3 Commits

Include renames

Author	SHA1	Message	Date
lars	1ec333ff6d	Merge remote-tracking branch 'origin/master' into fix/issue-87 ... # Conflicts: # giant/config.py	2026-08-28 11:31:05 +02:00
larsandClaude Sonnet 5	bd255419e1	Add inference-time model_config overrides with a sampling-key allowlist (gitea #87) ... giant predict/rollout rebuilt models straight from ckpt["model_config"] with no way to change sampling-only keys (e.g. stage2_model.n_sec.stop_sampling) without retraining. Adds config_overrides to load_for_inference, validated against giant.config.INFERENCE_OVERRIDES so a typo or shape-bearing key raises CheckpointCompatibilityError up front instead of an opaque load_state_dict mismatch. Wired as a repeatable --set dotted.path=value on both CLI commands, recorded in the rollout YAML sidecar, and surfaced in `giant model summary`'s output. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>	2026-08-28 11:21:36 +02:00
larsandClaude Opus 5	cc9646f279	Add giant model summary command (gitea #46) ... giant model summary --config config.toml builds the resolved Stage1/Stage2 graph from a config with no dataset attached (pdg_vocab/mat_vocab are supplied as placeholders via --pdg-vocab/--mat-vocab, since the real training vocab is dataset-derived) and prints per-module parameter counts, trunk in/out widths, which heads exist, and which conditioning/stage1_model/stage2_model config keys actually shaped the build. The consumed-keys half uses differential probing rather than static identifier matching: build once for a fingerprint (submodule presence, every parameter's/buffer's shape+dtype, every plain scalar attribute a module stores on itself), then perturb one leaf at a time, rebuild, and compare. A changed fingerprint (or a raise) means the key is consumed; no change means it's inert *under this particular config* -- e.g. any stage1_model.router.* key when router.enabled=false. A curated _NOT_BUILD_TIME table separates keys legitimately owned by the trainer/sampler/rollout (loss weights, WGAN-GP hyperparameters, teacher-forcing schedules) from genuinely-inert ones, verified against those call sites. A few config keys branch on equality against one specific string literal (n_sec.owner=="stage1", n_sec.mode=="stop_token", particle_type.target=="physical"); a single generic sentinel probe missed all three since the config's current value and the sentinel landed in the same branch, so those three leaves get their real alternative value tried too (_STRING_ALTERNATIVES). giant.config.leaf_paths is promoted out of tests/test_config_consumed_keys.py (previously a private test-local duplicate) so both audits -- the static per-identifier one and this new runtime per-config one -- walk the exact same DEFAULT_CONFIG tree. ExpertTrunk/RoutedTrunk now also expose in_dim (out_dim already existed), needed to report trunk widths generically. Decisions made during planning: --pdg-vocab/--mat-vocab default to 300 and len(MATERIAL_PROPERTIES); the consumed-keys report is scoped to conditioning/stage1_model/stage2_model only (train/meta are out of scope for a model-only build); the module tree prints every submodule at any depth. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>	2026-08-17 11:48:02 +02:00