9ip %SrSSKJr SSKrSSKrSSKrSSKrSSKrSSKrSSK r SSK r SSK r SSK r SSK r SSKrSSKrSSKrSSKrSSKrSSKrSSKrSSKrSSKJr SSKJr SSKJrJrJrJr SSKJrJrJ r J!r!J"r" SSK#J$r$ SS KJ%r% SSK&r&SSK'r&SS K(J)r) SS K*J+r+ SS K,J-r- SS K.J/r/ SSK0J1r1J2r2J3r3J4r4 SSK'J5r5 SSK6J7r7J8r8J9r9J:r: SSK;Jr>J?r? SSK@JArB SSKCJDrD SSKEJFrF SSKGJHrHJIrIJJrJ SSKKJLrLJMrM SSKNJOrOJPrPJQrQJRrRJSrS SSKTJUrUJVrV SSKWJXrXJYrYJZrZJ[r[J\r\ SSK]J^r^J_r_J`r`Jara SSKbJcrcJdrdJereJfrf SSKQJgrgJhrhJiriJjrjJkrkJlrlJmrmJnrnJoroJprpJqrqJrrrJsrsJtrt SSKuJvrvJwrwJxrx SS KyJzrz SS!K{J|r| SS"K}J~r~Jr SS#KJr SS$KJr SS%KJrJrJrJrJr SS&KSJr SS'KJrJrJrJr SS(KJrJrJrJrJrJrJrJrJrJrJrJrJrJrJrJrJrJrJrJrJrJr SS)KJr S*\S+'SSKr\GRX(a"SS,KJr SS-KJr SS.KJr SS/KJrJrJr SS0KJr \ GRp"\5r\&GRvGRy\S15r\&GRvGRy\S25r\GR~"5r\!"S35r\$"S45r"S5S65r"S7S85r\"5r\"5rSqS9\S:'\GR"\B5SjSkS;jj5rSlSmS<jjrSnS=jr\fGRSoS>j5rSpSqS@jjrSq\GR"5rSA\SB'SrSCjrSrSDjr\"SESF55rSsSGjr"SHSI5rStSuSJjjrSSKKJr SSLKJr \"5rSM\SN'SvSOjr\S?SSSSSP.SwSQjj5r\"SRSS55r\"STSU55r\"SVSW55r\"SXSY55rS?SZ.SxS[jjrS?SSSSSP.SyS\jjrSzSSSS].S{S^jjjr"S_S`5rSjS|SajjrS}SbjrS~Scjr"SdSe\GR5rSSfjr"SgSh5rSSijrg!\a SrGNf=f)a This module implements TorchDynamo's core frame conversion functionality, transforming Python frames into FX graphs. It handles: - Frame analysis and bytecode transformation - Guard creation and management for dynamic behaviors - Cache management for recompilation - Error handling and fallback mechanisms Key classes: - ConvertFrame: Main entry point for frame conversion with error handling - ConvertFrameAssert: Implements core frame to graph conversion logic - Tracker: Tracks input/output code objects during conversion - CatchErrorsWrapper: Provides error handling and suppression logic The conversion process preserves program semantics while enabling optimizations through torch.compile() and related systems. NOTE: _torchdynamo_orig_backend is used for convert frame wrappers to identify the inner wrapped function. By going down the _torchdynamo_orig_backend chain, one can recover the original unwrapped backend, which is checked for during the Dynamo cache lookup. ) annotationsN) dataclass)Path)CellTypeCodeType FunctionType ModuleType)AnyCallableOptionalTypeVarUnion) ParamSpec) ReferenceType)GlobalStateGuard)CallbackTrigger)get_compile_pg)TensorifyState)compile_contextCompileContext CompileIdtracing) structured)compile_time_strobelight_metajustknobs_check#maybe_upload_prof_stats_to_manifoldsignpost_event)_use_lazy_graph_module)ConstraintViolationErrorGuardOnDataDependentSymNode)_forward_from_src) _WaitCounter)DistributedDataParallel)_disable_current_modes/is_in_any_mode_without_ignore_compile_internalsis_in_torch_dispatch_mode)CapturedTracebackformat_traceback_short)config decoratorsexcgraph_break_hints trace_rules)remove_dead_coderemove_pointless_jumps) check_inst_exn_tab_entries_valid Instruction is_generator propagate_inst_exn_table_entriestransform_code_object)CacheSizeRelevantForFramecompute_cache_sizeexceeds_recompile_limitis_recompilation)always_optimize_code_objects dynamo_tls skip_code