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cudagraphszGLogs information from wrapping inductor generated code with cudagraphs.ÚdynamicÚtorchÚdistributedÚc10dz"torch.distributed.distributed_c10dztorch.distributed.rendezvousÚddpr   r   Úppztorch.distributed.pipeliningÚfsdpztorch.distributed.fsdpz"torch.distributed._composable.fsdpÚdtensorztorch.distributed._tensorztorch.distributed.tensorÚonnxz
torch.onnxÚexportztorch.exportztorch.export.dynamic_shapesztorch._export.converterztorch._export.non_strict_utilsztorch._export.serde.serializez"torch.fx.experimental.proxy_tensorÚguardszhThis prints the guards for every compiled Dynamo frame. It does not tell you where the guards come from.T)ÚvisibleÚverbose_guardsÚ )Úoff_by_defaultÚbytecodez{Prints the original and modified bytecode from Dynamo. Mostly useful if you're debugging our bytecode generation in Dynamo.ÚgraphzvPrints the dynamo traced graph (prior to AOTDispatch) in a table. If you prefer python code use `graph_code` instead. Ú
graph_codez4Like `graph`, but gives you the Python code instead.Úgraph_code_verbosezLVerbose FX pass logs, e.g. from tensorify_python_scalars and runtime_assert.Úgraph_sizesz5Prints the sizes of all FX nodes in the dynamo graph.Útrace_sourcezAs we execute bytecode, prints the file name / line number we are processing and the actual source code. Useful with `bytecode`Ú
trace_callzhLike trace_source, but it will give you the per-expression blow-by-blow if your Python is recent enough.Útrace_bytecodezCAs we trace bytecode, prints the instruction and the current stack.Ú
aot_graphszŠPrints the FX forward and backward graph generated by AOTDispatch, after partitioning. Useful to understand what's being given to InductorÚaot_joint_graphz_Print FX joint graph from AOTAutograd, prior to partitioning. Useful for debugging partitioningÚaot_graphs_effectszkPrints the FX forward and backward graph generated by AOTDispatch, useful for debugging effects processing.Úpre_grad_graphsz{Prints the FX graph before inductor pre grad passes. Useful to understand what's being given to Inductor before grad passesÚpost_grad_graphsz}Prints the FX graph generated by post grad passes. Useful to understand what's being given to Inductor after post grad passesÚir_pre_fusionz,Prints the IR before inductor fusion passes.Úir_post_fusionz+Prints the IR after inductor fusion passes.Úcompiled_autogradzzPrints various logs in compiled_autograd, including but not limited to the graphs. Useful for debugging compiled_autograd.Úcompiled_autograd_verbosezjWill affect performance. Prints compiled_autograd logs with C++ info e.g. autograd node -> fx node mappingÚ
ddp_graphsz„Only relevant for compiling DDP. DDP splits into multiple graphs to trigger comms early. This will print each individual graph here.Ú
recompilesz?Prints the reason why we recompiled a graph. Very, very useful.Úrecompiles_verbosezÅPrints all guard checks that fail during a recompilation. At runtime, Dynamo will stop at the first failed check for each failing guard. So not all logged failing checks are actually ran by Dynamo.)r   r   Úgraph_breaksz’Prints whenever Dynamo decides that it needs to graph break (i.e. create a new graph). Useful for debugging why torch.compile has poor performanceÚside_effectszžPrints all side effects that Dynamo codegenerates, including mutations to variables, attributes, cells, and globals. Useful for debugging side effect handlingÚnot_implementedzŒPrints log messages whenever we return NotImplemented in a multi-dispatch, letting you trace through each object we attempted to dispatch toÚoutput_codez>Prints the code that Inductor generates (either Triton or C++))r   r   Úkernel_codez?Prints the code that Inductor generates (on a per-kernel basis)ÚschedulezIInductor scheduler information. Useful if working on Inductor fusion algoÚ
perf_hintsÚonnx_diagnosticsÚcompute_dependenciesÚfusionzADetailed Inductor fusion decisions. More detailed than 'schedule'Úloop_orderingzLogs related to loop orderingÚloop_tilingÚauto_chunkerz Logs related to the auto chunkerÚoverlapz0Detailed Inductor compute/comm overlap decisionsÚoverlap_schedulingz5Detailed Inductor overlap scheduling pass informationÚsym_nodez.Logs extra info for various SymNode operationsÚtrace_shape_eventszBLogs traces for every ShapeEnv operation that we record for replayÚcudagraph_static_inputsz:Logs static inputs handling in dynamo, AOT, and cudagraphsÚbenchmarkingz+Detailed Inductor benchmarking information.Únode_runtime_estimationz@Node runtime estimation for compile-time optimization decisions.Ú
autotuningzKAutotuning choice logs, such as kernel source, perf, and tuning parameters.Úgraph_region_expansionzMLogs detailed steps of the duplicate graph region tracker expansion algorithmÚinductor_metricszGLogs Inductor metrics, such as num_bytes, nodes_num_elem, node_runtimesÚhierarchical_compilez,Logs debug info for hierarchical compilationÚ
annotationz=Logs detailed steps of the creating annotation on graph nodesÚcustom_format_test_artifactzTesting only)Ú
log_formatÚcachingz&Detailed Inductor caching information.N)Ú	_internalr   r   ÚDYNAMICÚDISTRIBUTED© ó    ú\/var/www/html/ia-enhanced/venv/lib/python3.12/site-packages/torch/_logging/_registrations.pyú<module>rT      só  ðç 6ò€ò
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