1 files changed, 97 insertions, 0 deletions
diff --git a/src/training/callbacks/lr_schedulers.py b/src/training/callbacks/lr_schedulers.py
new file mode 100644
index 0000000..00c7e9b
--- /dev/null
+++ b/src/training/callbacks/lr_schedulers.py
@@ -0,0 +1,97 @@
+"""Callbacks for learning rate schedulers."""
+from typing import Callable, Dict, List, Optional, Type
+
+from training.callbacks import Callback
+
+from text_recognizer.models import Model
+
+
+class StepLR(Callback):
+    """Callback for StepLR."""
+
+    def __init__(self) -> None:
+        """Initializes the callback."""
+        super().__init__()
+        self.lr_scheduler = None
+
+    def set_model(self, model: Type[Model]) -> None:
+        """Sets the model and lr scheduler."""
+        self.model = model
+        self.lr_scheduler = self.model.lr_scheduler
+
+    def on_epoch_end(self, epoch: int, logs: Dict = {}) -> None:
+        """Takes a step at the end of every epoch."""
+        self.lr_scheduler.step()
+
+
+class MultiStepLR(Callback):
+    """Callback for MultiStepLR."""
+
+    def __init__(self) -> None:
+        """Initializes the callback."""
+        super().__init__()
+        self.lr_scheduler = None
+
+    def set_model(self, model: Type[Model]) -> None:
+        """Sets the model and lr scheduler."""
+        self.model = model
+        self.lr_scheduler = self.model.lr_scheduler
+
+    def on_epoch_end(self, epoch: int, logs: Dict = {}) -> None:
+        """Takes a step at the end of every epoch."""
+        self.lr_scheduler.step()
+
+
+class ReduceLROnPlateau(Callback):
+    """Callback for ReduceLROnPlateau."""
+
+    def __init__(self) -> None:
+        """Initializes the callback."""
+        super().__init__()
+        self.lr_scheduler = None
+
+    def set_model(self, model: Type[Model]) -> None:
+        """Sets the model and lr scheduler."""
+        self.model = model
+        self.lr_scheduler = self.model.lr_scheduler
+
+    def on_epoch_end(self, epoch: int, logs: Dict = {}) -> None:
+        """Takes a step at the end of every epoch."""
+        val_loss = logs["val_loss"]
+        self.lr_scheduler.step(val_loss)
+
+
+class CyclicLR(Callback):
+    """Callback for CyclicLR."""
+
+    def __init__(self) -> None:
+        """Initializes the callback."""
+        super().__init__()
+        self.lr_scheduler = None
+
+    def set_model(self, model: Type[Model]) -> None:
+        """Sets the model and lr scheduler."""
+        self.model = model
+        self.lr_scheduler = self.model.lr_scheduler
+
+    def on_train_batch_end(self, batch: int, logs: Dict = {}) -> None:
+        """Takes a step at the end of every training batch."""
+        self.lr_scheduler.step()
+
+
+class OneCycleLR(Callback):
+    """Callback for OneCycleLR."""
+
+    def __init__(self) -> None:
+        """Initializes the callback."""
+        super().__init__()
+        self.lr_scheduler = None
+
+    def set_model(self, model: Type[Model]) -> None:
+        """Sets the model and lr scheduler."""
+        self.model = model
+        self.lr_scheduler = self.model.lr_scheduler
+
+    def on_train_batch_end(self, batch: int, logs: Dict = {}) -> None:
+        """Takes a step at the end of every training batch."""
+        self.lr_scheduler.step()