules (some exceptions include nodes that specify function inputs and outputs). Each ``Node`` has a function specified by its ``op`` property. The ``Node`` semantics for each value of ``op`` are as follows: - ``placeholder`` represents a function input. The ``name`` attribute specifies the name this value will take on. ``target`` is similarly the name of the argument. ``args`` holds either: 1) nothing, or 2) a single argument denoting the default parameter of the function input. ``kwargs`` is don't-care. Placeholders correspond to the function parameters (e.g. ``x``) in the graph printout. - ``get_attr`` retrieves a parameter from the module hierarchy. ``name`` is similarly the name the result of the fetch is assigned to. ``target`` is the fully-qualified name of the parameter's position in the module hierarchy. ``args`` and ``kwargs`` are don't-care - ``call_function`` applies a free function to some values. ``name`` is similarly the name of the value to assign to. ``target`` is the function to be applied. ``args`` and ``kwargs`` represent the arguments to the function, following the Python calling convention - ``call_module`` applies a module in the module hierarchy's ``forward()`` method to given arguments. ``name`` is as previous. ``target`` is the fully-qualified name of the module in the module hierarchy to call. ``args`` and ``kwargs`` represent the arguments to invoke the module on, *excluding the self argument*. - ``call_method`` calls a method on a value. ``name`` is as similar. ``target`` is the string name of the method to apply to the ``self`` argument. ``args`` and ``kwargs`` represent the arguments to invoke the module on, *including the self argument* - ``output`` contains the output of the traced function in its ``args[0]`` attribute. This corresponds to the "return" statement in the Graph printout. r_argsr_kwargsrgraphr:opTargettarget)rN _input_nodesusersrC _sort_key_repr_fnmetaTr(Nargskwargs return_typer+c j>US:Xa=[U5(d,[SUSUSUS[R"U5S3 5eOMU[;de[ U[ 5(d,[SUSUSUS[R"U5S3 5e[TU]!XX4U5 URXV5 g) a Instantiate an instance of ``Node``. Note: most often, you want to use the Graph APIs, i.e. ``Graph.call_module``, ``Graph.call_method``, etc. rather than instantiating a ``Node`` directly. Args: graph (Graph): The ``Graph`` to which this ``Node`` should belong. name (str): The name to which the output of this ``Node`` should be assigned op (str): The opcode for this ``Node``. Can be one of 'placeholder', 'call_method', 'call_module', 'call_function', 'get_attr', 'output' target ('Target'): The target this op should call. See the broader ``Node`` docstring for more details. args (Tuple['Argument']): The args to be passed to ``target`` kwargs (Dict[str, 'Argument']): The kwargs to be passed to ``target`` return_type (Optional[Any]): The python type expression representing the type of the output of this node. This field can be used for annotation of values in the generated code or for other types of analyses. r!zNode [graph = z , name = 'z '] target z has type z but a Callable is expectedz but a str is expectedN) callable ValueErrorr5typename _legal_opsrBrsuper__init___update_args_kwargs) selfrr:rrrrr __class__s r/r Node.__init__ sJ  F## $UG:dV:fXZX]XfXfgmXnWop11$ # ##fc** $UG:dV:fXZX]XfXfgmXnWop,, b+>   .r0cn0UREURURURURURUR UR URURURURURURURURS.E$)N)rr:rrrCrrr_erased_prev_nextrrrr)__dict__rr:rrrrrrrrrrrrrs r/ __getstate__Node.__getstate__?s mm ZZII''kkKKZZ||||ZZZZ --ZZ II!  r0statecNUR5Hup#[XU5 M gr-)rsetattr)rrrsrts r/ __setstate__Node.