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import os | |
import lightning.pytorch as pl | |
from lightning.pytorch.utilities import rank_zero_only | |
class CheckpointEveryNSteps(pl.Callback): | |
def __init__( | |
self, | |
checkpoints_dir, | |
save_step_frequency, | |
) -> None: | |
r"""Save a checkpoint every N steps. | |
Args: | |
checkpoints_dir (str): directory to save checkpoints | |
save_step_frequency (int): save checkpoint every N step | |
""" | |
self.checkpoints_dir = checkpoints_dir | |
self.save_step_frequency = save_step_frequency | |
def on_train_batch_end(self, *args, **kwargs) -> None: | |
r"""Save a checkpoint every N steps.""" | |
trainer = args[0] | |
global_step = trainer.global_step | |
if global_step == 1 or global_step % self.save_step_frequency == 0: | |
ckpt_path = os.path.join( | |
self.checkpoints_dir, | |
"step={}.ckpt".format(global_step)) | |
trainer.save_checkpoint(ckpt_path) | |
print("Save checkpoint to {}".format(ckpt_path)) | |