Release v0.12.0

asteroid-team · Jan 15, 2025 · 9115aba · 9115aba
1 parent bb90cf9
commit 9115aba
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Showing 6 changed files with 9 additions and 5 deletions.
diff --git a/README.md b/README.md
@@ -217,7 +217,9 @@ classification. It was successfully applied in the paper
 
 * Add new transforms: `Mix`, `Padding`, `RandomCrop` and `SpliceOut`
 
-### Changes
+## [v0.12.0] - 2025-01-15
+
+### Removed
 
 * Remove `librosa` dependency in favor of `torchaudio`
 

diff --git a/scripts/demo.py b/scripts/demo.py
@@ -96,7 +96,6 @@ def __exit__(self, type, value, traceback):
     num_samples = min(num_samples1, num_samples2)
     samples = torch.stack([samples1[:, :num_samples], samples2[:, :num_samples]], dim=0)
 
-
     modes = ["per_batch", "per_example", "per_channel"]
     for mode in modes:
         transforms = [

diff --git a/tests/test_background_noise.py b/tests/test_background_noise.py
@@ -16,6 +16,7 @@
 from .utils import TEST_FIXTURES_DIR
 from torch_audiomentations.utils.io import Audio
 
+
 class TestAddBackgroundNoise(unittest.TestCase):
     def setUp(self):
         self.sample_rate = 16000

diff --git a/tests/test_convolution.py b/tests/test_convolution.py
@@ -6,6 +6,7 @@
 from torch_audiomentations.utils.convolution import convolve as torch_convolve
 from torch_audiomentations.utils.io import Audio
 
+
 class TestConvolution:
     def test_convolve(self):
         sample_rate = 16000
@@ -15,7 +16,6 @@ def test_convolve(self):
         samples = audio(file_path).numpy()
         ir_samples = audio(TEST_FIXTURES_DIR / "ir" / "impulse_response_0.wav").numpy()
 
-
         expected_output = scipy_convolve(samples, ir_samples)
         actual_output = torch_convolve(
             torch.from_numpy(samples), torch.from_numpy(ir_samples)

diff --git a/torch_audiomentations/__init__.py b/torch_audiomentations/__init__.py
@@ -18,4 +18,4 @@
 from .utils.config import from_dict, from_yaml
 from .utils.convolution import convolve
 
-__version__ = "0.11.2"
+__version__ = "0.12.0"
diff --git a/torch_audiomentations/utils/io.py b/torch_audiomentations/utils/io.py
@@ -153,7 +153,9 @@ def downmix_and_resample(self, samples: Tensor, sample_rate: int) -> Tensor:
 
         # resample
         if self.sample_rate != sample_rate:
-            samples = torchaudio.functional.resample(samples, sample_rate, self.sample_rate)
+            samples = torchaudio.functional.resample(
+                samples, sample_rate, self.sample_rate
+            )
 
         return samples