How to do a full validation loop at iteration 0?

[jonaskohler]

Hi all

I have two issues with logging in lightning:
First, I would like to run a full validation loop in the beginning to get the validation loss at random initialziation.

Second, I set "log_every_n_steps=100" for the pl.Trainer and would have expected the trainer to log also at initialization 0 but it starts at 100.

Thus, I cannot see how the network behaves at initialization neither on the train nor the validation set. I tried to find a fix in the documentation but didn't succeed.

Any help is highly appreciated :)

[github-actions]

Hi! thanks for your contribution!, great first issue!

[ydcjeff]

First, if you would like to run validation before training in the first, you can use https://pytorch-lightning.readthedocs.io/en/latest/trainer.html#num-sanity-val-steps

Second, setting up log_every_n_steps=100 will only log at every 100 steps
if you would like to log at 0, you can check batch_idx==0 in training/validation_step and log what you want.

[rohitgr7]

will it makes sense to allow logging at global_step == 0?

[williamFalcon]

will it makes sense to allow logging at global_step == 0?

not sure... what does everyone think?

[jonaskohler]

Thanks for your answers. For me (speaking from a research perspective) it is definitely useful to know what's happening right at initialization. For example when examining different initialization schemes.

[williamFalcon]

yeah, i don’t think i mind logging batch 0.

@ananthsub?

[jonaskohler]

Please allow me a follow up question: When passing num_sanity_val_steps=-1 to the trainer, the method validation_epoch_end is called at iteration 0 but for some reason nothing is logged. I tried both self.log(..) as well as logs={...}, return 'log':logs.

As soon as the first epoch is over, everything logs as normal. What do I need to do to trigger the first log to show up on tensorboard? Thanks in advance

[ananthsub]

Logging at global step 0 sounds good to me. I think it'd simplify the logging internals too from (global step + 1) % log_every_n_steps to just (global step) % log_every_n_steps.

[rohitgr7]

(global step) % log_every_n_steps.

global_step is indexed at 0, so if log_every_n_steps = 10, it will log at 1, 11, 21 training_step .

[eladar]

Hi,
I've somewhat similar question - Is there any way to log the first training epoch (or several iteration) without doing optimization?
I want to get baseline for the initialized model and compare loss values both on training and validation samples.

Thanks in advance,
-ea

[stale]

This issue has been automatically marked as stale because it hasn't had any recent activity. This issue will be closed in 7 days if no further activity occurs. Thank you for your contributions, Pytorch Lightning Team!