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valoomba/
rdna3-qwen-attention

Name: rdna3-qwen-attention
Availability: InStock

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RDNA3 Qwen Attention

ROCm cached-decode GQA attention kernel for Qwen3.6-style full-attention layers on RDNA3 (gfx1100) GPUs.

The package exposes:

attention_decode(query, key, value, num_key_value_groups=None, scaling=None)
rdna3_gqa_attention_forward(...), a Transformers AttentionInterface-style wrapper that uses the native kernel for supported cached-decode calls and falls back to PyTorch SDPA otherwise.

python

from kernels import get_kernel

kernel = get_kernel("valoomba/rdna3-qwen-attention", version=1)
out = kernel.attention_decode(query, key, value)

For Transformers integration, register kernel.rdna3_gqa_attention_forward with the model's attention registry in the calling project.

Benchmarking script is available for this kernel:

kernels benchmark valoomba/rdna3-qwen-attention --version 1