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6183caf a9536c4 6183caf a9536c4 | 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 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 | import subprocess
import sys
import tempfile
import unittest
from pathlib import Path
import numpy as np
import soundfile as sf
REPO_ROOT = Path(__file__).resolve().parents[1]
if str(REPO_ROOT) not in sys.path:
sys.path.insert(0, str(REPO_ROOT))
class ModelDefaultTests(unittest.TestCase):
def test_roformer_default_uses_public_audio_separator_sota_model(self):
from infer import separator
self.assertEqual(
separator.ROFORMER_DEFAULT_MODEL,
"ensemble:vocal_rvc",
)
self.assertEqual(
separator.ROFORMER_SOTA_MODELS,
[
"melband_roformer_big_beta6x.ckpt",
"mel_band_roformer_vocals_fv4_gabox.ckpt",
],
)
self.assertIn(
"vocals_mel_band_roformer.ckpt",
separator.ROFORMER_LEGACY_SINGLE_MODEL,
)
def test_karaoke_default_uses_public_sota_ensemble(self):
from infer import separator
self.assertEqual(
separator.KARAOKE_DEFAULT_MODEL,
"ensemble:karaoke",
)
self.assertEqual(
separator.KARAOKE_SOTA_MODEL,
"ensemble:karaoke",
)
self.assertEqual(
separator.KARAOKE_SOTA_MODELS,
[
"mel_band_roformer_karaoke_aufr33_viperx_sdr_10.1956.ckpt",
"mel_band_roformer_karaoke_gabox_v2.ckpt",
"mel_band_roformer_karaoke_becruily.ckpt",
],
)
self.assertEqual(
separator.KARAOKE_LEGACY_SINGLE_MODEL,
"mel_band_roformer_karaoke_gabox.ckpt",
)
def test_deecho_default_uses_public_roformer_dereverb_model(self):
from infer import separator
self.assertEqual(
separator.ROFORMER_DEREVERB_DEFAULT_MODEL,
"dereverb_mel_band_roformer_anvuew_sdr_19.1729.ckpt",
)
def test_strict_sota_defaults_do_not_expose_model_fallback_lists(self):
from infer import separator
self.assertFalse(hasattr(separator, "ROFORMER_FALLBACK_MODELS"))
self.assertFalse(hasattr(separator, "KARAOKE_FALLBACK_MODELS"))
self.assertFalse(hasattr(separator, "ROFORMER_DEREVERB_FALLBACK_MODELS"))
def test_separator_import_survives_missing_audio_separator(self):
script = """
import importlib.abc
import sys
class BlockAudioSeparator(importlib.abc.MetaPathFinder):
def find_spec(self, fullname, path=None, target=None):
if fullname == "audio_separator" or fullname.startswith("audio_separator."):
raise ImportError("blocked audio_separator")
return None
sys.meta_path.insert(0, BlockAudioSeparator())
from infer import separator
assert separator.AUDIO_SEPARATOR_AVAILABLE is False
try:
separator.RoformerSeparator()
except ImportError as exc:
assert "audio-separator" in str(exc)
else:
raise AssertionError("RoformerSeparator should fail when audio_separator is missing")
"""
result = subprocess.run(
[sys.executable, "-c", script],
cwd=REPO_ROOT,
text=True,
capture_output=True,
check=False,
)
self.assertEqual(
result.returncode,
0,
msg=f"stdout:\n{result.stdout}\nstderr:\n{result.stderr}",
)
class KaraokeCandidateScoringTests(unittest.TestCase):
def test_karaoke_candidate_score_rewards_reconstruction_and_low_correlation(self):
from tools.evaluate_karaoke_models import score_karaoke_stems
sr = 16000
t = np.arange(sr, dtype=np.float32) / sr
lead_good = 0.18 * np.sin(2 * np.pi * 220 * t)
