Add normalization check for backward compatibility

lerobot/common/policies/normalize.py

@@ -418,3 +418,37 @@ class UnnormalizeBuffer(nn.Module):
             raise ValueError(norm_mode)
 
         return batch
+
+
+def convert_normalize_to_buffer_state_dict(state_dict: dict[str, torch.Tensor]) -> dict[str, torch.Tensor]:
+    """
+    Convert state dict from Normalize/Unnormalize classes to NormalizeBuffer/UnnormalizeBuffer format.
+
+    Args:
+        state_dict: State dict from a model using Normalize/Unnormalize classes
+
+    Returns:
+        Converted state dict compatible with NormalizeBuffer/UnnormalizeBuffer classes
+
+    Example:
+        # Old format (Normalize): "buffer_observation_image.mean"
+        # New format (NormalizeBuffer): "observation_image_mean"
+    """
+    converted_state_dict = {}
+
+    for key, value in state_dict.items():
+        # Check if this is a normalization buffer parameter
+        if key.startswith("buffer_") and ("." in key):
+            # Extract the prefix and stat type
+            # e.g. "buffer_observation_image.mean" -> "observation_image", "mean"
+            buffer_part = key[7:]  # Remove "buffer_" prefix
+            prefix, stat_type = buffer_part.rsplit(".", 1)
+
+            # Convert to new format: "observation_image_mean"
+            new_key = f"{prefix}_{stat_type}"
+            converted_state_dict[new_key] = value
+        else:
+            # Keep non-normalization keys unchanged
+            converted_state_dict[key] = value
+
+    return converted_state_dict