e0fe46a46f
CCCL segmented_sort.cu AST chain → traced back to base engine zip → discovered base patch_ops.sh deploys 10+ files we were missing. Missing patches that caused real failures: 1. paged_attn.py — Triton context_attention_fwd HANGS BI-V100 GPUs permanently. Base engine replaces it with _forward_prefix_pytorch pure-PyTorch fallback. WITHOUT THIS: GPU hang on any prefix-cached request → timeout → 0 score. 2. patch_xformers_sdpa_seq.py — head_dim=256 > cudnnFlashAttn 128 limit. Qwen3.5 uses head_dim=256. Without this bypass, attention crashes. 3. sequence.py — completion_tokens inflation under chunked prefill. Bug: get_output_token_ids_to_return(delta=True) with num_new_tokens=0 returns the ENTIRE prompt. 10K prompt × 3 chunks = 30K false tokens. 4. scheduler.py — num_cached_tokens tracking for prefix caching. 5. mamba_cache.py — GatedDeltaNet state management. 6. patch_model_runner.py — prefix_cache_hit stays True in chunked-prefill chunk 2+, causing undersized block_tables and crash. Also: conditional qwen3_5.py deployment (CCCL JIT pattern) — if Docker image already has a working qwen3_5.py (with corex integration), don't overwrite it. Only deploy ours if the image version is missing.