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import os
import pytest
import torchaudio
from torchaudio.pipelines import (
HUBERT_ASR_LARGE,
HUBERT_ASR_XLARGE,
HUBERT_BASE,
HUBERT_LARGE,
HUBERT_XLARGE,
VOXPOPULI_ASR_BASE_10K_DE,
VOXPOPULI_ASR_BASE_10K_EN,
VOXPOPULI_ASR_BASE_10K_ES,
VOXPOPULI_ASR_BASE_10K_FR,
VOXPOPULI_ASR_BASE_10K_IT,
WAV2VEC2_ASR_BASE_100H,
WAV2VEC2_ASR_BASE_10M,
WAV2VEC2_ASR_BASE_960H,
WAV2VEC2_ASR_LARGE_100H,
WAV2VEC2_ASR_LARGE_10M,
WAV2VEC2_ASR_LARGE_960H,
WAV2VEC2_ASR_LARGE_LV60K_100H,
WAV2VEC2_ASR_LARGE_LV60K_10M,
WAV2VEC2_ASR_LARGE_LV60K_960H,
WAV2VEC2_BASE,
WAV2VEC2_LARGE,
WAV2VEC2_LARGE_LV60K,
WAV2VEC2_XLSR53,
WAV2VEC2_XLSR_1B,
WAV2VEC2_XLSR_300M,
WAVLM_BASE,
WAVLM_BASE_PLUS,
WAVLM_LARGE,
)
@pytest.mark.parametrize(
"bundle",
[
WAV2VEC2_BASE,
WAV2VEC2_LARGE,
WAV2VEC2_LARGE_LV60K,
WAV2VEC2_XLSR53,
HUBERT_BASE,
HUBERT_LARGE,
HUBERT_XLARGE,
WAVLM_BASE,
WAVLM_BASE_PLUS,
WAVLM_LARGE,
],
)
def test_pretraining_models(bundle):
"""Smoke test of downloading weights for pretraining models"""
bundle.get_model()
@pytest.mark.skipif("CI" not in os.environ, reason="Run tests only in CI environment.")
@pytest.mark.parametrize(
"bundle",
[
WAV2VEC2_XLSR_300M,
WAV2VEC2_XLSR_1B,
],
)
def test_xlsr_pretraining_models(bundle):
"""Smoke test of downloading weights for pretraining models"""
bundle.get_model()
@pytest.mark.parametrize(
"bundle,lang,expected",
[
(WAV2VEC2_ASR_BASE_10M, "en", "I|HAD|THAT|CURIYOSSITY|BESID|ME|AT|THIS|MOMENT|"),
(WAV2VEC2_ASR_BASE_100H, "en", "I|HAD|THAT|CURIOSITY|BESIDE|ME|AT|THIS|MOMENT|"),
(WAV2VEC2_ASR_BASE_960H, "en", "I|HAD|THAT|CURIOSITY|BESIDE|ME|AT|THIS|MOMENT|"),
(WAV2VEC2_ASR_LARGE_10M, "en", "I|HAD|THAT|CURIOUSITY|BESIDE|ME|AT|THIS|MOMENT|"),
(WAV2VEC2_ASR_LARGE_100H, "en", "I|HAD|THAT|CURIOSITY|BESIDE|ME|AT|THIS|MOMENT|"),
(WAV2VEC2_ASR_LARGE_960H, "en", "I|HAD|THAT|CURIOSITY|BESIDE|ME|AT|THIS|MOMENT|"),
(WAV2VEC2_ASR_LARGE_LV60K_10M, "en", "I|HAD|THAT|CURIOUSITY|BESID|ME|AT|THISS|MOMENT|"),
(WAV2VEC2_ASR_LARGE_LV60K_100H, "en", "I|HAVE|THAT|CURIOSITY|BESIDE|ME|AT|THIS|MOMENT|"),
(WAV2VEC2_ASR_LARGE_LV60K_960H, "en", "I|HAVE|THAT|CURIOSITY|BESIDE|ME|AT|THIS|MOMENT|"),
(HUBERT_ASR_LARGE, "en", "I|HAVE|THAT|CURIOSITY|BESIDE|ME|AT|THIS|MOMENT|"),
(HUBERT_ASR_XLARGE, "en", "I|HAVE|THAT|CURIOSITY|BESIDE|ME|AT|THIS|MOMENT|"),
(
VOXPOPULI_ASR_BASE_10K_EN,
"en2",
"i|hope|that|we|will|see|a|ddrasstic|decrease|of|funding|for|the|failed|eu|project|and|that|more|money|will|come|back|to|the|taxpayers", # noqa: E501
),
(
VOXPOPULI_ASR_BASE_10K_ES,
"es",
"la|primera|que|es|imprescindible|pensar|a|pequeña|a|escala|para|implicar|y|complementar|así|la|actuación|global", # noqa: E501
),
(VOXPOPULI_ASR_BASE_10K_DE, "de", "dabei|spielt|auch|eine|sorgfältige|berichterstattung|eine|wichtige|rolle"),
(
VOXPOPULI_ASR_BASE_10K_FR,
"fr",
"la|commission|va|faire|des|propositions|sur|ce|sujet|comment|mettre|en|place|cette|capacité|fiscale|et|le|conseil|européen|y|reviendra|sour|les|sujets|au|moins|de|mars", # noqa: E501
),
(
VOXPOPULI_ASR_BASE_10K_IT,
"it",
"credo|che|illatino|non|sia|contemplato|tra|le|traduzioni|e|quindi|mi|attengo|allitaliano",
),
],
)
def test_finetune_asr_model(
bundle,
lang,
expected,
sample_speech,
ctc_decoder,
):
"""Smoke test of downloading weights for fine-tuning models and simple transcription"""
model = bundle.get_model().eval()
waveform, sample_rate = torchaudio.load(sample_speech)
emission, _ = model(waveform)
decoder = ctc_decoder(bundle.get_labels())
result = decoder(emission[0])
assert result == expected
|