backing_good = 0.05 * np.sin(2 * np.pi * 330 * t + 0.4)
input_vocals = lead_good + backing_good
with tempfile.TemporaryDirectory() as tmp_dir:
tmp_path = Path(tmp_dir)
input_path = tmp_path / "input.wav"
lead_good_path = tmp_path / "lead_good.wav"
backing_good_path = tmp_path / "backing_good.wav"
lead_bad_path = tmp_path / "lead_bad.wav"
backing_bad_path = tmp_path / "backing_bad.wav"
sf.write(input_path, input_vocals, sr)
sf.write(lead_good_path, lead_good, sr)
sf.write(backing_good_path, backing_good, sr)
sf.write(lead_bad_path, input_vocals, sr)
sf.write(backing_bad_path, 0.7 * input_vocals, sr)
good = score_karaoke_stems(input_path, lead_good_path, backing_good_path)
bad = score_karaoke_stems(input_path, lead_bad_path, backing_bad_path)
self.assertGreater(good["score"], bad["score"])
self.assertLess(good["reconstruction_error"], bad["reconstruction_error"])
self.assertLess(good["lead_backing_abs_corr"], bad["lead_backing_abs_corr"])
def test_karaoke_candidate_score_penalizes_truncated_stems(self):
from tools.evaluate_karaoke_models import score_karaoke_stems
sr = 16000
t = np.arange(sr, dtype=np.float32) / sr
lead_good = 0.18 * np.sin(2 * np.pi * 220 * t)
backing_good = 0.04 * np.sin(2 * np.pi * 330 * t + 0.4)
input_vocals = lead_good + backing_good
short_len = sr // 4
with tempfile.TemporaryDirectory() as tmp_dir:
tmp_path = Path(tmp_dir)
input_path = tmp_path / "input.wav"
lead_short_path = tmp_path / "lead_short.wav"
backing_short_path = tmp_path / "backing_short.wav"
lead_full_path = tmp_path / "lead_full.wav"
backing_full_path = tmp_path / "backing_full.wav"
sf.write(input_path, input_vocals, sr)
sf.write(lead_short_path, lead_good[:short_len], sr)
sf.write(backing_short_path, backing_good[:short_len], sr)
sf.write(lead_full_path, 0.97 * lead_good, sr)
sf.write(backing_full_path, 0.97 * backing_good, sr)
short = score_karaoke_stems(input_path, lead_short_path, backing_short_path)
full = score_karaoke_stems(input_path, lead_full_path, backing_full_path)
self.assertIn("length_coverage", short)
self.assertLess(short["length_coverage"], 0.999)
self.assertGreaterEqual(full["length_coverage"], 0.999)
self.assertGreater(full["score"], short["score"])
def test_reference_karaoke_score_uses_true_si_sdr_when_refs_exist(self):
from tools.evaluate_karaoke_models import score_reference_stems
sr = 16000
t = np.arange(sr, dtype=np.float32) / sr
lead = 0.18 * np.sin(2 * np.pi * 220 * t)
backing = 0.04 * np.sin(2 * np.pi * 330 * t + 0.4)
with tempfile.TemporaryDirectory() as tmp_dir:
tmp_path = Path(tmp_dir)
reference_lead_path = tmp_path / "reference_lead.wav"
reference_backing_path = tmp_path / "reference_backing.wav"
lead_path = tmp_path / "lead.wav"
backing_path = tmp_path / "backing.wav"
sf.write(reference_lead_path, lead, sr)
sf.write(reference_backing_path, backing, sr)
sf.write(lead_path, lead, sr)
sf.write(backing_path, backing, sr)
metrics = score_reference_stems(
reference_lead_path,
reference_backing_path,
lead_path,
backing_path,
)
self.assertGreater(metrics["mean_si_sdr"], 100.0)
self.assertIn("lead", metrics["stems"])
self.assertIn("backing", metrics["stems"])
if __name__ == "__main__":
unittest.main()
|