Disabling Validation Progress Bar

[ludwigwinkler]

Hi,

I would like to disable the validation progress bar via a custom TQDMProgressBar.
I'm logging the validation performance anyway, so an extra visual hint that the model is currently validating is unnecessary for me.

class CustomTQDMProgressBar(TQDMProgressBar):
	def __init__(self, refresh_rate=10, per_epoch_progress_bar=False, prefix=None):
		super().__init__(refresh_rate)
		self.prefix = prefix  # self.per_epoch_progress_bar= per_epoch_progress_bar
		self.per_epoch_progress_bar = per_epoch_progress_bar
	
        # overwrote the on_train_epoch_start to add a custom prefix
	def on_train_epoch_start(self, trainer: "pl.Trainer", *_: Any) -> None:
		total_train_batches = self.total_train_batches
		
		total_val_batches = self.total_val_batches
		if total_train_batches != float("inf") and total_val_batches != float("inf"):
			# val can be checked multiple times per epoch
			val_checks_per_epoch = total_train_batches // trainer.val_check_batch
			total_val_batches = total_val_batches * val_checks_per_epoch
		total_batches = total_train_batches + total_val_batches
		self.main_progress_bar.reset(convert_inf(total_batches))
		self.main_progress_bar.set_description(f"{self.prefix} Epoch {trainer.current_epoch}" if self.prefix is not None else f"Epoch {trainer.current_epoch}")
	
	def init_sanity_tqdm(self) -> tqdm:
		bar = tqdm(desc=f"{self.prefix} Validating",
		           position=(2 * self.process_position + 1),
		           # disable=self.is_disabled, # by Ludi
		           disable=True,
		           leave=False,
		           dynamic_ncols=True,
		           file=sys.stdout, )
		return bar
	
	def init_train_tqdm(self) -> tqdm:
		"""Override this to customize the tqdm bar for training."""
		bar = Tqdm(desc=self.train_description,
		           initial=self.train_batch_idx,
		           position=(2 * self.process_position),
		           disable=self.is_disabled,
		           leave=True,
		           dynamic_ncols=True,
		           file=sys.stdout,
		           smoothing=0,
		           bar_format="{l_bar}{r_bar}")
		
		return bar
	
	
	def init_validation_tqdm(self) -> Tqdm:
		"""Override this to customize the tqdm bar for validation."""
		# The main progress bar doesn't exist in `trainer.validate()`
		has_main_bar = self.trainer.state.fn != "validate"
		bar = Tqdm(desc=self.validation_description,
		           position=(2 * self.process_position + has_main_bar),
		           disable=True,
		           leave=not has_main_bar,
		           dynamic_ncols=True,
		           file=sys.stdout)
		# print(f'val: {bar.disable=}')
		return bar

Tqdm(disable=True) doesn't do the trick, so what does?

Ideally, I just let the main bar run from batch 0 to batch number len(train_dataloader)+len(val_dataloader) all in a single progress bar and the logged validation metrics are only updated once the training loop is in the validate state.

Thanks in advance!

[wujyuhin]

class MyProgressBar(TQDMProgressBar):
    def init_validation_tqdm(self):
        bar = super().init_validation_tqdm()
        if not sys.stdout.isatty():
            bar.disable = True
        return bar

    def init_predict_tqdm(self):
        bar = super().init_predict_tqdm()
        if not sys.stdout.isatty():
            bar.disable = True
        return bar

    def init_test_tqdm(self):
        bar = super().init_test_tqdm()
        if not sys.stdout.isatty():
            bar.disable = True
        return bar

trainer = pl.Trainer(
    ...
    callbacks=[MyProgressBar()],
)