| # Validation |
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|
| Required on NVIDIA Thor with CUDA 13 and CUTLASS DSL 4.4.x, 4.5.x, or 4.6.x: |
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|
| ```bash |
| python tests/test_fa4_cute_runtime.py --backend source --mode full |
| python tests/test_fa4_cute_runtime.py --backend installed --mode full \ |
| --artifact build/torch-cuda |
| ``` |
|
|
| The gate covers non-causal and causal GQA, head dimensions 48/72/128, and the |
| PI0.5 D256 encoder family. D256 cases include dense lengths 320/968 and padded |
| `seqused_k` lengths 456/712 in a 968-token buffer. Every case reports |
| max/p99/mean/cosine metrics and requires bitwise CUDA Graph replay after JIT |
| warmup. |
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|
| On 2026-08-06, the current source snapshot passed `8/8` rows on NVIDIA Thor |
| (SM110), PyTorch `2.13.0+cu130`, CUDA 13.0, and CUTLASS DSL 4.4.2. D48/D72/D128 |
| and all four D256 rows passed; worst p99 absolute error was `0.000244` and |
| worst cosine was `0.99999982`. CUDA Graph replay was bitwise deterministic. |
| The torch-noarch final-layout import probe also passed from the isolated Thor |
| environment. |
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| The same `8/8` source matrix passed on the same Thor with CUTLASS DSL 4.6.1. |
| The 4.6 compatibility aliases cover public API relocations only; D48/D72/D128 |
| and D256 dense/seqused results matched the 4.4.2 gate. |
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| Installed-artifact execution and performance must still be rerun after every |
| Hub rebuild. Source qualification alone is not a release artifact claim. |
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|
