[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/configs/mllama.py

@@ -0,0 +1,28 @@
+from transformers.models.mllama import configuration_mllama as mllama_hf_config
+
+
+class MllamaTextConfig(mllama_hf_config.MllamaTextConfig):
+    '''
+    Use this class to override is_encoder_decoder:
+    - transformers regards mllama as is_encoder_decoder=False
+    - vllm needs is_encoder_decoder=True to enable cross-attention
+    '''
+
+    def __init__(
+        self,
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self.is_encoder_decoder = True
+
+
+class MllamaConfig(mllama_hf_config.MllamaConfig):
+
+    def __init__(
+        self,
+        text_config=None,
+        **kwargs,
+    ):
+        if isinstance(text_config, dict):
+            text_config = MllamaTextConfig(**text_config)
+        super().__init__(text_config=text_config, **kwargs)