Support RL online quantization with torchao (#23014)

Signed-off-by: Jerry Zhang <jerryzh168@gmail.com>

vllm/model_executor/model_loader/utils.py

@@ -95,6 +95,13 @@ def initialize_model(
 
 def process_weights_after_loading(model: nn.Module, model_config: ModelConfig,
                                   target_device: torch.device) -> None:
+
+    # to avoid circular dependency
+    from vllm.model_executor.model_loader.online_quantization import (
+        maybe_save_metadata_and_attributes_for_weight_reloading)
+    maybe_save_metadata_and_attributes_for_weight_reloading(
+        model, model_config)
+
     for _, module in model.named_modules():
         if isinstance(module, QKVCrossParallelLinear):
             # NOTE(Isotr0py): special case for cross QKV layer because
@@ -243,7 +250,7 @@ def get_architecture_class_name(model_config: ModelConfig) -> str:
 class ParamMapping:
     """
     A class to handle parameter mapping for model weight loading.
-    It creates a bidirectional mapping between packed parameters and their 
+    It creates a bidirectional mapping between packed parameters and their
     constituent parts.
     """
     packed_mapping: dict[str, list[str]]