fix(libero): fail loudly on tasks with empty init-state sets

[akushonkamen]

Fixes #246

Description

make_env() in robots/libero/env_server.py:115-117 indexed straight into get_task_init_states(...) with no guard for tasks whose pruned_init file ships zero states:

• seed % len(...) degenerated to seed % 0, surfacing only as a context-free ZeroDivisionError at env_server.py:117;
• aggregation paths that tolerate the crash kept going and silently shrank the evaluation denominator (100 → 90/80), making results incomparable.

Fix:

• Guard make_env(): when the requested task has 0 init states, raise a RuntimeError naming the suite, the requested task id, and every empty task in the suite (best-effort scan via get_num_tasks(); API signature verified against RLinf/LIBERO-PRO@rpent, liberopro/liberopro/benchmark/__init__.py:269-295).
• Document the three currently known empty pruned_init tasks (libero_10_task#2, libero_spatial_task#3/#7) plus the HF-snapshot restore procedure in pro_hybrid_guide.md §2.3.
• Add 3 offline fake-suite unit tests (2 for the guard, 1 healthy-task rid-math regression) in tests/unit_tests/robots/libero/test_env_server_init_states.py.

Data side (BDDL consistency check + pruned_init regeneration) belongs to the upstream LIBERO-PRO simulation pipeline per the issue triage and was not done locally; a timeout 60 probe found no LIBERO entries under ~/.cache/huggingface, so real-dataset reproduction was not executed here (the issue-sanctioned fake-suite path covers the guard).

Testing

• Red (before fix): venvs/rlinf1662/bin/python -m pytest tests/unit_tests/robots/libero/test_env_server_init_states.py -q → 2 failed (test_make_env_fails_loudly_on_empty_init_states, test_make_env_error_lists_every_empty_task_in_suite, both ZeroDivisionError at env_server.py:117), 1 passed.
• Green (after fix): timeout 300 venvs/rlinf1662/bin/python -m pytest tests/unit_tests -k "env_server or init_state" -q --continue-on-collection-errors → 4 passed, 1 skipped (the flag is needed because of a pre-existing, unrelated collection error in tests/unit_tests/rpent/planner/test_codex_contracts.py / openai_codex). Re-confirmed right before submission with the same numbers.
• Regression: timeout 590 venvs/rlinf1662/bin/python -m pytest tests/unit_tests -q --continue-on-collection-errors → 14 failed, 1147 passed, 7 skipped.
• Baseline diff (stashed fix, clean main + new test file): 16 failed = the same 14 pre-existing failures + the 2 guard tests red → zero new failures introduced by the fix.
• Lint: timeout 120 ruff check robots/libero → All checks passed!; ruff format --check robots/libero → 18 files already formatted; tests/unit_tests/robots/libero passes both as well.
• End-to-end: /tmp/issue246-repro/repro_zero_states.py → RuntimeError listing suite, requested task, and the full empty-task inventory for the suite.

Manual verification

Not needed — offline tests fully cover the change. The guard's runtime message was exercised end-to-end via the fake-suite repro script above (no GPU/simulator/model service involved). Real-dataset reproduction was not possible locally (no HF LIBERO cache; see Description).

Checklist

• My code follows the code style of this project.
• I have updated related documentation when needed.
• I have added tests to cover my changes when needed.
• All new and existing tests passed. (14 pre-existing failures on main are unchanged by this PR; see baseline diff above.)

AI disclosure: this change was prepared with AI assistance; the contributor has reviewed the full diff and run all listed checks.

[chatgpt-codex-connector]

Codex Review Summary

This comment shows the latest Codex review activity on this pull request.

Review	Status	Commit	Review trigger
📝 Code Review	⚠️ Failed 2026-10-11T15:19:43.411929Z	8ad9992	PR opened

ℹ️ About Codex in GitHub

Your team has set up Codex to review pull requests in this repo. Reviews are triggered when you

• Open a pull request for review
• Mark a draft as ready
• Comment "@codex review" or "@codex security review".

Codex reacts with 👀 while any review is running, comments if it has suggestions, and reacts with 👍 once all reviews finish with no findings.