diff --git a/pprobe/bootstrap/hook_setup.py b/pprobe/bootstrap/hook_setup.py
index 2029964..ae3ddf5 100644
--- a/pprobe/bootstrap/hook_setup.py
+++ b/pprobe/bootstrap/hook_setup.py
@@ -241,12 +241,6 @@ def run_torch_catch_step_hook(self):
 
     def run_torch_catch_lr_hook(self):
         Logger.info(f"[PPROBE] torch catch lr hook executed")
-        self.module.optim.lr_scheduler.LRScheduler.step = (
-            lr_scheduler_step_method_wrapper(
-                self.module.optim.lr_scheduler.LRScheduler.step
-            )
-        )
-
         self.module.optim.Optimizer.zero_grad = optimizer_zero_grad_method_wrapper(
             self.module.optim.Optimizer.zero_grad
         )
diff --git a/pprobe/bootstrap/hooks/pytorch_optim.py b/pprobe/bootstrap/hooks/pytorch_optim.py
index 0beb3a2..65b4ee5 100644
--- a/pprobe/bootstrap/hooks/pytorch_optim.py
+++ b/pprobe/bootstrap/hooks/pytorch_optim.py
@@ -2,22 +2,15 @@
 from typing import Any, Callable, Optional
 
 
-def lr_scheduler_step_method_wrapper(
-    original_method: Callable, epoch: Optional[int] = None
-):
-    def wrapper(self) -> Any:
-        lr = self.get_lr()
-        Logger.info(f"[PPROBE] INIT LR ===> {lr}")
-        return original_method(self, epoch)
-
-    return wrapper
-
-
 def optimizer_zero_grad_method_wrapper(
     original_method, set_to_none: bool = True
 ) -> None:
     def wrapper(self) -> Any:
         for group in self.param_groups:
+            """
+            group:
+                dict_keys(['params', 'lr', 'momentum', 'dampening', 'weight_decay', 'nesterov', 'maximize', 'foreach', 'differentiable', 'fused', 'initial_lr'])
+            """
             lr = group["lr"]
             Logger.info(f"[PPROBE] Iteration optimizer lr ===> {lr}")
         return original_method(self, set_to_none)