[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/patch_model_runner.py

@@ -0,0 +1,78 @@
+"""
+Fix: prefix_cache_hit stays True for chunked-prefill chunk 2+ even when past cache.
+
+Root cause:
+  model_runner.py _compute_for_prefix_cache_hit has three cases:
+    Case 1: prefix_cache_len <= context_len  → "already past cache, do normal"
+    Case 2: context_len < prefix_cache_len < seq_len  → partial hit, correct
+    Case 3: seq_len <= prefix_cache_len  → full hit, reduce to 1 token
+
+  Case 1 does nothing (leaves prefix_cache_hit = True). Then in utils.py:
+    if inter_data.prefix_cache_hit:
+        block_table = computed_block_nums   ← ONLY the original prefix blocks!
+
+  But context_len > prefix_cache_len means chunk 1 tokens (between prefix_cache_len
+  and context_len) are ALSO in KV cache and need to be in block_table.
+  block_table = computed_block_nums misses all chunk-1 blocks.
+
+  In _forward_prefix_pytorch:
+    num_ctx_blocks = ceil(context_len / block_size)  # e.g. 268
+    block_tables.shape[1] = len(computed_block_nums)  # e.g. 12  <-- too small!
+    At tile_blk >= 12: blk_ids is empty → k_t shape [..., 0] → amax crash.
+
+Fix:
+  Set prefix_cache_hit = False for Case 1, so utils.py falls through to:
+    elif chunked_prefill_enabled:
+        block_table = block_tables[seq_id]   ← full block table (prefix + chunk1)
+"""
+
+import re
+import sys
+
+CANDIDATE_PATHS = [
+    "/usr/local/corex/lib64/python3/dist-packages/vllm/worker/model_runner.py",
+    "/usr/local/corex/lib/python3/dist-packages/vllm/worker/model_runner.py",
+]
+
+OLD_BLOCK = """\
+        if prefix_cache_len <= context_len:
+            # We already passed the cache hit region,
+            # so do normal computation.
+            pass"""
+
+NEW_BLOCK = """\
+        if prefix_cache_len <= context_len:
+            # We already passed the cache hit region,
+            # so do normal computation.
+            # Must clear prefix_cache_hit so _add_seq_group uses the full
+            # block_tables (prefix + previous-chunk blocks) instead of only
+            # computed_block_nums (prefix only).  Without this, block_tables
+            # passed to _forward_prefix_pytorch is too narrow for context_len,
+            # causing an empty blk_ids slice and a zero-dim amax() crash.
+            inter_data.prefix_cache_hit = False"""
+
+import os
+
+patched = False
+for path in CANDIDATE_PATHS:
+    if not os.path.exists(path):
+        continue
+    with open(path, "r") as f:
+        src = f.read()
+    if OLD_BLOCK not in src:
+        if NEW_BLOCK in src:
+            print(f"[patch_model_runner] already patched: {path}")
+            patched = True
+            break
+        print(f"[patch_model_runner] WARNING: expected block not found in {path}, skipping")
+        continue
+    patched_src = src.replace(OLD_BLOCK, NEW_BLOCK, 1)
+    with open(path, "w") as f:
+        f.write(patched_src)
+    print(f"[patch_model_runner] patched Case-1 prefix_cache_hit fix in: {path}")
+    patched = True
+    break
+
+if not patched:
+    print("[patch_model_runner] ERROR: could not find model_runner.py at any known path", file=sys.stderr)
+    sys.exit(1)