Trigger creation of lazy logger experiment in Trainer setup #17818
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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Jirka Borovec <[email protected]> (cherry picked from commit d4867cb)
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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Jirka Borovec <[email protected]> (cherry picked from commit d4867cb)
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What does this PR do?
Fixes #17298
Explanation:
Some loggers have a lazy experiment creation, because their experiments are non-picklable. Thus, one should only call
logger.experimentonce we've spawned/forked processes. The trainer respects this requirement, but until the first logging call, for some loggers like WandbLogger properties likelogger.versionandlogger.nameremain undefined until the first call oflogger.experiment. This is a problem for e.g. model checkpointing, when the checkpoint callback is resolving the log dir to put checkpoints in:https://github.com/Lightning-AI/lightning/blob/d75bfe5c387925d6b2297cdedd49055f93d6b4ef/src/lightning/pytorch/callbacks/model_checkpoint.py#L599-L600
Thus, I'm now introducing a triggering mechanism that ensures experiment attributes will always be available no earlier than when the setup hook gets called. Alternatively, we could also introduce a
lazy_init()method on the logger base interface that we call at the same place in the trainer.The fix is not specific to wandb, applies to neptune as well, but it was reported with wandb.
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cc @Borda @awaelchli @morganmcg1 @borisdayma @scottire @parambharat