Update to autotqdm, improve example

baal/active/active_loop.py

@@ -11,7 +11,7 @@
 from . import heuristics
 from .dataset import ActiveLearningDataset
 
-log = structlog.get_logger(__name__)
+log = structlog.get_logger('baal')
 pjoin = os.path.join
 
 

baal/active/heuristics/stochastics.py

@@ -7,7 +7,7 @@
 
 from baal.active.heuristics import AbstractHeuristic, Sequence
 
-log = structlog.get_logger(__name__)
+log = structlog.get_logger('baal')
 EPSILON = 1e-8
 
 

baal/calibration/calibration.py

@@ -11,7 +11,7 @@
 from baal.modelwrapper import TrainingArgs
 from baal.utils.metrics import ECE, ECE_PerCLs
 
-log = structlog.get_logger("Calibrating...")
+log = structlog.get_logger("baal")
 
 
 class DirichletCalibrator(object):

baal/experiments/base.py

@@ -4,7 +4,7 @@
 import numpy as np
 import structlog
 from torch.utils.data import Subset
-from tqdm import tqdm
+from tqdm.autonotebook import tqdm
 
 from baal import ModelWrapper, ActiveLearningDataset
 from baal.active.dataset.base import Dataset
@@ -24,7 +24,7 @@
     TransformersAdapter = None  # type: ignore
     TRANSFORMERS_AVAILABLE = False
 
-log = structlog.get_logger(__name__)
+log = structlog.get_logger('baal')
 
 
 class ActiveLearningExperiment:
@@ -78,7 +78,10 @@ def start(self):
                 "No item labelled in the training set."
                 " Did you run `ActiveLearningDataset.label_randomly`?"
             )
-        for _ in tqdm(itertools.count(start=0)):
+        for _ in tqdm(itertools.count(start=0),  # Infinite counter to rely on Criterion
+                      desc="Active Experiment",
+                      # Upper bound estimation.
+                      total=np.round(self.al_dataset.n_unlabelled // self.query_size)):
             self.adapter.reset_weights()
             train_metrics = self.adapter.train(self.al_dataset)
             eval_metrics = self.adapter.evaluate(

baal/modelwrapper.py

@@ -12,7 +12,7 @@
 from torch.optim import Optimizer
 from torch.utils.data import DataLoader
 from torch.utils.data.dataloader import default_collate
-from tqdm import tqdm
+from tqdm.autonotebook import tqdm
 
 from baal.active.dataset.base import Dataset
 from baal.metrics.mixin import MetricMixin
@@ -23,7 +23,7 @@
 from baal.utils.metrics import Loss
 from baal.utils.warnings import raise_warnings_cache_replicated
 
-log = structlog.get_logger("ModelWrapper")
+log = structlog.get_logger("baal")
 
 
 def _stack_preds(out):

baal/transformers_trainer_wrapper.py

@@ -22,7 +22,7 @@
 from baal.utils.array_utils import stack_in_memory
 from baal.utils.iterutils import map_on_tensor
 
-log = structlog.get_logger("BaalTransformersTrainer")
+log = structlog.get_logger("baal")
 
 
 def _stack_preds(out):

baal/utils/pytorch_lightning.py

@@ -18,7 +18,7 @@
 from baal.utils.cuda_utils import to_cuda
 from baal.utils.iterutils import map_on_tensor
 
-log = structlog.get_logger("PL testing")
+log = structlog.get_logger("baal")
 
 warnings.warn(
     "baal.utils.pytorch_lightning is deprecated. BaaL is now integrated into Lightning Flash!"

experiments/pytorch_lightning/active_image_classification.py

@@ -22,7 +22,7 @@
     BaaLDataModule,
 )
 
-log = structlog.get_logger("PL testing")
+log = structlog.get_logger("baal")
 
 warnings.warn(
     "baal.utils.pytorch_lightning is deprecated. BaaL is now integrated into Lightning Flash!"

experiments/pytorch_lightning/lightning_flash_example.py

@@ -29,7 +29,7 @@
 
 from baal.active import get_heuristic
 
-log = structlog.get_logger()
+log = structlog.get_logger('baal')
 
 IMG_SIZE = 128