fix(build): 回退qwen3_6_scripts+ex_engine到26e6cb40(能得分版本)

唯一改动: computility-run.yaml max_model_len 80000→100000

26e6cb40是Sub520能在竞赛平台docker build成功并得分的版本
之后所有commit都导致docker build失败
根因: 新增的65个文件(vendor_overrides/prebuilt/*.so/wheels等)
可能触发了竞赛平台docker build的某个限制

本次回退:
- qwen3_6_scripts/: 110→45文件(删掉65个新增文件)
- ex_engine/: 恢复到26e6cb40完全一致
- Dockerfile: 恢复5个RUN步骤结构(已验证能build)
- computility-run.yaml: max_model_len=100000(避免replay 400拒绝)

qwen3_6_scripts/patch_worker_profile_override.py

@@ -1,81 +0,0 @@
-from patch_utils import package_root, replace_one_of
-
-WORKER = package_root("vllm") / "worker" / "worker.py"
-
-CLEAN_BLOCK = """\
-        # Profile the memory usage of the model and get the maximum number of
-        # cache blocks that can be allocated with the remaining free memory.
-        torch.cuda.empty_cache()
-
-        # Execute a forward pass with dummy inputs to profile the memory usage
-        # of the model.
-        self.model_runner.profile_run()
-"""
-
-GUARDED_BLOCK = """\
-        # Profile the memory usage of the model and get the maximum number of
-        # cache blocks that can be allocated with the remaining free memory.
-        torch.cuda.empty_cache()
-
-        # Execute a forward pass with dummy inputs to profile the memory usage
-        # of the model. Mark this synthetic pass so BI100_PROFILE can skip
-        # timing it by default; profiling real requests is the useful signal.
-        _bi100_prev_startup_profile = os.environ.get("BI100_IN_STARTUP_PROFILE")
-        os.environ["BI100_IN_STARTUP_PROFILE"] = "1"
-        try:
-            self.model_runner.profile_run()
-        finally:
-            if _bi100_prev_startup_profile is None:
-                os.environ.pop("BI100_IN_STARTUP_PROFILE", None)
-            else:
-                os.environ["BI100_IN_STARTUP_PROFILE"] = _bi100_prev_startup_profile
-"""
-
-NEW_BLOCK = """\
-        # Profile the memory usage of the model and get the maximum number of
-        # cache blocks that can be allocated with the remaining free memory.
-        torch.cuda.empty_cache()
-
-        # BI100: Qwen3.6 batched dummy profile_run can trip GDN non-finite
-        # checks before the server starts. If the operator explicitly provides
-        # --num-gpu-blocks-override, trust that conservative capacity value and
-        # skip only the synthetic profile pass. Real inference still uses the
-        # normal GDN fail-fast path.
-        if self.cache_config.num_gpu_blocks_override is not None:
-            cache_block_size = self.get_cache_block_size_bytes()
-            if cache_block_size == 0:
-                num_cpu_blocks = 0
-            else:
-                num_cpu_blocks = int(self.cache_config.swap_space_bytes //
-                                     cache_block_size)
-            logger.warning(
-                "[BI100] skipping worker.profile_run because "
-                "num_gpu_blocks_override=%d was explicitly set",
-                self.cache_config.num_gpu_blocks_override)
-            gc.collect()
-            torch.cuda.empty_cache()
-            return self.cache_config.num_gpu_blocks_override, max(num_cpu_blocks, 0)
-
-        # Execute a forward pass with dummy inputs to profile the memory usage
-        # of the model. Mark this synthetic pass so BI100_PROFILE can skip
-        # timing it by default; profiling real requests is the useful signal.
-        _bi100_prev_startup_profile = os.environ.get("BI100_IN_STARTUP_PROFILE")
-        os.environ["BI100_IN_STARTUP_PROFILE"] = "1"
-        try:
-            self.model_runner.profile_run()
-        finally:
-            if _bi100_prev_startup_profile is None:
-                os.environ.pop("BI100_IN_STARTUP_PROFILE", None)
-            else:
-                os.environ["BI100_IN_STARTUP_PROFILE"] = _bi100_prev_startup_profile
-"""
-
-replace_one_of(
-    WORKER,
-    [
-        (GUARDED_BLOCK, NEW_BLOCK),
-        (CLEAN_BLOCK, NEW_BLOCK),
-    ],
-    required=True,
-    already_contains="[BI100] skipping worker.profile_run",
-)