BatchGen v1.0.9.post1

Highlights

Patch release for GLM-5 / GLM-5.1 FP8 on top of v1.0.9. Quiets noisy decode/startup logs that were overwhelming long stress runs, and bumps the BatchGen Python package to 1.0.9.post1. See #139.

• Worker async load confirmation (batchgen/batchgen_worker.py) — per-sequence [LOAD_CONFIRM] ... finalized uuid=... downgraded from info to debug.
• GLM-5 MoE bucket fallback (batchgen/models/glm/glm5/model.py) — oversize bucket fallback and GLM-5 hot-path banners downgraded from warning to debug.
• DSA fused indexer JIT helper (batchgen_kernels/attention/dsa/fused_indexer_kv_proj_cuda.py) — build-time prints replaced with debug logging; load_inline(verbose=...) is now opt-in via BATCHGEN_KERNEL_LOAD_TRACE=1.
• 3D MoE dispatch wrapper (batchgen/moe/dispatch_scatter_3d.py) — successful precompiled-kernel load banner downgraded from info to debug.
• Core engine loader (batchgen/models/engine_loader.py) — JIT fallback message routed through debug logging instead of stdout.
• DSA fused indexer score (batchgen_kernels/attention/dsa/fused_indexer_score.py) — softmax_scale constexpr + ReLU clamp; compute_head_gates reverted to BF16 matmul + FP32 promotion to match the PyTorch fallback path.

Wheels

• batchgen-1.0.9.post1 — rebuilt on H20 node 0 from tag v1.0.9.post1.
• batchgen_kernels-0.3.1.post1 — rebuilt on H20 node 0 from tag v1.0.9.post1 (sm_90a only).
• flash_attn_3, flash_mla, deep_gemm — reused unchanged from v1.0.9.

Build environment: CUDA 12.8, PyTorch 2.9.0+cu128, Python 3.11, NVIDIA H20 (SM 9.0).

Install:

RELEASE_URL="https://github.com/EfficientMoE/BatchGen/releases/download/v1.0.9.post1"
pip install \
  "${RELEASE_URL}/flash_attn_3-3.0.0b1-cp39-abi3-linux_x86_64.whl" \
  "${RELEASE_URL}/flash_mla-1.0.0+1408756-cp311-cp311-linux_x86_64.whl" \
  "${RELEASE_URL}/deep_gemm-2.1.1+c9f8b34-cp311-cp311-linux_x86_64.whl" \
  "${RELEASE_URL}/batchgen_kernels-0.3.1.post1-cp311-cp311-linux_x86_64.whl" \
  "${RELEASE_URL}/batchgen-1.0.9.post1-py3-none-any.whl"