Replace the single global train.mode + [model] block with the four
top-level blocks docs/v0.3.0-design.md specifies ([conditioning],
[stage1_model], [stage2_model], [train]), so Stage 1 and Stage 2 can
run independent generative objectives and Stage 2 can train standalone.
- migrate_config translates old config.toml/checkpoint dicts on load,
so nothing on /ceph goes dead; loudly rejects non-zero
expert_hidden_dim/expert_n_blocks, which v0.3.0 no longer supports.
- merge_cli_overrides/save_config generalize from one hardcoded nesting
level (model.router) to arbitrary recursive depth.
- default_out_dir_name candidates move to dotted paths against the new
schema, with per-stage router/generator discriminators.
- validate_config adds cross-block checks the per-block schema can't
express (particle_type.target=embedding needs a matching conditioning
mode, tie_to_stage1 needs an active stage 1, etc).
- resolve_expert_dims is deleted (experts always inherit the stage's
hidden_dim/n_res_blocks now) — pipeline.py/cli.py callers are left
dangling on purpose, to be updated in the network.py/train.py steps
that follow.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
lars
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