[DEPLOY] Complete submission: baseline + all optimizations

Adds ALL files needed for Dockerfile build:
  - qwen3_6_scripts/ (baseline patches + our optimizations)
  - vllm/ (full vllm package)
  - paged_attention_v2_pytorch.py (V2 with single-bmm optimization)
  - Dockerfile + computility-run.yaml

Our optimizations vs baseline:
  1. paged_attn.py: pre-gathered context KV (eliminates 194 gather calls),
     Triton try/fallback, V2 heuristic, threshold 32K→64K
  2. paged_attention_v2_pytorch.py: fills NotImplementedError,
     single-bmm Phase 1 (195 launches → 3)
  3. patch_enable_triton.py: HAS_TRITON=True with safety fallback
  4. patch_triton_tuning.py: BLOCK=64, NUM_WARPS=4 for BI-V100
  5. computility-run.yaml: gpu-memory-utilization 0.9→0.95,
     max-num-batched-tokens 8192→16384

This repo can now be submitted to dev.modelhub.org.cn as-is.

vllm/transformers_utils/__init__.py

@@ -0,0 +1,17 @@
+from vllm.envs import VLLM_USE_MODELSCOPE
+
+if VLLM_USE_MODELSCOPE:
+    # Patch here, before each import happens
+    import modelscope
+    from packaging import version
+
+    # patch_hub begins from modelscope>=1.18.1
+    if version.parse(modelscope.__version__) <= version.parse('1.18.0'):
+        raise ImportError(
+            'Using vLLM with ModelScope needs modelscope>=1.18.1, please '
+            'install by `pip install modelscope>=1.18.1`')
+
+    from modelscope.utils.hf_util import patch_hub
+
+    # Patch hub to download models from modelscope to speed up.
+    patch_hub()