fix setup logger bugs

benchmarks/run_async_requests.py

@@ -74,5 +74,5 @@ async def main(messages_list: List[List[Dict[str, Any]]]):
 
 
 if __name__ == "__main__":
-    # asyncio.run(main(llm_message()))
-    asyncio.run(main(mllm_message()))
+    asyncio.run(main(llm_message()))
+    # asyncio.run(main(mllm_message()))

examples/run_engine.py

@@ -131,6 +131,6 @@ async def image_generate(args):
 
 if __name__ == "__main__":
     args = parse_args()
-    # asyncio.run(llm_generate(args, llm_message()))
-    asyncio.run(llm_generate(args, mllm_message()))
+    asyncio.run(llm_generate(args, llm_message()))
+    # asyncio.run(llm_generate(args, mllm_message()))
     # asyncio.run(image_generate(args))

tllm/generate/message_processor.py

@@ -1,5 +1,4 @@
-import copy
-from typing import Dict, List, Optional, Tuple
+from typing import Dict, List, Tuple
 
 from PIL import Image
 from PIL.ImageFile import ImageFile

tllm/models/mlx/layers.py

@@ -104,7 +104,6 @@ def sdap(q, k, v, scale, mask):
         out = mx.matmul(scores, v[:, None])
         # 展平结果为[L, H, D]
         out = mx.flatten(out, 0, 1)
-
     else:  # 标准注意力计算
         scores = mx.matmul(q, mx.swapaxes(k, -1, -2))
         scores = scores + mask
@@ -204,7 +203,7 @@ def _rope(self, xs: mx.array, request_cache: RequestsCache, uuid_list: List[str]
         x_list = []
         start = 0
         for uuid, offset in zip(uuid_list, offset_list):
-            end = start + request_cache.get_seq_len(uuid)
+            end = start + request_cache.get_q_len(uuid)
             x_list.append(self.rope(xs[start:end].transpose(1, 0, 2), offset).transpose(1, 0, 2))
             start = end
         return cat_func(x_list)

tllm/models/mlx/llama.py

@@ -1,4 +1,4 @@
-from typing import Any, Dict, Optional
+from typing import Dict
 
 import mlx.core as mx
 import mlx.nn as nn
@@ -101,7 +101,7 @@ def from_pretrained(cls, config: AutoConfig, state_dict: Dict[str, mx.array], **
         state_dict = model.merge_weights(state_dict, is_merge)
 
         model = quantization_func(config, model, state_dict)
-        model.load_weights(list(state_dict.items()), strict=False)
+        model.load_weights(list(state_dict.items()))
 
         mx.eval(model.parameters())
         model.eval()
@@ -137,7 +137,7 @@ def __init__(self, config):
         self.norm = nn.RMSNorm(config.hidden_size, eps=config.rms_norm_eps)
 
     @classmethod
-    def from_pretrained(cls, config, state_dict: Optional[Any], **kwargs):
+    def from_pretrained(cls, config, state_dict, **kwargs):
         model = cls(config)
 
         cls.config = config

tllm/singleton_logger.py

@@ -65,19 +65,19 @@ def _add_file_handler(cls, logger: logging.Logger):
             logger.addHandler(file_handler)
 
     @classmethod
-    def _setup_logger(cls, name=Literal["master", "handler"]) -> logging.Logger:
-        if cls.logger is None:
+    def _setup_logger(cls, name: Literal["master", "handler"]) -> logging.Logger:
+        if cls.logger is None:  # 仅在第一次调用时创建logger
             cls.logger = logging.getLogger(name)
             cls.logger.setLevel(cls._level)
 
-            ch = logging.StreamHandler()
-            ch.setLevel(cls._level)
+            if not cls.logger.hasHandlers():  # 检查是否已经存在 handlers
+                ch = logging.StreamHandler()
+                ch.setLevel(cls._level)
+                formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
+                ch.setFormatter(formatter)
+                cls.logger.addHandler(ch)
 
-            formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
-            ch.setFormatter(formatter)
-
-            cls.logger.addHandler(ch)
-            cls._add_file_handler(cls.logger)
+            cls._add_file_handler(cls.logger)  # 始终添加文件handler
         return cls.logger
 
     @classmethod