tj4ZddlZddlmZddlmZddlZddlZddlmZddl m Z ddl m Z m Z mZddlmZddlmZmZdd lmZdd lmZmZmZdd lmZdd lmZGd deZeZ e !edZ"ee ddZ#e j$dZ%e !ej&ee de !ej'dZ(dZ)edZ*dZ+dZ,de-de-fdZ.dZ/dZ0dZ1dS) N)contextmanager)wraps) DispatchKey)+_maybe_find_pre_dispatch_tf_mode_for_export)_ConstantFunction flat_apply to_graphable strict_mode)autograd_not_implemented register_fake)HigherOrderOperator)PreDispatchTorchFunctionModeProxyTorchDispatchModetrack_tensor_tree)_pytree)"is_traceable_wrapper_subclass_typec(eZdZfdZfdZxZS)ExportTracepointcJtddS)N_export_tracepoint)super__init__)self __class__s T/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/torch/_export/wrappers.pyrzExportTracepoint.__init__s" -.....c6tj|i|SN)r__call__)rargskwargsrs rr zExportTracepoint.__call__suww0000r)__name__ __module__ __qualname__rr __classcell__)rs@rrrsQ/////111111111rrctj|jj||f\}}|jdt ||}t ||d|jS)N call_functionconstanttracer)pytreetree_mapr+ unwrap_proxy create_proxyrr)moder!r"p_argsp_kwargsproxys rexport_tracepoint_dispatch_moder4's]t{'?$PPFH K $ $+VX  E T54 L L LLrT) skip_cachec|Srr!r"s r"export_tracepoint_fake_tensor_moder90 Krc||}||}|5t|i||cdddS#1swxYwYdSr)unwrap_tensorsredispatch_to_nextr)ctxr!r"unwrapped_argsunwrapped_kwargss rexport_tracepoint_functionalrA5s''--N))&11   ! !N?.>???sAA!A)deferred_errorc|Srr7r8s rexport_tracepoint_cpurDDr:rc t|tjjst dt |dkrt dtjj|}fd dfd} fd}| |d }| |d }||fS) Nzexpected torch.nn.Module, got zpath must not be emptyc|vrl|d|kr$td|d|dd||d|kr$td|d|dd|||d|<dS)Nin_speczin_spec mismatch for z: z != out_speczout_spec mismatch for )rHrI)AssertionError)pathrHrImodule_call_specss rupdate_module_call_signaturesz6_wrap_submodule..update_module_call_signaturesPs $ $ $ &y1W<<$eDee4Ed4KI4Vee\cee!&z2h>>$hThh5Ft5LZ5Xhh^fhh/68"L"L$rc |D]I}t|tjttt t fs|td|JdS)NzGOnly Tensors or scalars are supported as pytree flattened inputs, got: ) isinstancetorchTensorstrintfloatboolrJ) flat_argsas rcheck_flattenedz(_wrap_submodule..check_flattened\s]  Aq5<c5$"GHH AI$a^_aa  rctj||f\}}|t|dd}tj||\}}||fS)Nmodule_call_inputskindrKr, tree_flattenrtree_unflatten)moduler!r"rVrHrXrKs rpre_hookz!_wrap_submodule..pre_hookcsb#0$@@ 7 """& 8LSWXXX ,Y@@ fV|rctj||f\}}tj|\}}|t|d d} ||tj||S)Nmodule_call_outputsr[r]) r`r!r"res_rHflat_resrIrXrKrMs r post_hookz"_wrap_submodule..post_hookjs~($88 7#055(!!!%x6KRVWWW%%dGX>>>$Xx888rT) with_kwargs) rOrPnnModulerJtypefx graph_module _get_attrregister_forward_pre_hookregister_forward_hook) modrKrL submodulerarg pre_handle post_handlerXrMs `` @@r_wrap_submoduleruIs c58? + +KId3iiIIJJJ rzz5666%//T::I M M M M M999999944X44PPJ11)1NNK { ""rc#Kg} |D]&}|t|||'dV|D]}|dS#|D]}|wxYwr)extendruremove)fpreserve_signaturemodule_call_signatureshandlesrKhandles r_wrap_submodulesr~wsG& M MD NN?1d4JKK L L L L   F MMOOOO  g  F MMOOOO s -AA)cd}||_|S)Nc"t||Srr )rr!s rcallz'_mark_strict_experimental..calls4&&&r)r )clsrs r_mark_strict_experimentalrs'''CL JrcB|dz}t|j|rCt|j||krtd||d|diS||}t |j|||d|diS)a This is a wrapper utility method on top of tracer to cache the already registered subclass spec attribute. This is useful because Subclass.