| """Unit tests for :mod:`physix.training.dataset`.""" |
|
|
| from __future__ import annotations |
|
|
| import pytest |
|
|
| from physix.systems import SUPPORTED_SYSTEMS |
| from physix.training.dataset import ( |
| DatasetSpec, |
| EvalDatasetSpec, |
| build_eval_dataset, |
| build_training_dataset, |
| ) |
|
|
|
|
| _EXPECTED_COLUMNS = { |
| "prompt", |
| "system_id", |
| "state_variables", |
| "parameters", |
| "initial_conditions", |
| "timestamps", |
| "observed", |
| "previous_r_match", |
| } |
|
|
|
|
| def test_training_dataset_has_expected_schema() -> None: |
| ds = build_training_dataset(DatasetSpec(instances_per_system=2)) |
|
|
| assert _EXPECTED_COLUMNS.issubset(set(ds.column_names)) |
| |
| assert len(ds) == len(SUPPORTED_SYSTEMS) * 2 |
|
|
|
|
| def test_training_dataset_default_curriculum_is_demo_systems() -> None: |
| """Default DatasetSpec must train on exactly the same systems the |
| live demo exposes. Mismatches would mean GRPO improves systems we |
| never benchmark — the failure mode that produced flat headline |
| metrics in the v1 training run. |
| """ |
| ds = build_training_dataset(DatasetSpec(instances_per_system=1)) |
| assert set(ds["system_id"]) == set(SUPPORTED_SYSTEMS) |
|
|
|
|
| def test_training_dataset_explicit_system_ids_override_default() -> None: |
| ds = build_training_dataset( |
| DatasetSpec(system_ids=("free_fall", "simple_pendulum"), instances_per_system=1) |
| ) |
| assert set(ds["system_id"]) == {"free_fall", "simple_pendulum"} |
|
|
|
|
| def test_training_dataset_rejects_unknown_system_ids() -> None: |
| with pytest.raises(ValueError, match="Unknown system_ids"): |
| build_training_dataset(DatasetSpec(system_ids=("not_a_real_system",))) |
|
|
|
|
| def test_training_dataset_rejects_empty_system_ids() -> None: |
| with pytest.raises(ValueError, match="non-empty"): |
| build_training_dataset(DatasetSpec(system_ids=())) |
|
|
|
|
| def test_training_dataset_prompts_are_chat_lists() -> None: |
| ds = build_training_dataset(DatasetSpec(instances_per_system=1)) |
| prompt = ds[0]["prompt"] |
|
|
| assert isinstance(prompt, list) |
| assert prompt[0]["role"] == "system" |
| assert prompt[1]["role"] == "user" |
| assert "TRAJECTORY" in prompt[1]["content"] |
|
|
|
|
| def test_eval_dataset_marks_held_out_rows() -> None: |
| ds = build_eval_dataset(EvalDatasetSpec(instances_per_system=1)) |
|
|
| held_out_rows = [r for r in ds if r["is_held_out"]] |
| train_rows = [r for r in ds if not r["is_held_out"]] |
|
|
| assert len(held_out_rows) >= 2 |
| assert len(train_rows) >= 6 |
| held_out_ids = {row["system_id"] for row in held_out_rows} |
| assert held_out_ids == {"projectile_drag", "charged_b_field"} |
|
|
|
|
| def test_dataset_observed_arrays_match_state_variables() -> None: |
| ds = build_training_dataset(DatasetSpec(instances_per_system=1)) |
|
|
| for row in ds: |
| observed = row["observed"] |
| for var in row["state_variables"]: |
| assert var in observed |
| assert len(observed[var]) > 0 |
|
|