tests : fix multi-seq split replay and partial-state cases for trained models ( #31216 )
tests : fix multi-seq split replay against trained models
The rollback snapshot is captured by the graph that decoded the rolled-back
tail, while the reference context decodes the same prefix with different
batch shapes. The two states differ in the last bits and trained models
amplify the difference with every replayed token. Compare only the first
replayed token of each seq, then restore the rollback state into the
reference context before the seq-1-only tail.
Assisted-by: dsh:llama.cpp/ggml-org/Qwen3.8-Flash-Next-GGUF (MacBook, M5 Max, 128GB)
tests : require bit-exact seq-1 isolation in split replay
The seq state save is not always bit-lossless - SWA-masked cells are not
saved - so reload the restored state back into the rollback context. That
way both contexts enter the seq-1-only tail with byte-identical memory,
including the cell layout, and the tail logits must match bit-exact. Also
assert that the restored state round-trips bit-identical.
Assisted-by: dsh:llama.cpp/ggml-org/Qwen3.8-Flash-Next-GGUF (MacBook, M5 Max, 128GB)
tests : drop the n_swa partial-state check from ps
The check keys off llama_model_n_swa(), which returns 0 for dsv4 even
though its raw KV cache has a 128-cell sliding window. The partial state
grows with the tokens there by design, so the flatness check is wrong.
Keep the partial <= full invariant.
Assisted-by: dsh:llama.cpp/ggml-org/Qwen3.8-Flash-Next-GGUF (MacBook, M5 Max, 128GB)
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https://github.com/ggml-org/llama.cpp/attestations/60276548
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