vllm.models.step5.nvidia.ops
¶
Modules:
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add–Add low-precision tensors without materializing their FP32 conversions.
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attention_gate–Headwise sigmoid output gating with the original low-precision rounding.
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mtp_norm–Normalize MTP embedding and hidden states directly into the projection input.
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qkv_indexer_norm_rope–Joint attention QKV and sparse-indexer preparation for decode.
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rms_norm–RMSNorm with independent input, weight and output dtypes.
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sparse_prefill–Compact sparse-prefill KV gathering and reusable host planning metadata.
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sparse_prefill_pages–Compact eight-token pages for sparse prefill attention.
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swa_decode–Sliding-window GQA decode with split KV and a fused headwise gate.