  if T.TYPE_CHECKING:
      import argparse
      from lib.config import ConfigValueType
  
  logger = logging.getLogger(__name__)  # pylint: disable=invalid-name
  _CONFIG: dict[str, ConfigValueType] = {}
  
  
 
</s> remove     from collections.abc import Callable, Generator
 </s> add     from collections.abc import Callable </s> remove logger = logging.getLogger(__name__)  # pylint: disable=invalid-name
 </s> add logger = logging.getLogger(__name__) </s> remove matplotlib.use("TkAgg")

 </s> add  </s> remove from lib.training import PreviewDataGenerator, TrainingDataGenerator
from lib.training.generator import BatchType, DataGenerator
 </s> add from lib.training import Feeder, LearningRateFinder </s> remove from .generator import PreviewDataGenerator, TrainingDataGenerator
 </s> add from .generator import Feeder
from .lr_finder import LearningRateFinder
keras = tf.keras
K = tf.keras.backend


  if T.TYPE_CHECKING:
      import argparse
      from lib.config import ConfigValueType
  
keras = tf.keras
K = tf.keras.backend


  logger = logging.getLogger(__name__)  # pylint: disable=invalid-name
  _CONFIG: dict[str, ConfigValueType] = {}
  
  
keep keep keep add keep keep keep keep
 Learning Rate finder (#1341)

* Add LR Finder support structure

* Move trainer.Feeder to lib.training.generator

* Expose model.io

* Add lr_finder

* Update docs and locales

* Pre-PR fixups
  - Fix training graph not displaying
  - CI fixes
  - Switch lr finder progress to tqdm
  - Exit lr finder early on NaN
  - Display lr finder progress in GUI 
plugins/train/model/_base/model.py