Revert base Runner

AlexEMG · Sep 10, 2025 · Jun 25, 2025 · Jun 26, 2025 · Jun 26, 2025 · Jun 26, 2025
commit bba86890a4ed252e48801702f2ab062492ae6668
diff --git a/deeplabcut/pose_estimation_pytorch/runners/base.py b/deeplabcut/pose_estimation_pytorch/runners/base.py
@@ -114,43 +114,7 @@ def load_snapshot(
             The content of the snapshot file.
         """
         snapshot = attempt_snapshot_load(snapshot_path, device, weights_only)
-
-        # Handle the case where snapshot keys have 'model.' prefix
-        snapshot_weights = snapshot["model"]
-        model_state_dict = model.state_dict()
-
-        # Diagnostic: Always add 'model.' prefix for superanimal_topviewmouse detectors
-        is_topviewmouse = hasattr(model, 'superanimal_name') and getattr(model, 'superanimal_name', None) == 'superanimal_topviewmouse'
-        is_detector = 'FasterRCNN' in str(type(model)) or 'SSDLite' in str(type(model))
-        if is_topviewmouse and is_detector:
-            print(f"DEBUG: Forcing prefix ADD for superanimal_topviewmouse detector!")
-            cleaned_weights = {}
-            for key, value in snapshot_weights.items():
-                if not key.startswith('model.'):
-                    cleaned_key = 'model.' + key  # Add 'model.' prefix
-                    cleaned_weights[cleaned_key] = value
-                else:
-                    cleaned_weights[key] = value
-            print(f"DEBUG: Loading cleaned weights with {len(cleaned_weights)} keys")
-            model.load_state_dict(cleaned_weights)
-        elif (any(key.startswith('model.') for key in snapshot_weights.keys()) and 
-            not any(key.startswith('model.') for key in model_state_dict.keys())):
-            print(f"DEBUG: Detected 'model.' prefix mismatch, cleaning keys...")
-            # Strip the 'model.' prefix from snapshot keys
-            cleaned_weights = {}
-            for key, value in snapshot_weights.items():
-                if key.startswith('model.'):
-                    cleaned_key = key[6:]  # Remove 'model.' prefix
-                    cleaned_weights[cleaned_key] = value
-                else:
-                    cleaned_weights[key] = value
-            print(f"DEBUG: Loading cleaned weights with {len(cleaned_weights)} keys")
-            model.load_state_dict(cleaned_weights)
-        else:
-            print(f"DEBUG: No prefix mismatch, loading original weights")
-            # Use original snapshot weights
-            model.load_state_dict(snapshot["model"])
-
+        model.load_state_dict(snapshot["model"])
         return snapshot