pytorch

a1c46e5f - component-level configurable logging for dynamo, inductor, aot (#94858)

component-level configurable logging for dynamo, inductor, aot (#94858) Summary: Adds NNC-like logging that is configured through an env var `TORCH_COMPILE_LOGS` Examples: `TORCH_LOGS="dynamo,guards" python script.py` - prints dynamo logs at level INFO with guards of all functions that are compiled `TORCH_LOGS="+dynamo,guards,graph" python script.py` - prints dynamo logs at level DEBUG with guards and graphs (in tabular) format of all graphs that are compiled [More examples with full output](https://gist.github.com/mlazos/b17f474457308ce15e88c91721ac1cce) Implementation: The implementation parses the log settings from the environment, finds any components (aot, dynamo, inductor) or other loggable objects (guards, graph, etc.) and generates a log_state object. This object contains all of the enabled artifacts, and a qualified log name -> level mapping. _init_logs then adds handlers to the highest level logs (the registered logs), and sets any artifact loggers to level DEBUG if the artifact is enabled. Note: set_logs is an alternative for manipulating the log_state, but if the environment contains TORCH_LOGS, the environment settings will be prioritized. Adding a new log: To add a new log, a dev should add their log name to torch._logging._registrations (there are examples there already). Adding a new artifact: To add a new artifact, a dev should add their artifact name to torch._logging._registrations as well. Additionally, wherever the artifact is logged, `torch._logging.getArtifactLogger(__name__, <artifact_name>)` should be used instead of the standard logging implementation. [design doc](https://docs.google.com/document/d/1ZRfTWKa8eaPq1AxaiHrq4ASTPouzzlPiuquSBEJYwS8/edit#) Pull Request resolved: https://github.com/pytorch/pytorch/pull/94858 Approved by: https://github.com/ezyang