Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance

 

Try #1

from pytorch_lightning.strategies.ddp import DDPStrategy

trainer = pl.Trainer(

strategy = DDPStrategy(find_unused_parameters=False),

accelerator = 'gpu',

devices = 3

)

..

Try #2

from pytorch_lightning.plugins import DDPPlugin

trainer = pl.Trainer(

val_check_interval=0.1,

gpus=-1,

accelerator="ddp",

callbacks=[checkpoint_callback, early_stop_callback],

plugins=DDPPlugin(find_unused_parameters=False),

precision=16,

)

..

Thank you.

pytorch lightning change checkpoints output dir and version str

 

Use "save_dir",  "name",  "version" params in pl_loggers function.

more detail : https://pytorch-lightning.readthedocs.io/en/stable/extensions/generated/pytorch_lightning.loggers.TensorBoardLogger.html

..

from pytorch_lightning import loggers as pl_loggers

tb_logger = pl_loggers.TensorBoardLogger(save_dir="logs", name='no_default', version='my_version_2')

trainer = Trainer(max_epochs=num_epochs, callbacks=[checkpoint_callback], logger=tb_logger)

..

And you can retrieve what is my logging path by:

tb_logger.log_dir or self.logger.log_dir (in class)

> logs/no_default/my_version_2

Thank you.

www.marearts.com

🙇🏻‍♂️