diff --git a/tests/loss_function_test.py b/tests/loss_function_test.py index cd60177..4d14871 100644 --- a/tests/loss_function_test.py +++ b/tests/loss_function_test.py @@ -1,5 +1,3 @@ -from asyncio import base_tasks - import pytest import torch diff --git a/tests/models/demucs_test.py b/tests/models/demucs_test.py index 1ea50c5..f5a0ec4 100644 --- a/tests/models/demucs_test.py +++ b/tests/models/demucs_test.py @@ -1,7 +1,6 @@ import pytest import torch -from enhancer import data from enhancer.data.dataset import EnhancerDataset from enhancer.models import Demucs from enhancer.utils.config import Files @@ -41,4 +40,4 @@ def test_forward(batch_size, samples): ) def test_demucs_init(dataset, channels, loss): with torch.no_grad(): - model = Demucs(num_channels=channels, dataset=dataset, loss=loss) + _ = Demucs(num_channels=channels, dataset=dataset, loss=loss) diff --git a/tests/models/test_waveunet.py b/tests/models/test_waveunet.py index 798ed5d..9c4dd96 100644 --- a/tests/models/test_waveunet.py +++ b/tests/models/test_waveunet.py @@ -1,7 +1,6 @@ import pytest import torch -from enhancer import data from enhancer.data.dataset import EnhancerDataset from enhancer.models import WaveUnet from enhancer.utils.config import Files @@ -41,4 +40,4 @@ def test_forward(batch_size, samples): ) def test_demucs_init(dataset, channels, loss): with torch.no_grad(): - model = WaveUnet(num_channels=channels, dataset=dataset, loss=loss) + _ = WaveUnet(num_channels=channels, dataset=dataset, loss=loss) diff --git a/tests/utils_test.py b/tests/utils_test.py index 1cc171a..65c723d 100644 --- a/tests/utils_test.py +++ b/tests/utils_test.py @@ -1,11 +1,8 @@ -from logging import root - import numpy as np import pytest import torch from enhancer.data.fileprocessor import Fileprocessor -from enhancer.utils.config import Files from enhancer.utils.io import Audio @@ -48,6 +45,6 @@ def test_fileprocessor_names(dataset_name): def test_fileprocessor_invaliname(): with pytest.raises(ValueError): - fp = Fileprocessor.from_name( + _ = Fileprocessor.from_name( "undefined", "clean_dir", "noisy_dir", 16000 ).prepare_matching_dict()