fix server warmup

ktransformers/server/backend/interfaces/ktransformers.py

@@ -73,13 +73,13 @@ class KTransformersInterface(TransformersInterface):
 
         self._infer_lock = asyncio.Lock()
 
-    def decode_one_tokens(self, i):
+    def decode_one_tokens(self):
         device_map = self.model.gguf_loader.tensor_device_map
         torch_device = get_device("blk.0.self_attn", device_map)
         torch_device = "cuda:0" if torch_device == "cuda" else torch_device
         global warm_uped
-        if self.args.use_cuda_graph and ( (warm_uped == True and int(i) == 1) or (warm_uped == False and int(i) == 2) ):
-            warm_uped = True
+        if self.args.use_cuda_graph and warm_uped == True:
+            
             if not hasattr(self, "cuda_graph_runner"):
                 self.cuda_graph_runner = CUDAGraphRunner()
                 self.cuda_graph_runner.capture(
@@ -93,15 +93,18 @@ class KTransformersInterface(TransformersInterface):
                     use_cache=True,
                 )
 
-        if hasattr(self, "cuda_graph_runner"):
-            logits = self.cuda_graph_runner(
-                self.current_ids, self.active_cache_position.unsqueeze(0), self.active_cache_position
-            )
-            self.cache.change_seq_length(1)
-            torch.cuda.synchronize()
-            logits = logits[0, -1, :]
-            return self.logits_to_token(logits)
-
+            if hasattr(self, "cuda_graph_runner"):
+                logits = self.cuda_graph_runner(
+                    self.current_ids, self.active_cache_position.unsqueeze(0), self.active_cache_position
+                )
+                self.cache.change_seq_length(1)
+                torch.cuda.synchronize()
+                logits = logits[0, -1, :]
+                return self.logits_to_token(logits)
+        
+        if self.args.use_cuda_graph:
+            warm_uped = True
+            
         if self.use_static_cache:
             mask = torch.ones((1, self.seq_length)).to(torch_device)
             logits = self.model(

ktransformers/server/backend/interfaces/transformers.py

@@ -219,7 +219,7 @@ class TransformersInterface(BackendInterfaceBase):
         self.ever_generated_ids.add(last)
         return last
 
-    def decode_one_tokens(self, i):
+    def decode_one_tokens(self):
         if self.use_static_cache:
             mask = torch.ones((1, self.seq_length)).to(self.args.device)
             logits = self.model(
@@ -299,7 +299,7 @@ class TransformersInterface(BackendInterfaceBase):
                                              num_heads=self.model.config.num_attention_heads, head_dim_ckv=self.model.config.kv_lora_rank, 
                                              head_dim_kpe=self.model.config.qk_rope_head_dim, page_size=self.cache.page_size,
                                              sm_scale=(self.model.config.qk_rope_head_dim + self.model.config.qk_nope_head_dim) ** (-0.5), q_data_type=torch.bfloat16, kv_data_type=torch.bfloat16)
-                next_token = self.decode_one_tokens(i)
+                next_token = self.decode_one_tokens()
                 self.profiler.inc("decode")
                 if next_token == self.tokenizer.eos_token_id:
                     assert self.args.batch_size == 1