Added Custom Learning Rate

Project_Model/Libs/Transformer/Classes/WarmupLR.py

@@ -0,0 +1,47 @@
+from typing import override
+import torch
+
+
+# custom LR from attention is all you need
+class WarmupLR(torch.optim.lr_scheduler.LRScheduler):
+
+    def __init__(
+        self,
+        optimizer: torch.optim.Optimizer,
+        warmup_steps: int,
+        embedding_size: int,
+        warming_multiplier: float = -1.5,
+        decaying_multiplier: float = -0.5,
+        multiplicative_factor: float = 1.0,
+        last_epoch: int = -1,
+    ) -> None:
+        self.__warmup_steps = warmup_steps
+        self.__embedding_size = embedding_size
+        self.__warming_multiplier = warming_multiplier
+        self.__decaying_multiplier = decaying_multiplier
+        self.__multiplicative_factor = multiplicative_factor
+        super().__init__(optimizer, last_epoch)
+
+    def __scale_at(self, step: int) -> float:
+        step = max(step, 1)
+        return (
+            self.__multiplicative_factor
+            * (self.__embedding_size**self.__decaying_multiplier)
+            * min(
+                step**self.__decaying_multiplier,
+                step * (self.__warmup_steps**self.__warming_multiplier),
+            )
+        )
+
+    @override
+    def get_lr(self) -> list[float]:
+        torch.optim.lr_scheduler._warn_get_lr_called_within_step(self)
+
+        step = max(self.last_epoch, 1)
+        scale = self.__scale_at(step)
+        return [base_lr * scale for base_lr in self.base_lrs]
+
+    def _get_closed_form_lr(self):
+        step = max(self.last_epoch, 1)
+        scale = self.__scale_at(step)
+        return [base_lr * scale for base_lr in self.base_lrs]

Project_Model/Libs/Transformer/Classes/__init__.py

@@ -5,6 +5,7 @@ from .FeedForwardNetwork import FeedForwardNetwork
 from .TorchMultiHeadAttention import TorchMultiHeadAttention
 from .SpannedMasker import SpannedMasker
 from .DeToken import DeToken
+from .WarmupLR import WarmupLR
 
 __all__ = [
     "Decoder",
@@ -12,5 +13,6 @@ __all__ = [
     "FeedForwardNetwork",
     "TorchMultiHeadAttention",
     "SpannedMasker",
-    "DeToken"
+    "DeToken",
+    "WarmupLR"
 ]