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| """ |
| This file implemented unit tests for loading all pretrained HiFiGAN NGC checkpoints and converting Mel-spectrograms into |
| audios. In general, each test for a single model is ~3.5 seconds on an NVIDIA RTX A6000. |
| """ |
|
|
| import pytest |
|
|
| from nemo.collections.tts.models import HifiGanModel |
|
|
| available_models = [model.pretrained_model_name for model in HifiGanModel.list_available_models()] |
|
|
|
|
| @pytest.fixture(params=available_models, ids=available_models) |
| @pytest.mark.run_only_on('GPU') |
| def pretrained_model(request, get_language_id_from_pretrained_model_name): |
| model_name = request.param |
| language_id = get_language_id_from_pretrained_model_name(model_name) |
| model = HifiGanModel.from_pretrained(model_name=model_name) |
| return model, language_id |
|
|
|
|
| @pytest.mark.nightly |
| @pytest.mark.run_only_on('GPU') |
| def test_inference(pretrained_model, mel_spec_example): |
| model, _ = pretrained_model |
| _ = model.convert_spectrogram_to_audio(spec=mel_spec_example) |
|
|