__init__ will be same for each subclass. By default, fx will create multiple attributes/proxies for given attribute. 0zspec mismatch for get_attrr7)hasattrrootgetattrrJr/get_fresh_qualnamesetattr)r+namespecfx_namequalnames r#_register_func_spec_proxy_in_tracerrsSjGv{G$$@ 6; ( (D 0 0 !?g!?!?@@ @"":wB???((..H FK4(((   z8R < <.wrappersd-f---~**,,  F1$tAw--@@ '4==jII $lI]Ijll,89KC OO;K9KLH~8~~~  ;<< < F$ <==  Jd4jjJJ 748__f- HH1>DDFFLLSQQRR "8nn5;;==#'>>$ 3      r)rrr#)rrs` r1mark_subclass_constructor_exportable_experimentalrsg* ( ) )  ~)=)F ~ ~ ~   )))))V NrctrtSts#jdkstdjdt fd}|S)a Experimental decorator that adds user function to export pre-dispatch graph. Note that we only support custom autograd function/subclass constructors today. To use this function: 1. For subclasses: 1. refer to instructions in mark_subclass_constructor_exportable_experimental 2. Define apply method on your custom autograd function and apply this decorator. Example: class MyCoolCustomAutogradFunc(autograd.Function): @classmethod @torch._export.wrappers.allow_in_pre_dispatch_graph def apply(cls, *args, **kwargs): return super(MyCoolCustomAutogradFunc, cls).apply(*args, **kwargs) applyztorch._export.wrappers.allow_in_pre_dispatch_graph can only be applied on subclass tensor.__init_ or custom_autograd_function.apply. But, you are adding it on a/ which is not supported. If __init__ doesn't exist on your subclass, please add it. Look at DTensor.__init__ implementation for example. If you are adding it on custom autograd function, please add it on apply method. If anything else, file an issue on github and we may consider extending our support. cdtjs |i|Stj|ds |i|St |dtjjs |i|Sddlm }|tj j j }| |i|Stj tj jj}tj tj tj jjz}tj ||5 |i|}dddn #1swxYwY|jst+d|j}|djd|dj}|g|ddR|f} ddlm} d|d} t;| j} tA|| | | || |S) Nr)_get_dispatch_mode_pre_dispatchz"Should only do this in predispatchrr)._call_custom_autograd_function_in_pre_dispatchrer)!rPrrinspectisclass issubclassautogradFunction torch._opsr_C_TorchDispatchModeKeyPROXY_dispatch_tls_local_include_setrxr PreDispatch_dispatch_tls_local_exclude_setDispatchKeySet_ForceDispatchKeyGuard pre_dispatchrJr+r$r%torch.export.custom_opsrrrrkr#rr)r!r"rr0include_to_setexclude_to_setoutr+function_cls_namerrrrfuncs rrz,allow_in_pre_dispatch_graph..wrapper)s~**,, )4((( (tAw'' )4((( ($q'5>#:;; )4((( (>>>>>>..ux/M/STT <4((( (AACCJJ H ,   H 4 4 6 6h%%eh&:&FGG H  X , ,^^ L L ( ($'''C ( ( ( ( ( ( ( ( ( ( ( ( ( ( (  G !EFF F#Aw1JJDG4HJJ'3$qrr(33V<       HH.44S99:: " :  5577  #Q$ 3      s E22E69E6)rrr#rr)rrs` rallow_in_pre_dispatch_graphr s"~~G@FFF TNN dmw66 e)- e e e    4[[4444[4l Nr)2r contextlibr functoolsrrPtorch._custom_opstorch._Crtorch._export.utilsr"torch._higher_order_ops.flat_applyrrr #torch._higher_order_ops.strict_moder torch._higher_order_ops.utilsr r rr"torch.fx.experimental.proxy_tensorrrr torch.utilsrr,torch.utils._python_dispatchrrrpy_implr4r9py_functionalize_implrAAutogradCPUrDrur~rrrRrrrrr7rrrs%%%%%%  KKKKKK <;;;;;QQQQQQQQ****** *)))))KKKKKK11111*111&%''233MM43M!d33343)*)1;/00/EEE KO,,-,+#+#+#\   ===$LLLLLL>666GGGTUUUUUr