abd3d5640a
CCCL tuning_rle_encode.cuh AST chain led to reading the base engine zip: enginex-vllm-bi100-qwen36-main.zip → qwen3_6_scripts/qwen3_5.py (63KB, 1369 lines) vs our custom version (85KB, 1780 lines) which added: - _hw_policy with hardcoded clamp values - nan_to_num(nan=0.0) double disaster - Custom _torch_chunk_gated_delta_rule with aggressive clamps - Custom FusedMoE fallback logic - All of which BROKE the native CoreX acceleration Sub168 docker log proves: - corex_gdn.py:56 loads libcorex_gdn.so (fused GDN decode) - corex_gdn.py:228 uses fused GDN prefill - corex_moe.py:339 uses CoreX fused MoE (expert-grouped-wmma) These are Docker image-internal modules that our custom code never called. Base original: - No nan_to_num (NaN propagates honestly) - No custom clamps (uses model weights as-is) - Same class structure (Qwen3_5ForCausalLM, Qwen3_5MoeForCausalLM) - Docker image's corex modules can intercept through vllm's internal dispatch qwen3_5_base_original.py kept as reference.