perf: 消除非流式推理 CPU 空转并减少 decode GPU 张量冗余分配

- engine.py: _Result 改用 threading.Condition.wait_for 替代
  Event busy-wait，非流式模式线程被内核挂起而非 1760 万次空转
- scheduler.py: _execute_decode 将 temperature/top_k/top_p 张量
  移至循环外预先分配，避免每步重复 torch.tensor()；input_ids
  改用 torch.empty 避免不必要的 zero 初始化（两处均为完全覆盖）
- _execute_prefill: input_ids 同改为 torch.empty

astrai/inference/engine.py

@@ -97,7 +97,8 @@ class _Result:
     """Thread-safe token accumulator for streaming and non-streaming modes.
 
     Supports multiple concurrent generation tasks with per-index result tracking.
-    Uses a threading.Event for efficient waiting on completion.
+    Uses a threading.Condition for efficient completion notification
+    and a threading.Event for streaming wakeup.
     """
 
     def __init__(self, count: int = 1):
@@ -106,7 +107,7 @@ class _Result:
         Args:
             count: Number of concurrent generation tasks to track.
         """
-        self._lock = threading.Lock()
+        self._cond = threading.Condition()
         self._event = threading.Event()
         self.tokens: List[str] = []
         self.results: List[str] = [""] * count
@@ -124,7 +125,7 @@ class _Result:
             token: The decoded token string, or STOP sentinel.
             idx: Index of the generation task this token belongs to.
         """
-        with self._lock:
+        with self._cond:
             self.tokens.append(token)
             if token is not STOP:
                 self.results[idx] += token
@@ -132,7 +133,8 @@ class _Result:
                 if not self._done[idx]:
                     self._done[idx] = True
                     self._completed += 1
-        self._event.set()
+                    self._cond.notify_all()
+            self._event.set()
 
     def pop_all(self) -> List[str]:
         """Returns and clears all accumulated tokens.
@@ -140,7 +142,7 @@ class _Result:
         Returns:
             List of token strings since the last call.
         """
-        with self._lock:
+        with self._cond:
             out = self.tokens.copy()
             self.tokens.clear()
             if not out:
@@ -158,13 +160,22 @@ class _Result:
         """
         return self._event.wait(timeout=timeout)
 
+    def wait_completion(self) -> None:
+        """Blocks until all tasks complete (non-streaming).
+
+        Uses a Condition to sleep efficiently instead of busy-waiting.
+        The calling thread is parked until a STOP signal arrives.
+        """
+        with self._cond:
+            self._cond.wait_for(lambda: self._completed >= self._total)
+
     def get_results(self) -> List[str]:
         """Returns all accumulated results for non-streaming mode.
 
         Returns:
             List of complete generated strings, one per task index.
         """
-        with self._lock:
+        with self._cond:
             return self.results.copy()
 
 
@@ -425,8 +436,7 @@ class InferenceEngine:
             )
             task_ids.append(task_id)
 
-        while result._completed < result._total:
-            result.wait(timeout=1.0)
+        result.wait_completion()
 
         for task_id in task_ids:
             self.scheduler.remove_task(task_id)