def main(hparams):
"""Main training routine specific for this project."""
# ------------------------
# 1 INIT LIGHTNING MODEL
# ------------------------
model = LightningTemplateModel(hparams)
# ------------------------
# 2 INIT TRAINER
# ------------------------
trainer = pl.Trainer(gpus=2, num_nodes=2, distributed_backend='ddp')
# ------------------------
# 3 START TRAINING
# ------------------------
trainer.fit(model)
def main(hparams):
"""
Main training routine specific for this project
:param hparams:
"""
# ------------------------
# 1 INIT LIGHTNING MODEL
# ------------------------
model = LightningTemplateModel(hparams)
# ------------------------
# 2 INIT TRAINER
# ------------------------
trainer = pl.Trainer()
# ------------------------
# 3 START TRAINING
# ------------------------
trainer.fit(model)
def main(hparams):
"""
Main training routine specific for this project
:param hparams:
"""
# ------------------------
# 1 INIT LIGHTNING MODEL
# ------------------------
model = LightningTemplateModel(hparams)
# ------------------------
# 2 INIT TRAINER
# ------------------------
trainer = Trainer(gpus=hparams.gpus,
distributed_backend=hparams.distributed_backend,
use_amp=hparams.use_16bit)
# ------------------------
# 3 START TRAINING
# ------------------------
trainer.fit(model)
model = LightningTemplateModel(hparams)
# ------------------------
# 2 INIT TRAINER
# ------------------------
trainer = pl.Trainer()
# ------------------------
# 3 START TRAINING
# ------------------------
trainer.fit(model)
if __name__ == '__main__':
# ------------------------
# TRAINING ARGUMENTS
# ------------------------
# these are project-wide arguments
root_dir = os.path.dirname(os.path.realpath(__file__))
parent_parser = ArgumentParser(add_help=False)
# each LightningModule defines arguments relevant to it
parser = LightningTemplateModel.add_model_specific_args(
parent_parser, root_dir)
hyperparams = parser.parse_args()
# ---------------------
# RUN TRAINING
# ---------------------
main(hyperparams)