__setstate__SsKKMDA DQ "r0cUR$)zv Returns the next ``Node`` in the linked list of Nodes. Returns: The next ``Node`` in the linked list of Nodes. )rrs r/next Node.nextWzzr0cUR$)z~ Returns the previous ``Node`` in the linked list of Nodes. Returns: The previous ``Node`` in the linked list of Nodes. )rrs r/prev Node.prevbrr0cHURUR:XdS5eX:Xa[RS5 gUR5 URnXsUlUlXsUlUlURR nUR R n[U5[U5:a#US[U5S-GtpV/UQUS-P7Ulg[U5[U5:a#US[U5S-GtpV/UQUS- P7Ulg/UQSP7Ulg)a Insert x before this node in the list of nodes in the graph. Example:: Before: p -> self bx -> x -> ax After: p -> x -> self bx -> ax Args: x (Node): The node to put before this node. Must be a member of the same graph. z0Attempting to move a Node into a different GraphzMTrying to prepend a node to itself. This behavior has no effect on the graph.Nrr)rlogdebug_remove_from_listrrrr|)rxppsknskprefixrds r/prepend Node.prependmszzQWW$X&XX$ 9 II_    JJ"gggg s8c#h ~SA.LV,F,C!G,AK XC ~SA.LV,F,C!G,AK#C))AKr0otherc4URUR:$r-rrrs r/__gt__ Node.__gt__~~//r0c4URUR:$r-rrs r/__lt__ Node.__lt__rr0c X:=(d X:H$r-rs r/__ge__ Node.__ge__|,t},r0c X:=(d X:H$r-rrs r/__le__ Node.__le__rr0c:URRU5 g)z Insert ``x`` after this node in the list of nodes in the graph. Equivalent to ``self.next.prepend(x)`` Args: x (Node): The node to put after this node. Must be a member of the same graph. N)rr)rrs r/append Node.appends 1r0cNURURp!X!sUlUlgr-)rr)rrns r/rNode._remove_from_listszz4::1r0.cUR$)a The tuple of arguments to this ``Node``. The interpretation of arguments depends on the node's opcode. See the :class:`Node` docstring for more information. Assignment to this property is allowed. All accounting of uses and users is updated automatically on assignment. )rrs r/r Node.argsszzr0rec:URXR5 g)z Set the tuple of arguments to this Node. The interpretation of arguments depends on the node's opcode. See the ``fx.Graph`` docstring for more information. N)rr)rres r/rrs   LL1r0cUR$)a The dict of keyword arguments to this ``Node``. The interpretation of arguments depends on the node's opcode. See the :class:`Node` docstring for more information. Assignment to this property is allowed. All accounting of uses and users is updated automatically on assignment. )rrs r/r Node.kwargss||r0rsc<URURU5 g)z Set the dict of kwargs to this Node. The interpretation of arguments depends on the node's opcode. See the ``fx.Graph`` docstring for more information. N)rr)rrss r/rrs   Q/r0cH[URR55$)a  Return all Nodes that are inputs to this Node. This is equivalent to iterating over ``args`` and ``kwargs`` and only collecting the values that are Nodes. Returns: List of ``Nodes`` that appear in the ``args`` and ``kwargs`` of this ``Node``, in that order. )ryrkeysrs r/all_input_nodesNode.all_input_nodessD%%**,--r0rdr[cV[UR5nX#U'[U5Ulg)a Update an existing positional argument to contain the new value ``arg``. After calling, ``self.args[idx] == arg``. Args: idx (int): The index into ``self.args`` of the element to update arg (Argument): The new argument value to write into ``args`` N)ryrr})rrdr[rs r/ update_argNode.update_args#DIIS $K r0cSUs=::a [UR5::dS5e S5eURSUnURUSnX24-U-Ul0n[X%R5 UR 5HJnX`R ;dMUR R U5 URR U5 ML g)z Insert an positional argument to the argument list with given index. Args: idx (int): The index of the element in ``self.args`` to be inserted before. arg (Argument): The new argument value to insert into ``args`` rz6insert_args index must be between 0 and len(self.args)N)r|rrr setdefaultrrr)rrdr[ args_left args_right_new_input_nodesnew_uses r/ insert_argNode.insert_args  &DII & D C D & D C D &IIdsO YYst_ '*4 -/C445',,.G///!!,,W5 ((./r0keyc00UREX0EUlg)a Update an existing keyword argument to contain the new value ``arg``. After calling, ``self.kwargs[key] == arg``. Args: key (str): The key in ``self.kwargs`` of the element to update arg (Argument): The new argument value to write into ``kwargs`` N)r)rrr[s r/ update_kwargNode.update_kwargs0/c/ r0c:URRSS5$)a Return the Python stack trace that was recorded during tracing, if any. When traced with fx.Tracer, this property is usually populated by `Tracer.create_proxy`. To record stack traces during tracing for debug purposes, set `record_stack_traces = True` on the `Tracer` instance. When traced with dynamo, this property will be populated by default by `OutputGraph.create_proxy`. stack_trace would have the innermost frame at the end of the string. stack_traceN)rgetrs r/rNode.stack_tracesyy}}]D11r0tracec XRS'g)Nr)r)rrs r/rr-s#( - r0c^UR(aURU5$UR$r-)rr:rs r/__repr__ Node.