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use tqdm.auto in trainer

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This will import the ipywidgets version of tqdm if available. This works nicely in notebooks by not filling up the log.

In the terminal it will use the same old tqdm.

We might also want to consider passing in the tqdm we want as an argument since there may be some edge cases where ipywidgets is available but the interface doesn't support it (e.g. vscode?) or isn't working. In which case people will get a warning message, but may want to configure it themselves.
This commit is contained in:
Mike Clark
2020-01-26 00:19:23 +00:00
committed by GitHub
parent b35c472bb1
commit d52f9d5227
1 changed files with 4 additions and 4 deletions
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pytorch_lightning/trainer/trainer.py
+4 -4
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@@ -7,7 +7,7 @@ import logging
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
import tqdm
from tqdm.auto import tqdm
from torch.optim.optimizer import Optimizer
from pytorch_lightning.trainer.auto_mix_precision import TrainerAMPMixin
@@ -808,13 +808,13 @@ class Trainer(TrainerIOMixin,
ref_model.on_train_start()
if not self.disable_validation and self.num_sanity_val_steps > 0:
# init progress bars for validation sanity check
pbar = tqdm.tqdm(desc='Validation sanity check',
pbar = tqdm(desc='Validation sanity check',
total=self.num_sanity_val_steps * len(self.get_val_dataloaders()),
leave=False, position=2 * self.process_position,
disable=not self.show_progress_bar, dynamic_ncols=True, unit='batch')
self.main_progress_bar = pbar
# dummy validation progress bar
self.val_progress_bar = tqdm.tqdm(disable=True)
self.val_progress_bar = tqdm(disable=True)
eval_results = self.evaluate(model, self.get_val_dataloaders(),
self.num_sanity_val_steps, False)
@@ -828,7 +828,7 @@ class Trainer(TrainerIOMixin,
self.early_stop_callback.check_metrics(callback_metrics)
# init progress bar
pbar = tqdm.tqdm(leave=True, position=2 * self.process_position,
pbar = tqdm(leave=True, position=2 * self.process_position,
disable=not self.show_progress_bar, dynamic_ncols=True, unit='batch',
file=sys.stdout)
self.main_progress_bar = pbar