Weight mapper fixes: - Reorder substr renames: compressor renames first, then .self_attn.compressor. → .attn.mla_attn.compressor., then indexer renames (so indexer keys end up under mla_attn after the compressor rename already fired) - Add compressor param renames: kv_proj→wkv, gate_proj→wgate, kv_norm→norm, position_bias→ape (checkpoint uses NVFP4 naming, model uses internal names) - Add indexer param renames: q_b_proj→wq_b, kv_proj→compressor.wkv, gate_proj→compressor.wgate, kv_norm→k_norm, position_bias→compressor.ape, weights_proj stays (structural: compressor.indexer → indexer.compressor) - Remove broken suffix renames (already fixed in prior commit) Model architecture fixes: - Patch deepseek_compressor.py to pass quant_config (was None, but NVFP4 checkpoint has quantized compressor weights with input_scale/weight_scale) - Patch deepseek_v4_attention.py indexer: weights_proj now uses quant_config (was None, but checkpoint has quantized weights) - Add indexer.compressor.fused_wkv_wgate stacking in load_weights Infrastructure: - Add deepseek_compressor.py to Dockerfile - Force MoE backend to flashinfer_cutedsl (was auto-selecting FLASHINFER_TRTLLM) - Update unit test to 50 cases (compressor + indexer + quantization scales)
37 lines
969 B
YAML
37 lines
969 B
YAML
services:
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vllm:
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build:
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context: .
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dockerfile: Dockerfile
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ports:
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- "8000:8000"
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environment:
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- OMP_NUM_THREADS=128
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- CUDA_LAUNCH_BLOCKING=0
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- PYTHONUNBUFFERED=1
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- VLLM_RPC_TIMEOUT_MS=600000
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- CLAWMINE_DEBUG=1
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command:
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- /model
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- --trust-remote-code
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- --enable-expert-parallel
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- --tensor-parallel-size=8
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- --compilation-config={"cudagraph_mode":"NONE","custom_ops":["all"]}
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- --tokenizer-mode=deepseek_v4
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- --tool-call-parser=deepseek_v4
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- --enable-auto-tool-choice
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- --reasoning-parser=deepseek_v4
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- --moe-backend=flashinfer_cutedsl
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- --gpu-memory-utilization=0.9
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- --host=0.0.0.0
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- --port=8000
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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count: all
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capabilities: [gpu]
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volumes:
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- /root/nvidia-meeting/DeepSeek-V4-Pro-NVFP4:/model:ro
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