- add logits_positions to AutoRegressiveLM.forward, gathering rows before the final norm so the lm_head GEMM covers only the positions prefill samples from
- execute_prefill builds last_token_indices up front and passes them in, dropping the post-forward gather of a [tokens, vocab] tensor
- prefill graph warmup passes a single index; decode stays untouched (every row is sampled) and prefill itself runs eager, so graph capture is unaffected
- update the ragged-prefill fake to slice by the received index and add a packed-row exact-equality test
Benchmark: NVIDIA L20 (idle), CUDA 12.8, torch 2.11.0+cu128, 1.2B bf16 checkpoint, 512-token prompts, greedy; prefill B=32: 368.1 -> 323.5 ms (44.5k -> 50.6k tok/s, +13.8%), B=8: 89.3 -> 78.9 ms (+13.2%), B=1: 12.3 -> 11.4 ms (+7.9%); decode step unchanged; full suite: 897 passed
ViperEkura
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