[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.

qwen3_6_scripts/reasoning/__init__.py

@@ -0,0 +1,16 @@
+"""
+Reasoning parser module for vLLM 0.6.3 (BI-V100 / Qwen3.6-27B adaptation).
+
+Usage: --reasoning-parser qwen3
+"""
+
+from vllm.reasoning.abs_reasoning_parsers import ReasoningParser, ReasoningParserManager
+
+__all__ = ["ReasoningParser", "ReasoningParserManager"]
+
+# Lazy-register Qwen3 parser; imported on first get_reasoning_parser("qwen3").
+ReasoningParserManager.register_lazy(
+    "qwen3",
+    "vllm.reasoning.qwen3_reasoning_parser",
+    "Qwen3ReasoningParser",
+)