ɯwg0ddlZddlZddlmZddlmZmZmZmZm Z ddl Z ddl m cm ZddlmZddlmZmZmZddlmZmZddlmZdd lmZmZmZmZe j>j@d Z!d e jDjFd eee$d e ee$e jDjJfee$e jDjJfffdZ&d e jDjFdeee$dee$e jDjJfdee$e jDjJfd df dZ' d&dejPdeejPdeee$d efdZ) d&d e jDjFd eee$deee$dejPdeejPdee$efdee$efdeee$fdZ*de jDjFdedee$efdee$efd df dZ+Gdde,Z-Gdd e jDjFe-!Z. d&d"e jDjFdeefd#Z/d$ed e j`jbfd%Z2y)'N)chain)AnyDictListOptionalTuple)"_check_input_constraints_for_graph) _assign_attr _AttrKind_recursive_getattr)_PyTreeCodeGen _PyTreeInfo)_remove_effect_tokens)ExportedProgramExportGraphSignature InputKind OutputKindc"tj|\}}||jk7rtd|jd|t |j j Dcgc]}|jdk(s|c}||jScc}w)Nz>Trying to flatten user inputs with exported input tree spec: z- but actually got inputs with tree spec of: placeholder) pytreetree_flatten_with_path_in_spec ValueErrorr graphnodesoprange_constraints)selfargskwargsflat_args_with_path received_specnodes Y/home/mcse/projects/flask/flask-venv/lib/python3.12/site-packages/torch/export/_unlift.py!_check_input_constraints_pre_hookr&s)/)F)Ft)L& % M}}o<o    .****G$dgg.FG  Gs B 5B gm lifted_inputsreturnci}i}|jjDcgc]}|jdk(s|}}t|t|k(sJt ||D]\}}||||j <|jj |5|jj|}|j||j} |jj|| |_ |||<ddd||fScc}w#1swYxYw)z_ Unlift inputs referring to params/buffers/constants as getattr nodes in the graph rN) rrrlenzipnameinserting_afterget_attrreplace_all_uses_withmeta erase_node) r'r(unlifted_name_to_nodeinput_name_to_noder$placeholder_nodes input_node lifted_node getattr_nodemetadatas r%_unlift_inputs_as_getattrr:)s*,((..U$DGG}%??##J/$, !5A%k2  B B B !"4 44V B BsC>C>A DD mutated_outputsr3r4cd}|jjD]}|jdk(s|}n|Jtj|j d}t |t |k(sJg}i}t||D]\} } | |j| | |vr|| } n| |vr|| } ntd| d|jj|5|jjtjjjj | | f} | || <ddd|Dcgc] }||vr||n|} }|jj|5|jj#t%| }|j&j)|j&|j+||jj-|dddy#1swYnxYwcc}w#1swYyxYw)zt Find the all the buffers and inputs that were mutated and insert copy_ operators to reflect mutations. NoutputrzCould not find z in either buffer or input nodes)rrrr tree_flattenr r+r,append RuntimeErrorinserting_before call_functiontorchopsatencopy_defaultr=tupler1updater0r2)r'r;r3r4 output_noder$outputsuser_output_nodesreturn_nodes_to_copy return_nodemutated_node_name mutated_node copy_node output_args new_outputs r%_insert_copy_for_mutationsrTFsK 77h K   "" "!!+"2"23A6G w<3/ // /*-g*G:& &  $  $ $[ 1   5 501BCL "4 4-.?@L!"3!44TU XX & &{ 3 :.. $$,,|[.II1:  -  : ::,& '+.B&BT"LK  " "; /)XX__U;%78 {//0))*5 K( )) : : ))s AG$6G1%A6G6$G. 6G?in_specout_specforward_arg_namesc|r|}n|jtk(r|jdk(r|jdjtk(r{|jdjtk(r[t |jdjDcgc]}d| }}|j |jdjn%t |jDcgc]}d| }}tt|||Scc}wcc}w)zK Create the codegen for the graph module based on the in/out specs rrarg_) typerH num_childrenchildren_specsdictrangeextendcontextr r)rUrVrWnamesis r% _get_codegenrd{s! LLE !$$)&&q)..%7&&q)..