Datasets:
File size: 2,653 Bytes
2f94fe0 | 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 | from __future__ import annotations
from pathlib import Path
import pytest
from voice_code_bench.figures import MODEL_LABELS, PAPER_MODEL_IDS, default_output_path, parse_overall_results, spearman
DATASET_ROOT = Path(__file__).resolve().parents[1]
RESULTS_PATH = DATASET_ROOT / "baselines" / "results.csv"
def test_paper_model_set_remains_frozen() -> None:
rows = parse_overall_results(RESULTS_PATH, model_set="paper")
assert len(rows) == len(PAPER_MODEL_IDS) == 12
assert all(row["model"] != "Thinking Machines Inkling-NVFP4 via Modal (effort=max)" for row in rows)
assert all(row["model"] != "Meta OmniASR LLM Unlimited 7B v2 via Modal" for row in rows)
wer = [float(row["wer"]) for row in rows]
assert spearman(wer, [float(row["ctem"]) for row in rows]) == pytest.approx(-0.7342657343)
assert spearman(wer, [float(row["tsr"]) for row in rows]) == pytest.approx(-0.7285475271)
def test_all_model_set_includes_current_post_publication_results() -> None:
assert MODEL_LABELS["modal_meta_omniasr_llm_unlimited_7b_v2"] == (
"Meta OmniASR LLM Unlimited 7B v2 via Modal",
"Batch",
)
rows = parse_overall_results(RESULTS_PATH, model_set="all")
assert len(rows) == 15
inkling = next(
row
for row in rows
if row["model"] == "Thinking Machines Inkling-NVFP4 via Modal (effort=max)"
)
assert inkling["wer"] == pytest.approx(24.2933573221)
assert inkling["ctem"] == pytest.approx(84.2780026991)
assert inkling["tsr"] == pytest.approx(49.6666666667)
parakeet = next(
row
for row in rows
if row["model"] == "NVIDIA Parakeet TDT 0.6B v3 via Modal"
)
assert parakeet["wer"] == pytest.approx(23.6612849770)
assert parakeet["ctem"] == pytest.approx(78.6099865047)
assert parakeet["tsr"] == pytest.approx(37.3333333333)
omniasr = next(
row
for row in rows
if row["model"] == "Meta OmniASR LLM Unlimited 7B v2 via Modal"
)
assert omniasr["wer"] == pytest.approx(26.1090857440)
assert omniasr["ctem"] == pytest.approx(72.4696356275)
assert omniasr["tsr"] == pytest.approx(25.6666666667)
def test_model_set_default_outputs_do_not_overlap() -> None:
paper_output = DATASET_ROOT / "paper" / "figures" / "wer_entity_scatter.pdf"
all_output = DATASET_ROOT / "baselines" / "figures" / "wer_entity_scatter.pdf"
assert default_output_path(DATASET_ROOT, "paper") == paper_output
assert default_output_path(DATASET_ROOT, "all") == all_output
with pytest.raises(ValueError, match="Unknown figure model set"):
default_output_path(DATASET_ROOT, "unknown")
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