fix: 修复 CLI 参数缺失/重复、device_ids 越界、generate 参数名不一致、scheduler 时序、非流式截断等 bug

- train.py: 补上 --batch_size、--grpo_clip_eps，删除 3 处重复 --group_size
- generate.py: --model_dir 改为 --param_path 对齐 README
- automodel.py: from_pretrained 新增 strict 参数（默认 True）
- parallel/setup.py: 修复 device_ids 索引越界
- train_callback.py: scheduler.step() 移至 on_step_end
- test_train_strategy.py: 测试中补 optimizer.step()
- engine.py: 非流式改为循环等待所有任务完成，补 remove_task 清理
- scheduler.py: Task 添加 _pages_freed 标志，杜绝双重释放
- trainer.py: accumulation_steps=0 时 clamp 为 1
- tokenizer.py: save_pretrained 添加 _tokenizer is None 检查
- benchmark.py: 修复 ModelConfig 过时 import 路径
- inference/__init__.py: 修复 stale docstring

astrai/inference/engine.py

@@ -408,13 +408,14 @@ class InferenceEngine:
             Single string for one prompt, list of strings for batch.
         """
         result = _Result(count=len(prompts))
+        task_ids = []
 
         for i, p in enumerate(prompts):
 
             def make_cb(idx):
                 return lambda tok: result.append(tok, idx)
 
-            self.scheduler.add_task(
+            task_id = self.scheduler.add_task(
                 prompt=p,
                 max_tokens=max_tokens,
                 temperature=temperature,
@@ -422,8 +423,14 @@ class InferenceEngine:
                 top_k=top_k,
                 stream_callback=make_cb(i),
             )
+            task_ids.append(task_id)
+
+        while result._completed < result._total:
+            result.wait(timeout=1.0)
+
+        for task_id in task_ids:
+            self.scheduler.remove_task(task_id)
 
-        result.wait()
         res = result.get_results()
         return res if is_batch else res[0]