[BugFix] num_seqs (#3291)

lizexu123 · web-flow · commit e0aeac58e1ad · 2025-08-11T13:38:55.000+08:00
* fix num_seqs

* merge develop
diff --git a/fastdeploy/model_executor/models/ernie4_5_moe.py b/fastdeploy/model_executor/models/ernie4_5_moe.py
@@ -450,7 +450,7 @@ def empty_input_forward(self):
             self.fd_config.model_config.moe_layer_start_index,
             self.fd_config.model_config.num_hidden_layers,
         ):
-            self.ernie.layers[i].mlp.expert(fake_hidden_states)
+            self.ernie.layers[i].mlp.experts(fake_hidden_states, self.ernie.layers[i].mlp.gate)
 
     def forward(
         self,
diff --git a/fastdeploy/worker/gpu_model_runner.py b/fastdeploy/worker/gpu_model_runner.py
@@ -795,7 +795,7 @@ def _prepare_inputs(self) -> None:
             output_padding_offset,
         ) = pre_process(
             self.share_inputs["input_ids"],
-            self.share_inputs["seq_lens_this_time"],
+            getattr(self.share_inputs, "seq_lens_this_time", self.seq_lens_this_time_buffer),
             self.speculative_decoding,
             (self.share_inputs["draft_tokens"] if self.speculative_decoding else None),
             self.share_inputs["seq_lens_encoder"],
@@ -880,7 +880,7 @@ def initialize_forward_meta(self):
             max_len_tensor_cpu=self.share_inputs["max_len_tensor_cpu"],
             seq_lens_encoder=self.share_inputs["seq_lens_encoder"],
             seq_lens_decoder=self.share_inputs["seq_lens_decoder"],
-            seq_lens_this_time=self.share_inputs["seq_lens_this_time"],
+            seq_lens_this_time=getattr(self.share_inputs, "seq_lens_this_time", self.seq_lens_this_time_buffer),
             batch_id_per_token=self.share_inputs["batch_id_per_token"],
             cu_seqlens_q=self.share_inputs["cu_seqlens_q"],
             cu_seqlens_k=self.share_inputs["cu_seqlens_k"],
diff --git a/fastdeploy/worker/worker_process.py b/fastdeploy/worker/worker_process.py
@@ -244,6 +244,7 @@ def event_loop_ep(self) -> None:
         """
         while True:
             self.worker_healthy_live_signal.value[self.local_rank % self.max_chips_per_node] = int(time.time())
+            num_running_requests = 0
 
             if self.fd_config.parallel_config.tensor_parallel_rank == 0 and self.task_queue.num_tasks() > 0:
                 tasks, read_finish = self.task_queue.get_tasks()
@@ -271,6 +272,8 @@ def event_loop_normal(self) -> None:
         self.nnode = int((self.parallel_config.tensor_parallel_size + 7) // 8)
         mp_num_per_node = self.parallel_config.tensor_parallel_size // self.nnode
         req_ids = []
+        num_running_requests = 0
+
         while True:
             if self.local_rank == 0:
                 if self.model_weights_status.value[0] != 0:
