[Fix]Fix vl when import fastdeploy and fix rl config rank bug (#2953)

* support vl ori_vacab_size

* support trainer_degree in name_mapping

* fix

* fix import error

* fix local rank

fastdeploy/import_ops.py

@@ -43,8 +43,7 @@ def import_custom_ops(package, module_name, global_ns):
                 logger.warning(f"Failed to import op {func_name}: {e}")
 
     except Exception:
-        logger.warning(
-            f"Ops of {package} import failed, it may be not compiled.")
+        logger.warning(f"Ops of {package} import failed, it may be not compiled.")
 
     preprocess_static_op(global_ns)
 
@@ -71,6 +70,7 @@ def wrap_unified_op(original_cpp_ext_op, original_custom_op):
         original_cpp_ext_op: Original C++ extension operator function.
         original_custom_op: Original custom operator function.
     """
+    try:
 
         @paddle.jit.marker.unified
         @functools.wraps(original_custom_op)
@@ -85,6 +85,9 @@ def wrap_unified_op(original_cpp_ext_op, original_custom_op):
                 return res
             return original_custom_op(*args, **kwargs)
 
+    except:
+        unified_op = None
+        logger.warning("Paddle version not support JIT mode.")
     return unified_op
 
 

fastdeploy/rl/rollout_config.py

@@ -58,6 +58,7 @@ class RolloutModelConfig:
         disable_any_whitespace: bool = True,
         enable_logprob: bool = False,
         graph_optimization_config: str = None,
+        local_rank: int = 0
     ):
         # Required parameters
         self.model_name_or_path = model_name_or_path
@@ -98,10 +99,11 @@ class RolloutModelConfig:
         self.disable_any_whitespace = disable_any_whitespace
         self.enable_logprob = enable_logprob
         self.graph_optimization_config = graph_optimization_config
+        self.local_rank = local_rank
 
     def __str__(self):
         return "\n".join(f"{k}: {v}" for k, v in self.__dict__.items())
 
     def initialize(self):
         """Initialize the final fd config"""
-        return initialize_fd_config(self, ranks=self.tensor_parallel_size, local_rank=0)
+        return initialize_fd_config(self, ranks=self.tensor_parallel_size, local_rank=self.local_rank)