support ep+tp at op layer (#4688)

fastdeploy/worker/xpu_model_runner.py

@@ -1156,6 +1156,13 @@ class XPUModelRunner(ModelRunnerBase):
         # 1. Prepare inputs of model and decoder.
         self._prepare_inputs(is_dummy_run=is_dummy_run)
 
+        # NOTE(wufeisheng): If `not_need_stop`` is False, it means the current worker is in an idle state.
+        # This logic is not used in TP (Tensor Parallelism) mode. However, in EP (Expert Parallelism) mode,
+        # when there is data on other runner, the current runner is required to execute part of the model.
+        if not self.not_need_stop() and not is_dummy_run:
+            self._execute_empty_input()
+            return None
+
         # 2. Padding inputs for cuda grph
 
         # 3. Execute model
@@ -1225,6 +1232,17 @@ class XPUModelRunner(ModelRunnerBase):
 
         return None
 
+    def _execute_empty_input(self) -> None:
+        """
+        In certain scenarios, such as during EP,
+        the runner needs to execute partial modules of the model without input data.
+        This requires the model to implement the `empty_input_forward` method.
+        """
+        if hasattr(self.model, "empty_input_forward"):
+            self.model.empty_input_forward()
+        else:
+            raise ValueError(f"{type(self.model)} has no attribute 'empty_input_forward")
+
     @profile_run_guard(True)
     def profile_run(self) -> None:
         """Execute a forward pass with dummy inputs to profile the memory usage of the model"""