AttentionHistory (giant/model/network.py) adds causal self-attention over
the emitted-secondary prefix as the alternative to MarkovHistory, with a
parallel forward() for training and an init_cache()/step() KV-cache path
for sample.py's per-slot AR inference loop, wired into
Stage2Autoregressive via history="attention".
giant/train.py adds _stage2_tf_prob and _assemble_stage2_ar_inputs_scheduled,
mixing ground-truth history with a detached sample_secondaries_ar self-sample
per slot so teacher_forcing="scheduled"/"never" close the train/inference gap
teacher_forcing="always" always avoided; wired into both stage-2 AR trainers.
config.py's validate_config no longer rejects these two previously
unimplemented schema values.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
lars
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