46 lines
1.2 KiB
Python
46 lines
1.2 KiB
Python
import pytest
|
|
import torch
|
|
|
|
from mayavoz.data.dataset import MayaDataset
|
|
from mayavoz.models import Demucs
|
|
from mayavoz.utils.config import Files
|
|
|
|
|
|
@pytest.fixture
|
|
def vctk_dataset():
|
|
root_dir = "tests/data/vctk"
|
|
files = Files(
|
|
train_clean="clean_testset_wav",
|
|
train_noisy="noisy_testset_wav",
|
|
test_clean="clean_testset_wav",
|
|
test_noisy="noisy_testset_wav",
|
|
)
|
|
dataset = MayaDataset(
|
|
name="vctk", root_dir=root_dir, files=files, sampling_rate=16000
|
|
)
|
|
return dataset
|
|
|
|
|
|
@pytest.mark.parametrize("batch_size,samples", [(1, 1000)])
|
|
def test_forward(batch_size, samples):
|
|
model = Demucs()
|
|
model.eval()
|
|
|
|
data = torch.rand(batch_size, 1, samples, requires_grad=False)
|
|
with torch.no_grad():
|
|
_ = model(data)
|
|
|
|
data = torch.rand(batch_size, 2, samples, requires_grad=False)
|
|
with torch.no_grad():
|
|
with pytest.raises(ValueError):
|
|
_ = model(data)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"dataset,channels,loss",
|
|
[(pytest.lazy_fixture("vctk_dataset"), 1, ["mae", "mse"])],
|
|
)
|
|
def test_demucs_init(dataset, channels, loss):
|
|
with torch.no_grad():
|
|
_ = Demucs(num_channels=channels, dataset=dataset, loss=loss)
|