implemented locking in training setup

backend/data/yolox_m.py

@@ -0,0 +1,15 @@
+#!/usr/bin/env python3
+# -*- coding:utf-8 -*-
+# Base configuration for YOLOX-M model
+# These parameters are preserved during transfer learning from COCO
+
+class BaseExp:
+    """Base experiment configuration for YOLOX-M"""
+    
+    # Model architecture (protected - always use these for yolox-m)
+    depth = 0.67
+    width = 0.75
+    
+    scheduler = "yoloxwarmcos"
+
+    activation = "silu"