TorchPatcher)augment_exc_messageBackendCompilerFailedFailOnRecompileLimitHitformat_error_msgInternalTorchDynamoError PackageErrorRecompileLimitExceededResumePrologueTracingErrorShortenTracebackSkipCodeRecursiveExceptionTorchRuntimeErrorUncapturedHigherOrderOpErrorunimplemented_v2 Unsupported)CheckFunctionManager'get_and_maybe_log_recompilation_reasons GuardedCode)Hooks)DynamoTracerOutput)log_frame_dynamic_whitelistput_code_state)ExecutionRecord)TORCH_DYNAMO_RESUME_IN_PREFIX)DistributedStateExceptionStackInstructionTranslator LocalStateSpeculationLog)is_numpy)ConvertFrameReturn FrameActionFrameExecStrategywrap_guarded_code)_get_error_on_graph_breakchromium_event_timedCleanupManagerCompileTimeInstructionCountercounters dynamo_timedformat_bytecodegen_record_file_name#get_hook_for_recompile_user_contextget_metrics_contextincrement_frame is_namedtupleistype LazyStringmaybe_disable_inference_mode*maybe_disable_inference_mode_for_fake_prop orig_code_mapreset_graph_break_dup_checkersetup_compile_debug to_int_ustroubleshooting_urlwrite_record_to_file)#torch_function_mode_stack_state_mgrzOptional[ModuleType]np) CompilerFn)CompilePackage)WrapBackendDebug) BytecodeHook CacheEntryDynamoFrameType)FrameStateSizeEntrybytecode graph_breaks_T_Pc\rSrSrSrg) TODO_UNKNOWNN)__name__ __module__ __qualname____firstlineno____static_attributes__r[/var/www/html/land-doc-ocr/venv/lib/python3.13/site-packages/torch/_dynamo/convert_frame.pyrrsrrc<\rSrSrSSjrS SjrS SjrSSjrSrg) Trackerc0/Ul[5UlgN)seensetseen_idsselfs r__init__Tracker.__init__s35 "%% rc^^[U5mTTR;aS[R"UUU4Sj5nTRR U5 TRR T5 gg)Nc:>TRRT5$r)rremove)_idxrs rTracker.add..sDMM4H4H4Mr)idrweakrefrefrappendadd)r strong_objobjrs` @rr Tracker.addsRn dmm #++j*MNC II  S ! 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KK:H E@    =  NN + +O  e + MM5 6O4*6*F + > MM. = >,! 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MM    -//v}}../   MM , , .sS9B+B B B&B+ B B B($B+'D9(B++B D66D99ET)errorr)torch.fx.experimental.validatorrrrestartrVrWrP output_graphoutput_instructionsupdate code_optionsr4r1r0r/r_torch_dynamo_tracer_output)rrlocalsbuiltinsrr tf_mode_stackrr instructionsr rMrrrrrr tracer_outputrrOrrrs ` @@@r trace_framers(W!#L " '!+#F(//*  *62 ++!!!)))) 44 QF//0(6(601A,1OP Q  (:6(N% s B C C:%C55C:cd\rSrSr%SrS\S'S\S'S\S'S S S jjrS rg ) DynamoOutputi@aS Represents the core data returned from a single dynamo run, including: - Guards, wrapped inside tracer_output.output_graph.guards - Generated bytecode - Other information needed for compilation. This data structure should capture all the "interesting" information dynamo produces on the frontend side before it enters user backend. rPrtypes.CodeTyper~zOptional[float]last_attempt_start_timeNc URRce[UURRUU(a UROSU(a UROSUUS9$)N) save_guards strict_error)rrrL guard_fail_fnguard_filter_fn)rrrsaverrs r build_guardsDynamoOutput.build_guardsOs^!!..:::#     + + #(E  d%*E ! !