biondizzle
918342feeb
The nightly vLLM image puts ALL MHC code in layers/mhc.py (not kernels/mhc/). It imports tilelang at top level and JIT-compiles kernels. Replace the entire file with pure PyTorch implementations using direct_register_custom_op for mhc_pre, mhc_post, mhc_fused_post_pre, and hc_head_fused_kernel. No tilelang dependency at all. Also removes the separate mhc_torch_ops.py and kernels/mhc/ patches which don't apply to the nightly image layout.
74 lines
3.8 KiB
Docker
74 lines
3.8 KiB
Docker
# DeepSeek V4 NVFP4 vLLM + CuTeDSL NVFP4 MoE Kernel
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FROM vllm/vllm-openai:nightly-x86_64
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# Remove broken nixl_ep (built against CUDA 12, image is CUDA 13)
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RUN pip uninstall -y nixl-ep; rm -rf /usr/local/lib/python3.12/dist-packages/nixl_ep
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RUN apt-get update && apt-get install -y git screen cmake libcusolver-dev-13-0 libcusparse-dev-13-0 libcublas-dev-13-0 libcurand-dev-13-0 libcufft-dev-13-0 libnvjitlink-dev-13-0 && rm -rf /var/lib/apt/lists/*
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# Remove the broken symlink if it exists
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RUN rm -f /usr/local/cuda/lib64/libcudrt.so.12
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ENV CUDA_HOME=/usr/local/cuda
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ENV TORCH_CUDA_ARCH_LIST="10.0"
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# Install CuTeDSL (NVFP4 block-scaled GEMM kernel framework)
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RUN pip install nvidia-cutlass-dsl==4.5.0 nvidia-cutlass-dsl-libs-base==4.5.0
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ARG CACHE_BUSTER=${TIMESTAMP}
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# Copy the NVFP4 mega_moe Python kernel (no C++ build needed)
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COPY src/ /root/nvfp4-megamoe-kernel/src/
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COPY pyproject.toml /root/nvfp4-megamoe-kernel/pyproject.toml
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RUN cd /root/nvfp4-megamoe-kernel && pip install -e .
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# Copy the CuTeDSL kernel and bridge layer
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COPY cutedsl/ /root/nvfp4-megamoe-kernel/cutedsl/
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ENV PYTHONPATH="/root/nvfp4-megamoe-kernel:${PYTHONPATH}"
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# Patch vLLM — overwrite model files and register architecture
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ARG VLLM_MODELS_DIR=/usr/local/lib/python3.12/dist-packages/vllm/model_executor/models
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ARG VLLM_LAYERS_DIR=/usr/local/lib/python3.12/dist-packages/vllm/model_executor/layers
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ARG VLLM_QUANT_DIR=/usr/local/lib/python3.12/dist-packages/vllm/model_executor/layers/quantization
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ARG VLLM_FUSED_MOE_DIR=/usr/local/lib/python3.12/dist-packages/vllm/model_executor/layers/fused_moe
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ARG VLLM_LOADER_DIR=/usr/local/lib/python3.12/dist-packages/vllm/model_executor/model_loader
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# Core model patches
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COPY vllm/patches/deepseek_v4.py ${VLLM_MODELS_DIR}/deepseek_v4.py
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COPY vllm/patches/deepseek_v4_attention.py ${VLLM_LAYERS_DIR}/deepseek_v4_attention.py
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COPY vllm/patches/layers/deepseek_compressor.py ${VLLM_LAYERS_DIR}/deepseek_compressor.py
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# Replace MHC TileLang kernels with pure PyTorch (avoids TileLang JIT on Blackwell)
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# The nightly image has all MHC in layers/mhc.py (imports tilelang at top level).
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# Our replacement is pure PyTorch — no tilelang dependency at all.
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COPY vllm/patches/layers/mhc.py ${VLLM_LAYERS_DIR}/mhc.py
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# CuTeDSL NVFP4 linear kernel (registered as NvFp4LinearKernel)
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ARG VLLM_NVFP4_DIR=/usr/local/lib/python3.12/dist-packages/vllm/model_executor/kernels/linear/nvfp4
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COPY vllm/kernels/linear/nvfp4/cutedsl.py ${VLLM_NVFP4_DIR}/cutedsl.py
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# Register CuTeDSL kernel in vLLM's linear kernel selection
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ARG VLLM_LINEAR_DIR=/usr/local/lib/python3.12/dist-packages/vllm/model_executor/kernels/linear
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COPY vllm/patches/register_cutedsl_kernel.py /tmp/register_cutedsl_kernel.py
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RUN python3 /tmp/register_cutedsl_kernel.py ${VLLM_LINEAR_DIR}/__init__.py && rm /tmp/register_cutedsl_kernel.py
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# Config patches (add cutedsl to MoEBackend)
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ARG VLLM_CONFIG_DIR=/usr/local/lib/python3.12/dist-packages/vllm/config
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COPY vllm/patches/kernel.py ${VLLM_CONFIG_DIR}/kernel.py
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# NVFP4 MoE backend registration
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COPY vllm/patches/fused_moe/oracle/nvfp4.py ${VLLM_FUSED_MOE_DIR}/oracle/nvfp4.py
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COPY vllm/patches/fused_moe/experts/cutedsl_moe.py ${VLLM_FUSED_MOE_DIR}/experts/cutedsl_moe.py
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# Register DeepseekV4ForCausalLM model architecture (if not already in upstream)
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RUN grep -q '"DeepseekV4ForCausalLM"' ${VLLM_MODELS_DIR}/registry.py || \
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sed -i 's/"DeepseekV32ForCausalLM": ("deepseek_v2", "DeepseekV3ForCausalLM"),/"DeepseekV32ForCausalLM": ("deepseek_v2", "DeepseekV3ForCausalLM"),\n "DeepseekV4ForCausalLM": ("deepseek_v4", "DeepseekV4ForCausalLM"),/' \
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${VLLM_MODELS_DIR}/registry.py
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# Verify
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RUN python3 -c "import torch; print(f'PyTorch {torch.__version__} OK')" && \
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python3 -c "import vllm; print('vLLM OK')" && \
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python3 -c "import nvfp4_megamoe_kernel; print('NVFP4 kernel OK')" && \
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python3 -c "import cutlass; print('CuTeDSL OK')"
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