[Feat] support mixed ep (#2969)

* Support mixed ep

* fix comment

* fix comment

* update mixep

* fix conflict

* fix typo

* update

* fix typo

* fix code style

* fix conflict

fastdeploy/worker/gpu_model_runner.py

@@ -794,6 +794,14 @@ class GPUModelRunner(ModelRunnerBase):
         # Update Batch type for cuda graph
         # TODO(gongshaotian): Use seq_lens_encoder to set is_decode_batch
         is_decode_batch = not ((self.share_inputs["seq_lens_this_time"] > 1).sum() > 0)
+
+        # mix ep in single node
+        if self.fd_config.parallel_config.use_ep and self.fd_config.parallel_config.splitwise_role == "mixed":
+            is_decode_batch_list = []
+            paddle.distributed.all_gather_object(is_decode_batch_list, is_decode_batch)
+            is_decode_batch = all(is_decode_batch_list)
+            self.fd_config.parallel_config.moe_phase.phase = "decode" if is_decode_batch else "prefill"
+
         self.forward_meta.step_use_cudagraph = self.use_cudagraph and is_decode_batch
 
         # Initialzie attention meta data
@@ -1163,16 +1171,18 @@ class GPUModelRunner(ModelRunnerBase):
             We plan to replace it with 'ModelForwardBatch'.
             intermediate_tensors:
         """
-        # NOTE(wufeisheng): For Expert Parallelism
-        if not self.not_need_stop():
-            self._execute_empty_input()
-            return None
-
         # 1. Prepare inputs of model and sampler.
         skip_idx_list = self._get_skip_idx(model_forward_batch)
         self._prepare_inputs()
         self.sampler.pre_process(skip_idx_list)
 
+        # 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():
+            self._execute_empty_input()
+            return None
+
         # 2. Padding inputs for cuda graph
         self.padding_cudagraph_inputs()