o ‡ZŽhêã@sŽdZddlZddlmZmZmZmZddlmZm Z m Z ddl m Z m Z mZddlmZddlmZdd lmZmZmZmZmZmZmZmZmZmZmZmZmZmZdd lm Z m!Z!m"Z"m#Z#m$Z$m%Z%m&Z&m'Z'm(Z(dd l)m*Z*dd l+m,Z,dd l-m.Z.ddl/m0Z0ddl1m2Z2m3Z3m4Z4m5Z5ddl6m7Z8gd¢Z9ej: ;ejej?j>ur»ddl@Ze Aej>¡e_>ejBjC Dej>d¡ddd„ZEddd„ZFdS)až TorchDynamo is a Python-level JIT compiler designed to make unmodified PyTorch programs faster. TorchDynamo hooks into the frame evaluation API in CPython (PEP 523) to dynamically modify Python bytecode right before it is executed. It rewrites Python bytecode in order to extract sequences of PyTorch operations into an FX Graph which is then just-in-time compiled with a customizable backend. It creates this FX Graph through bytecode analysis and is designed to mix Python execution with compiled backends to get the best of both worlds: usability and performance. This allows it to seamlessly optimize PyTorch programs, including those using modern Python features. éNé)ÚconfigÚ convert_frameÚ eval_frameÚresume_execution)Ú list_backendsÚlookup_backendÚregister_backend)Úcallback_handlerÚon_compile_endÚon_compile_start)Ú code_context)Úreplay)Úallow_in_graphÚassume_constant_resultÚdisableÚdisallow_in_graphÚforbid_in_graphÚ graph_breakÚ mark_dynamicÚ mark_staticÚmark_static_addressÚmaybe_mark_dynamicÚnonstrict_traceÚrunÚ set_stanceÚsubstitute_in_graph) Ú_reset_guarded_backend_cacheÚexplainÚexportÚis_dynamo_supportedÚis_inductor_supportedÚoptimizeÚoptimize_assertÚOptimizedModuleÚ reset_code)Ú is_compiling)ÚGenerationTracker)Úreset_code_state)ÚTensorifyState)Úgraph_break_reasonsÚguard_failuresÚ orig_code_mapÚreset_frame_count)Úloader)rrrrrrrrrrrr"r#rrrrrrÚresetr$r&r rrrzaten::manual_seedÚreturncCsöddl}| t¡}| d¡tj`tƒtj ¡t ƒtj  ¡t  ¡t  ¡t  ¡tjj ¡tƒtƒtjj ¡dt_tj ¡t ¡t ¡t ¡tjjj ¡tjjj ¡tjj  !d¡WdƒdS1stwYdS)a± Clear all compile caches and restore initial state. This function is intended to reset Dynamo's state *as if* you had started a fresh process invocation, which makes it good for testing scenarios where you want to behave as if you started a new process. It does NOT affect any file system caches. NB: this does NOT reset logging state. Don't use this to test logging initialization/reinitialization. rNztorch._dynamo.resetF)"ÚloggingÚ getLoggerÚ__name__ÚinforÚ compile_lockÚreset_code_cachesÚ input_codesÚclearr(Ú output_codesr,r+r*rZContinueExecutionCacheÚcacherr-ÚtorchÚ_dynamoZcompiled_autogradr/Z FRAME_COUNTERZFRAME_COMPILE_COUNTERr r'r)ÚutilsZwarn_once_cacheZuser_obj_id_to_weakrefZ_CZ _autogradZ _saved_tensors_hooks_set_tracing)r1Úlog©r?úE/var/www/auris/lib/python3.10/site-packages/torch/_dynamo/__init__.pyr/bs0       "ír/cCs€ddl}| t¡}| d¡ tj$tƒtjjtj jD] }|ƒ}|r)t |ƒqt   ¡WdƒdS1s9wYdS)z¯ Clears in-memory code cache, which is what stores compiled products. This resets less state than :func:`reset` and is mostly only used for testing purposes. rNztorch._dynamo.reset_code_caches) r1r2r3r4rr5r(r7Úseenr9r%r r8)r1r>Z weak_codeÚcoder?r?r@r6‡s  ÿ€ "ør6)r0N)GÚ__doc__r;ÚrrrrZbackends.registryrrr Úcallbackr r r r rZ decoratorsrrrrrrrrrrrrrrrrrr r!r"r#r$r%Zexternal_utilsr&Zmutation_guardr'Zpgor(Zsymbolic_convertr)r=r*r+r,r-Z polyfillsr.Ú_Ú__all__Z serializationZadd_safe_globalsr<Z _DimRangeZ manual_seedÚrandomZtorch.jit._builtinsZ_disable_dynamoZjitZ _builtinsZ_register_builtinr/r6r?r?r?r@Ús.   @,     %