__repr__1s" ====& &yyr0c[U[5(aU$[US5(aE[USS5nUc [ U5$UR S:XaSU3$UR S:XaSU3$[ U5$)z Make target printouts more user-friendly. 1) builtins will be printed as `builtins.xyz` 2) operators will be printed as `operator.xyz` 3) other callables will be printed with qualified name, e.g. torch.add r4r3Nr@z builtins. _operatorz operator.)rBrrxr8rYr4)rr:s r/_pretty_print_targetNode._pretty_print_target6s fc " "M 6< ( (6:t4D| +622  J."4&))""k1"4&))"6**r0placeholder_namesmaybe_return_typenamecXURS:XGa[UR[5(deURnX0R(aUS[ UR53-OS- nU(aUR U5 gUR(a[ UR5S3OSnUR(aS[URS5-S-OSnS URS US [UR5S URS URSU3 $URS:XayURb[ UR5S3OSnS URS US [UR5S URS URUR5S3 $URS:XaEUR(a"U(aS[ UR53US'SURS3$URb[ UR5S3OSnS URS US [UR5S URS URUR5S[UR5S[UR5S3$)aO Return a descriptive string representation of ``self``. This method can be used with no arguments as a debugging utility. This function is also used internally in the ``__str__`` method of ``Graph``. Together, the strings in ``placeholder_names`` and ``maybe_return_typename`` make up the signature of the autogenerated ``forward`` function in this Graph's surrounding GraphModule. ``placeholder_names`` and ``maybe_return_typename`` should not be used otherwise. Args: placeholder_names: A list that will store formatted strings representing the placeholders in the generated ``forward`` function. Internal use only. maybe_return_typename: A single-element list that will store a formatted string representing the output of the generated ``forward`` function. Internal use only. Returns: str: If 1) we're using ``format_node`` as an internal helper in the ``__str__`` method of ``Graph``, and 2) ``self`` is a placeholder Node, return ``None``. Otherwise, return a descriptive string representation of the current Node. rrrrjN z (default=rrprwz : z [num_users=z] = z[target=rkr"r#z -> zreturn z ](args = z , kwargs = )rrBrrrCrIrrr:r|rrrar)rrrarg_strmaybe_typename default_vals r/ format_nodeNode.format_nodeOsnD 77m #dkk3// //kkG w2j&;% Node.sr0F)propagate_meta replace_withdelete_user_cbr c^^^U(aR[TR5S:XdS5eTRR5HupEUTRU'M [TR5n/nTR R nUHn U"U 5(dURU 5 M#S[S[4UU4Sjjn [USS5(a%URHn U "TTRU S9 M [U RU 5n [U RU 5n [U [ 5(de[U ["5(deU R%X5 M [TR5[U5- S:XdeUVs/sH oU;dM UPM sn$s snf) a_ Replace all uses of ``self`` in the Graph with the Node ``replace_with``. Args: replace_with (Node): The node to replace all uses of ``self`` with. delete_user_cb (Callable): Callback that is called to determine whether a given user of the self node should be removed. propagate_meta (bool): Whether or not to copy all properties on the .meta field of the original node onto the replacement node. For safety, this is only valid to do if the replacement node doesn't already have an existing .meta field. Returns: The list of Nodes on which this change was made. rzmCalled node.replace_all_uses_with(replace_with, propagate_meta=True), but replace_with already has .meta keysrr+c>UT:XaT$U$r-r)rr rs r/maybe_replace_node6Node.replace_all_uses_with..maybe_replace_nodes9''Hr0_replace_hooksNoldnewr)r|rrryrr owning_modulerrr8rr:r rrrBr}r~r)rr r r rsrt to_processskippedmuse_noder replace_hooknew_args new_kwargsrs`` r/replace_all_uses_withNode.replace_all_uses_withs~2 |(()Q. : . )'( !!!$*$**%  JJ $ $"H!(++x( d t   q*D11$%$4$4L T|/@/@xP%5#8==2DEH$X__6HIJh.. ..j$// //  ( ( >'#*4::W-222%::a')9::::s  F*!F*cURS;agURS:Xa\[URSS5nUbUR(ag[URSS5(agUR[;$URS:XaqUR R cS 5eUR R RUR5nUcS UR35e[US S5$g) z Returns whether this op is impure, i.e. if its op is a placeholder or output, or if a call_function or call_module which is impure. Returns: bool: If the op is impure or not. >r#rTr!