%  rr)NFNF) rrrzOptional[Hooks]rrrrrrrrL)rrrr__doc__rrrrrrrr@sm&%,, "&,0"      *       rrcB\rSrSr%SrS\S'S\S'S\S'S \S 'S rg ) BackendInputica Represents core data structure that dynamo will pass to a backend, including: - Graph module - Example inputs - The FakeTensorMode used for compiling graph. This data structure should capture all the information dynamo produces on for the user backend. r: backend_idtorch.fx.GraphModulerr example_inputsz,torch._subclasses.fake_tensor.FakeTensorMode fake_moderNrrrrrrrrrrrrcs O&&;;rrc.\rSrSr%SrS\S'S\S'Srg) CaptureOutputita CaptureOutput should represent all the information produced from torch compiler for a single graph capture. This intends to be consumed by various compiler frontends so that we can share as much compiler internals as possible and avoid great divergence between different stacks. This data structure should eventually contain all the information compiler produces as more refactors happens to converge different compiler frontends. r dynamo_outputr backend_inputrNr$rrrr&r&ts rr&cH\rSrSr%S\S'S\S'S\S'S\S'S\S 'S rg ) FrameInfoirrdict[str, object]rr r tuple[CellType]rrN)rrrrrrrrrr*r*s    rr*) _is_export_deprecated_do_not_usec ^^SSKJm SmSUU4Sjjn[URURUR UR URUUS[5S9 nTce[UT5$![an[U5 [R(aeUnURb6URRS5 URnURbM6URS5UReSnAff=f)a A standalone function which takes a frame and returns dynamo captured graph plus other important compile information. This should serve as the common interface for different torch compiler AOT frontengs (e.g. precompile, export). Note that this function doesn't apply context managers like metrics context or compile id, and the expectation is that the caller will apply them depending on the use case. The CaptureOutput is separated into two parts: 1. 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Backend specific information (indexed by unique backend id) such as: - fx graph - example inputs r)TracingContextNc>TR5RnUce[URS[5(de[ URSXU5mU$)Nr )rr#r-metar:r)gmr"r#r/r(s rfullgraph_compiler-fullgraph_capture..fullgraph_compilersb#&&(22 $$$"'',/5555$ GGL !2y  rT)rrMrrestart_reasons)r2r!r"zlist[torch.Tensor]rr!) torch._guardsr/ compile_framerrr r rrrKr>r*verbose __cause__with_tracebackr&)rr-r3r'rOcur_exnr/r(s @@rfullgraph_capturer<s(-,0M   2D    6% JJ MM LL NN MM*3E  .  $$ $  66  6A >> !"+    , ,T 2''G+t$!++5 6sA A77 DA$D'DDc@^^^^^^^^^ ^ ^ ^ ^[5mSUUUUU UU U UUUU U4 Sjjn Sn[R"5HTnU[R"5l[ SU3SS9 [TU 5unnUce[UUUS9sSSS5 s $ g!,(df  Mh=f![Ran[U[R5(d[R"5 [R!S[#[$UR&55 UR)UR*=(d [-[/U555 [0R0"5nUS:a[3S S S /S 9 SnAGMESnAGMLSnAf[R4aqn[U[R5(d[R"5 [R7S UTR8TR:TR<5 eSnAff=f)a  A helper function taking a frame and backend, then return the generated bytecode and guards as a common data structure. This is a shared interface for multiple compiler frontends (e.g. torch.compile, torch.export) that needs to capture a graph out of python code. c~> [RR5n[TT T TTTUTTUUT T T TTS9nUceU$)Nr)r overrides _get_current_function_mode_stackr)rr r rr rrrrrMrrrr rrrs r transform compile_frame..transformsj OO < < > $           1#/! &(((rNcompile_attempt_Tlog_pt2_compile_event)rr~rzRestarting analysis due to %sdz!Excessive RestartAnalysis() callsrzDynamo attempted to trace the same frame 100+ times. 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