[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/multimodal/__init__.py

@@ -0,0 +1,24 @@
+from .base import (BatchedTensorInputs, MultiModalDataBuiltins,
+                   MultiModalDataDict, MultiModalInputs, MultiModalPlugin,
+                   NestedTensors)
+from .registry import MultiModalRegistry
+
+MULTIMODAL_REGISTRY = MultiModalRegistry()
+"""
+The global :class:`~MultiModalRegistry` is used by model runners to
+dispatch data processing according to its modality and the target model.
+
+See also:
+    :ref:`input_processing_pipeline`
+"""
+
+__all__ = [
+    "BatchedTensorInputs",
+    "MultiModalDataBuiltins",
+    "MultiModalDataDict",
+    "MultiModalInputs",
+    "MultiModalPlugin",
+    "NestedTensors",
+    "MULTIMODAL_REGISTRY",
+    "MultiModalRegistry",
+]