_schemaN_nondeterministic_seededFr z1self.graph.owning_module not set for purity checkz'Did not find expected submodule target _is_impure)rr8r is_mutabler&rr get_submodule)rschema target_mods r/ is_impureNode.is_impures 77/ / 77o %T[[)T:F!f&7&7t{{$>FF;;";; ; 77m # ((4 CB C411?? LJ& G8 F G&:|U; ;r0r$ arg_types kwarg_typesnormalize_to_only_use_kwargscnURS:XaI[UR5(de[URURUR UU5$URS:XaL[ UR[5(de[XRURUR 5$g)a1 Returns normalized arguments to Python targets. This means that `args/kwargs` will be matched up to the module/functional's signature and return exclusively kwargs in positional order if `normalize_to_only_use_kwargs` is true. Also populates default values. Does not support positional-only parameters or varargs parameters. Supports module calls. May require `arg_types` and `kwarg_types` in order to disambiguate overloads. Args: root (torch.nn.Module): Module upon which to resolve module targets. arg_types (Optional[Tuple[Any]]): Tuple of arg types for the args kwarg_types (Optional[Dict[str, Any]]): Dict of arg types for the kwargs normalize_to_only_use_kwargs (bool): Whether to normalize to only use kwargs. Returns: Returns NamedTuple ArgsKwargsPair, or `None` if not successful. r!r N) rrrrrrrBrr)rr$r(r)r*s r/normalized_argumentsNode.normalized_argumentss< 77o %DKK(( ((%     WW %dkk3// //#D++tyy$++N Nr0c^^S[S[4UU4SjjnURRn[USS5(a%URHnU"TTR US9 M [ URU5n[ URU5n[U[5(de[U[5(deURXg5 g)z Loop through input nodes of ``self``, and replace all instances of ``old_input`` with ``new_input``. Args: old_input (Node): The old input node to be replaced. new_input (Node): The new input node to replace ``old_input``. rr+c>UT:XaT$U$r-r)r new_input old_inputs r/r3Node.replace_input_with..maybe_replace_node+s !Y9 5A 5r0rNr) rrrr8rr:r rrrBr}r~r)rr1r0rrrrrs `` r/replace_input_withNode.replace_input_withs 6$ 64 6 6 JJ $ $ 1& - - ! 0 0  TJ!1tyy*<= .@A (E*****d++++   6r0 candidatecXR:XagURRRUS5nX lURRR X5 gr-)r:r_graph_namespace create_name_rename_object)rr5r:s r/_rename Node._rename9sH  ! zz**66y$G  ##224>r0valuecjUS:Xa}[US5(alURRn[USS5(aD[ U[ 5(deUR HnURH nU"XUS9 M M Sn[X5(a[[URS5(a@XRR;a'SnURRRU5 [RXU5 U(a&URRRU5 gg)Nr:rrF_find_nodes_lookup_tableT) rxrrr8rBrrrr>removeobject __setattr__insert)rr:r<rrrupdates r/rANode.__setattr__@s 6>gdF33 ((Aq*D11!%---- JJD()(8(8 $tD)9' D   $>?? ;;;F JJ / / 6 6t <4u-  JJ / / 6 6t < r0)rrrrr:r-)r+r)rrr+N)r+N)NN)NNF)r1rr0rr+N)7r3r4rF__firstlineno____doc__r}__annotations__r~rrrrrrrrpropertyrrrboolrrrrrrrrsetterrryrintrrrrr staticmethodr@rrrr&r5r6Modulerr,r3r:rA__static_attributes__ __classcell__)rs@r/rrsC6  !! #z/ "" N I G |$$   3-Nx# .// sCx.$/&*2/2/2/  2/  2/ O$ 2/S*_%2/c]2/ 2/02/h d38n ( $sCx. 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(S 2? # ?0?B$/4E8; % 8;8;!&408;  8; f 8;08;t%0#4#1#J%0+/04-2 *hhoo*E#J'*d38n- * '+ * . ! *1*X$/7072???==C=D==r0recF[U5(dS5e[X5$)z Apply fn recursively to each Node appearing in arg. arg may be a list, tuple, slice, or dict with string keys: the return value will have the same type and structure. z.torch.fx.map_arg(a, fn): fn must be a callable)rr rer*s r/rrUs# B<<III< q r0c[X5$)z Apply fn recursively to each object appearing in arg. arg may be a list, tuple, slice, or dict with string keys: the return value will have the same type and structure. )r rQs r/rras Q ##r0)br@rRloggingoperatorrDcollections.abcrrtypingrrrrr r r5torch._Cr r r torch.fx.operator_schemasrrr_opsr_compatibilityrrr__all__ getLoggerr3rrrKfloatrIcomplexdtyperQdevice memory_formatlayout OpOverloadSymIntSymBoolSymFloatBaseArgumentTypes__args__ base_typesrr}slicerangerrr~fromkeysr_C_set_grad_enabledamp_enter_autocast_exit_autocastr%ryrG_assert _assert_asyncatenmsg_assert_scalardefault_assert_tensor_metadatasym_constrain_rangesym_constrain_range_for_sizeprofiler_record_function_enter_record_function_enter_new_record_function_exitinductoraccumulate_grad_setitemsetr&rxr.r'rr=r@rIrYrarrrrr0r/rs -II >> ) A !   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