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for #330, use tqdm.auto in trainer #752

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merged 3 commits into from
Jan 26, 2020
Merged

for #330, use tqdm.auto in trainer #752

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d52f9d5
use tqdm.auto in trainer
wassname Jan 26, 2020
b41f76c
use `from tqdm.auto` in eval loop
wassname Jan 26, 2020
7ca9f11
indents
wassname Jan 26, 2020
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8 changes: 4 additions & 4 deletions pytorch_lightning/trainer/evaluation_loop.py
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Original file line number Diff line number Diff line change
Expand Up @@ -127,7 +127,7 @@
from abc import ABC, abstractmethod

import torch
import tqdm
from tqdm.auto import tqdm

from pytorch_lightning.utilities.debugging import MisconfigurationException

Expand Down Expand Up @@ -293,9 +293,9 @@ def run_evaluation(self, test=False):
# main progress bar will already be closed when testing so initial position is free
position = 2 * self.process_position + (not test)
desc = 'Testing' if test else 'Validating'
pbar = tqdm.tqdm(desc=desc, total=max_batches, leave=test, position=position,
disable=not self.show_progress_bar, dynamic_ncols=True,
unit='batch', file=sys.stdout)
pbar = tqdm(desc=desc, total=max_batches, leave=test, position=position,
disable=not self.show_progress_bar, dynamic_ncols=True,
unit='batch', file=sys.stdout)
setattr(self, f'{"test" if test else "val"}_progress_bar', pbar)

# run evaluation
Expand Down
12 changes: 6 additions & 6 deletions pytorch_lightning/trainer/trainer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@
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
Expand Down Expand Up @@ -808,13 +808,13 @@ def run_pretrain_routine(self, model):
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()),
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just formatting to pass flake8

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)
Expand All @@ -828,9 +828,9 @@ def run_pretrain_routine(self, model):
self.early_stop_callback.check_metrics(callback_metrics)

# init progress bar
pbar = tqdm.tqdm(leave=True, position=2 * self.process_position,
disable=not self.show_progress_bar, dynamic_ncols=True, unit='batch',
file=sys.stdout)
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

# clear cache before training
Expand Down