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Save Axolotl config as WandB artifact #716

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merged 5 commits into from
Oct 11, 2023
Merged

Save Axolotl config as WandB artifact #716

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76b280c
saver axolotl config to wandb
Oct 11, 2023
2bb79c0
format fix
jphme Oct 11, 2023
3c4495e
fix
jphme Oct 11, 2023
b48ede8
error handling and log
jphme Oct 11, 2023
2759f00
only pass config path
jphme Oct 11, 2023
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1 change: 1 addition & 0 deletions src/axolotl/cli/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -194,6 +194,7 @@ def load_cfg(config: Path = Path("examples/"), **kwargs):
# load the config from the yaml file
with open(config, encoding="utf-8") as file:
cfg: DictDefault = DictDefault(yaml.safe_load(file))
cfg.axolotl_config_path = config
# if there are any options passed in the cli, if it is something that seems valid from the yaml,
# then overwrite the value
cfg_keys = cfg.keys()
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24 changes: 24 additions & 0 deletions src/axolotl/utils/callbacks.py
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Expand Up @@ -514,3 +514,27 @@ def log_table_from_dataloader(name: str, table_dataloader):
return control

return LogPredictionCallback


class SaveAxolotlConfigtoWandBCallback(TrainerCallback):
"""Callback to save axolotl config to wandb"""

def __init__(self, cfg):
self.cfg = cfg

def on_train_begin(
self,
args: AxolotlTrainingArguments, # pylint: disable=unused-argument
state: TrainerState, # pylint: disable=unused-argument
control: TrainerControl,
**kwargs, # pylint: disable=unused-argument
):
if is_main_process():
try:
artifact = wandb.Artifact(name="axolotl-config", type="config")
artifact.add_file(local_path=self.cfg.axolotl_config_path)
wandb.run.log_artifact(artifact)
LOG.info("Axolotl config has been saved to WandB as an artifact.")
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maybe log.debug is enough

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Im indifferent, we log/print 20+ lines of Wandb initialization (and hundreds of lines on training begin) anyway, wouldn't it make sense to leave it at info to make people aware that their config is archived - how should anyone (except us) ever find/know it otherwise?
With an explicit (short) statement after successful archivation in the log, people then know that they can e.g safely overwrite their config.yml for a new experiment.

But happy to change that as well, whats your opinion @winglian ?

except (FileNotFoundError, ConnectionError) as err:
LOG.warning(f"Error while saving Axolotl config to WandB: {err}")
return control
4 changes: 4 additions & 0 deletions src/axolotl/utils/trainer.py
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Expand Up @@ -30,6 +30,7 @@
from axolotl.utils.callbacks import (
EvalFirstStepCallback,
GPUStatsCallback,
SaveAxolotlConfigtoWandBCallback,
SaveBetterTransformerModelCallback,
bench_eval_callback_factory,
log_prediction_callback_factory,
Expand Down Expand Up @@ -775,6 +776,9 @@ def setup_trainer(cfg, train_dataset, eval_dataset, model, tokenizer, total_num_
LogPredictionCallback = log_prediction_callback_factory(trainer, tokenizer)
trainer.add_callback(LogPredictionCallback(cfg))

if cfg.use_wandb:
trainer.add_callback(SaveAxolotlConfigtoWandBCallback(cfg))
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if cfg.do_bench_eval:
trainer.add_callback(bench_eval_callback_factory(trainer, tokenizer))

Expand Down