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ENH: Add lightning.Trainer config, fix #691 #687 #742 #745 #752
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…f torch.cuda.is_available
…splits.py: :constant: -> :const:
…htning.pytorch everywhere instead of pytorch_lightning as lightning -- trying to make it so we can resolve API correctly in docstrings
…id-version-1.1.toml
…remove 'device' attribute
…g; remove 'device' attribute
… remove 'device' attribute
…nfig; remove 'device' attribute. Also clean up docstring, removing attributes that no longer exist
…od of EvalConfig/LearncurveConfig/PredictConfig/TrainConfig
…ble.device attribute that no longer exists
…ainer must be > 0
… over-ride config in toml file
…ne place in tests/test_eval/
… to put tensors on device, not to change a config
…witched to using lightning as the dependency
This was referenced May 5, 2024
NickleDave
added a commit
that referenced
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May 6, 2024
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This adds a
trainer
table to thetrain
/eval
/predict
/learncurve
tables in the configuration file, with keysaccelerator
anddevices
, like so:Those keys gets passed directly to
lightning.Trainer
as the corresponding parameters when instantiating. For now we only allowdevices
to be a list of a single int whenaccelerator
is anything besidescpu
, e.g.gpu
, to fix the bugs in #742 #745 #687