$6*/w/E/Ea/H/U/U)VWAtA3ZWEW LL//2:: ;).w/C/C)DEAtA3ZEEE       XFs C> D state_dict constantsct||\}} t|||| t||||j_|jj |j |S)a  Args: lifted_inputs: A list matching the graph module's input nodes. For an input node that is referring to a lifted parameter/buffer, this list will contain the fqn the corresponding attribute. Otherwise, this list will contain None. This is used to unlift the lifted parameters as get_attr nodes. mutated_outputs: A list matching the graph module's output nodes. For an output node that is referring to a mutated buffer or user input, this list will contain the name of the corresponding buffer or user input that needs to be mutated. Otherwise, this list will contain None. This is used to re-insert an inplace copy_ operator to copy the mutated values back to the original node. )r:rTrdr_codegenlint recompile) r'r(r;rUrVrerfrWr3r4s r%_unliftrksc21J M1-- O24F%Wh8IJBHHHHMMOLLN Inew_gmgraph_signaturect|j}|jD]3}||vrd}||}nd}||}t|||tj |5|j D]$}||}t|||tj&t|j|jD]$}||}t|||tj&y)NFT attr_kind persistentrq) setnon_persistent_buffersbuffersr r BUFFER parameters PARAMETERrlifted_custom_objslifted_tensor_constantsCONSTANT)rmrnrerfrur-rrvalues r%_register_attrs_to_new_gmr~s !!G!GH''   ) )JdOEJt$E 649+;+;     ** 4    ))   **O,S,S  $   ((   rlc*eZdZdZdZdfd ZxZS)_StatefulGraphModuleFactoryzO Metaclass that ensures a private constructor for _StatefulGraphModule cLt|jd|jd)N.z has no public constructor. ) TypeError __module__ __qualname__)clsr r!s r%__call__z$_StatefulGraphModuleFactory.__call__s,~~a 0 011M N  rlc(t||||S)Nr)superr)rrootrr __class__s r%_createz#_StatefulGraphModuleFactory._creates#w  /   rlN)__name__rr__doc__rr __classcell__rs@r%rrs   rlrc eZdZdfd ZxZS)_StatefulGraphModulec<t||||xsg|_yr)r__init__r)rrrrrs r%rz_StatefulGraphModule.__init__s u%!2!8brlr)rrrrrrs@r%rrs 99rlr) metaclassplain_graph_modulec<tj||j|}|jtd||S|j D]}|j |}|jr)tjd|d|j}|jd^}}t||}t||t|||tj |j"D]/}t|j |||tj$d 1|S) NrT) with_kwargszA model attribute `z` requires gradient. but it's not properly registered as a parameter. torch.export will detach it and treat it as a constant tensor but please register it as parameter instead.rrsFrp)rrrregister_forward_pre_hookr&r{ get_buffer requires_gradwarningswarndetachrsplitr delattrr r r|rurw) rrrn stateful_gm constant_fqnbufferprefixfieldsubmods r%_create_stateful_graph_modulers4'..  +/K )))t*(??V '' 5    MM%l^4?@  ]]_F%,,S1#K8V[,)BTBTU%V."88   ) )& 1  &&    rlepc Ft|}tjj|jt j |j}t||j|j|j|jjjd}|jjDcgc]Z}|jt j"t j$t j&t j(fvr |j*nd\}}|jj,Dcgc]<}|jt.j0t.j2fvr |j*nd>}}t5||||j6j8|j6j:|j|j|}t=||j>|j}|jjA|jj|Scc}wcc}w)NrW)rW)!rrCfx GraphModule graph_modulecopydeepcopyrr~rnrerfr1get input_specskindrrwCONSTANT_TENSORry CUSTOM_OBJtarget output_specsrBUFFER_MUTATIONUSER_INPUT_MUTATIONrk call_specrUrVrrrI)rrmrWrUr(rVr; unlift_gms r%&_unlift_exported_program_lifted_statesr<s r "B XX ! !"//4==3J KFfb&8&8"--V,,001DE))55 * ||  ))##$$  NN  *M *,**77,  }}**J,J,JKL OO ,O,    + F.$$b&8&8INN"//../ O *,srs 33 $$BNN6=$5 5 &5 4UXX]]" #T#uxx}}*<%= =>5:2) 2)(3-(2) UXX]] 232)S%((--/0 2)  2)p.2 __v' S * R.2" " &"(3-("__ " v' " S#X "CH~" S *"J# HH # )# S#X# CH~ #  # L $ $9588//;V97; 9,,9 23 9x--588??-rl