[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/model_executor/models/__init__.py

@@ -0,0 +1,23 @@
+from .interfaces import (HasInnerState, SupportsLoRA, SupportsMultiModal,
+                         SupportsPP, has_inner_state, supports_lora,
+                         supports_multimodal, supports_pp)
+from .interfaces_base import (VllmModelForEmbedding,
+                              VllmModelForTextGeneration, is_embedding_model,
+                              is_text_generation_model)
+from .registry import ModelRegistry
+
+__all__ = [
+    "ModelRegistry",
+    "VllmModelForEmbedding",
+    "is_embedding_model",
+    "VllmModelForTextGeneration",
+    "is_text_generation_model",
+    "HasInnerState",
+    "has_inner_state",
+    "SupportsLoRA",
+    "supports_lora",
+    "SupportsMultiModal",
+    "supports_multimodal",
+    "SupportsPP",
+    "supports_pp",
+]