File size: 2,999 Bytes
d5f6dbd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 | """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))
# Default curriculum is the 3 demo systems × 2 instances = 6 rows.
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 # 2 Tier 3 systems
assert len(train_rows) >= 6 # 6 Tier 1+2 systems
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
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