[NewFeture]add ep rollout model init and update/clear ep buffer (#4039)

* fix gid

* merge

* fix test

* fix bug

* fix

* fix ci

fastdeploy/config.py

@@ -338,20 +338,26 @@ class ParallelConfig:
         else:
             self.pd_disaggregation_mode = "None"
 
-    def set_tp_group(self):
+    def set_communicate_group(self):
         # different tp group id
         # prevent different tp_groups using the same group_id
         tp_gid_offset = envs.FD_TP_GROUP_GID_OFFSET
         dist.collective._set_custom_gid(self.data_parallel_rank + tp_gid_offset)
+
         self.tp_group = dist.new_group(
             range(
                 self.data_parallel_rank * self.tensor_parallel_size,
                 (self.data_parallel_rank + 1) * self.tensor_parallel_size,
             )
         )
+        dist.collective._set_custom_gid(None)
+
         # same ep group id
-        dist.collective._set_custom_gid(self.data_parallel_size + tp_gid_offset)
-        self.ep_group = dist.new_group(range(self.expert_parallel_size))
+        if self.enable_expert_parallel:
+            dist.collective._set_custom_gid(self.data_parallel_size + tp_gid_offset)
+            self.ep_group = dist.new_group(range(self.expert_parallel_size))
+            dist.collective._set_custom_gid(None)
+
         logger.info(
             f"data_parallel_size: {self.data_parallel_size}, tensor_parallel_size: {self.tensor_parallel_size}, expert_parallel_size: {self.expert_parallel_size}, data_parallel_rank: {self.data_parallel_rank}, tensor_parallel_rank: {self.tensor_parallel_rank}, expert_parallel_rank: {self.expert_parallel_rank}, tp_group: {self.tp_group}."
         )
@@ -833,6 +839,7 @@ class LoadConfig:
         load_strategy: Specifies the weight loading method when enabled:
             - 'ipc': Real-time IPC streaming with automatic resharding
             - 'ipc_snapshot': Load from disk snapshot of IPC weights
+            - 'meta': Only model meta messages
             - None: No dynamic loading
     """
 
@@ -843,7 +850,7 @@ class LoadConfig:
         self.load_choices: Union[str, LoadChoices] = LoadChoices.DEFAULT.value
         self.use_fastsafetensor = int(envs.FD_USE_FASTSAFETENSOR) == 1
         self.dynamic_load_weight: bool = False
-        self.load_strategy: Optional[Literal["ipc", "ipc_snapshot"]] = None
+        self.load_strategy: Optional[Literal["ipc", "ipc_snapshot", "meta", "normal"]] = "normal"
         for key, value in args.items():
             if hasattr(self, key):
                 setattr(self, key, value)
@@ -1201,12 +1208,10 @@ class FDConfig:
 
         num_ranks = self.parallel_config.tensor_parallel_size * self.parallel_config.data_parallel_size
         self.max_chips_per_node = 16 if current_platform.is_iluvatar() else 8
-        if num_ranks > self.max_chips_per_node:
+        if num_ranks > self.max_chips_per_node and self.load_config.load_strategy != "meta":
             self.worker_num_per_node = self.max_chips_per_node
             nnode = ceil_div(num_ranks, self.worker_num_per_node)
             assert nnode == self.nnode, f"nnode: {nnode}, but got {self.nnode}"
-
-            # assert nnode == self.nnode, f"nnode: {nnode}, but got {self.nnode}"
         else:
             self.worker_num_per_node = num_ranks