[None][fix] fix log_once usage

tensorrt_llm/_torch/autotuner.py

@@ -354,7 +354,7 @@ def choose_one(self, custom_op: str, runners: List[TunableRunner],
                 # Only log once for each custom op and only when cache is not empty
                 logger.warning_once(
                     f"[AutoTunner] Using the fallback tactic, due to cache miss on input shapes={input_shapes}",
-                    key=(custom_op))
+                    key=custom_op)
             return runner, tactic
 
         assert len(runners) > 0, "At least one runner is required"

tensorrt_llm/_torch/models/modeling_llava_next.py

@@ -171,7 +171,8 @@ def pack_image_features(self,
                     logger.warning_once(
                         "Image feature shape does not line up with the provided patch size. "
                         "You may be using the `default` vision_feature_select_strategy with a"
-                        " visual encoder that does not have CLS.")
+                        " visual encoder that does not have CLS.",
+                        key="llava_next_vision_model_pack_image_features")
 
                 image_feature = image_feature.view(num_patch_height,
                                                    num_patch_width, height,

tensorrt_llm/logger.py

@@ -109,6 +109,7 @@ def log(self, severity, *msg):
         self._func_wrapper(severity)(" ".join(parts))
 
     def log_once(self, severity, *msg, key):
+        assert key is not None, "key is required for log_once"
         if key not in self._appeared_keys:
             self._appeared_keys.add(key)
             self.log(severity, *msg)