fix(build): 回退到comp168(2d5232c)——唯一确认docker build成功的版本

Dockerfile: comp168结构 (2 COPY + 1 RUN, 无ex_engine, 无CUDA编译)
qwen3_6_scripts/: comp168内容 (31文件, 141行patch_ops.sh)
computility-run.yaml: max_model_len=100000 (comp168=100000, 避免replay 400拒绝)

comp168得分: functional=0.923, replay=60194, total=60194
改动: 只有yaml的max_model_len从comp168的100000保持不变

qwen3_6_scripts/model_runner.py

@@ -1720,34 +1720,16 @@ class ModelRunner(GPUModelRunnerBase[ModelInputForGPUWithSamplingMetadata]):
             model_forward_end = torch.cuda.Event(enable_timing=True)
             model_forward_start.record()
 
-        # CCCL checked_allocator pattern (c2h/checked_allocator.cuh):
-        # Wrap forward pass in OOM recovery. On CUDA OOM, clear cache and
-        # retry once. If retry also OOMs, re-raise — the engine will abort
-        # this request but NOT die, keeping the server alive for subsequent
-        # requests. This is the key difference vs competitor Sub168 which
-        # died permanently on OOM during replay.
-        def _run_forward():
-            with set_forward_context(model_input.attn_metadata):
-                return model_executable(
-                    input_ids=model_input.input_tokens,
-                    positions=model_input.input_positions,
-                    kv_caches=kv_caches,
-                    attn_metadata=model_input.attn_metadata,
-                    intermediate_tensors=intermediate_tensors,
-                    **MultiModalInputs.as_kwargs(multi_modal_kwargs,
-                                                 device=self.device),
-                    **seqlen_agnostic_kwargs)
-        try:
-            hidden_or_intermediate_states = _run_forward()
-        except torch.cuda.OutOfMemoryError:
-            # CCCL checked_allocator: on OOM, free caches and retry once
-            import gc
-            logger.warning(
-                "CUDA OOM in model forward — clearing cache and retrying "
-                "(CCCL checked_allocator recovery pattern)")
-            torch.cuda.empty_cache()
-            gc.collect()
-            hidden_or_intermediate_states = _run_forward()
+        with set_forward_context(model_input.attn_metadata):
+            hidden_or_intermediate_states = model_executable(
+                input_ids=model_input.input_tokens,
+                positions=model_input.input_positions,
+                kv_caches=kv_caches,
+                attn_metadata=model_input.attn_metadata,
+                intermediate_tensors=intermediate_tensors,
+                **MultiModalInputs.as_kwargs(multi_modal_kwargs,
+                                             device=self.device),
+                **seqlen_agnostic_kwargs)
 
         if (self.observability_config is not None
                 and self.observability_config.collect_model_forward_time):