feat: add new model to handle staggered acquisition #130
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- Add LatentStagModel: decode-only architecture with learned z0 - Add latent_stag.py: training loop with z0 bank optimization - Add diagnostics_stag.py: validation diagnostics for staggered model - Add benchmark_rollout.py: compare LatentModel vs LatentStagModel - Add latent_stag_20step.yaml: config with cross-validation datasets - Remove simulation_config/training_data_path mutual exclusivity validation Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
use same key patterns as latent.py (Val/, CrossVal/) for consistency. log diagnostics duration and long rollout metrics. also fix device mismatch in stimulus_utils_test.py. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
plot_long_rollout_mse returns only a Figure, not a tuple. call compute_rollout_stability_metrics separately to get metrics. also fix incorrect type annotation in diagnostics.py. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
only log figures to tensorboard, don't save to disk. remove unused run_dir parameter. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
match latent.py pattern: run_validation_diagnostics returns (metrics, figures) and caller logs with proper prefixes. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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z0latent_stag.pyand forked the default config intolatent_stag_20step.yaml.