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36bb7a1f42
This adds some utilities for conveniently working with fast combined CapturedTraceback from Python. The main goal of these utilities is to make it easier for people to use CapturedTraceback as a drop-in replacement for `traceback.extract_stack`, which is 20x slower than CapturedTraceback. I port symbolic shapes to use the new CapturedTraceback code, to validate that the APIs work and are useful. Signed-off-by: Edward Z. Yang <ezyang@meta.com> Pull Request resolved: https://github.com/pytorch/pytorch/pull/107358 Approved by: https://github.com/zdevito, https://github.com/albanD ghstack dependencies: #107438
16 lines
716 B
Python
16 lines
716 B
Python
# Top level logging module for torch logging
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# Design doc: https://docs.google.com/document/d/1ZRfTWKa8eaPq1AxaiHrq4ASTPouzzlPiuquSBEJYwS8/edit#
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# Simple setup for onboarding (see above doc for more detail):
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# 1. register any top-level log qualified name for your module in torch._logging._registrations (see there for examples)
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# 2. register any artifacts (<artifact_name> below) in torch._logging._registrations
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# a. call getArtifactLogger(__name__, <artifact_name>) at your logging site instead of the standard logger to log your artifact
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import torch._logging._registrations
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from ._internal import (
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_init_logs,
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DEFAULT_LOGGING,
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getArtifactLogger,
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LazyString,
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set_logs,
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warning_once,
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)
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