Merge branch 'release/3.3.1'

.github/workflows/test.yml

@@ -13,7 +13,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest]
-        python-version: [3.8, 3.9, "3.10"]
+        python-version: ["3.9", "3.10", "3.11"]
     steps:
       - uses: actions/checkout@v2
       - name: Set up Python ${{ matrix.python-version }}

CHANGELOG.md

@@ -1,5 +1,18 @@
 # Changelog
 
+
+## Version 3.3.1 (2024-06-19)
+
+### Breaking changes
+
+- setup: drop support for Python 3.8
+
+### Fixes
+
+- fix: fix support for `numpy==2.x` ([@ibevers](https://github.com/ibevers/))
+- fix: fix support for `speechbrain==1.x` ([@Adel-Moumen](https://github.com/Adel-Moumen/))
+
+
 ## Version 3.3.0 (2024-06-14)
 
 ### TL;DR

pyannote/audio/core/inference.py

@@ -526,7 +526,7 @@ def aggregate(
         warm_up: Tuple[float, float] = (0.0, 0.0),
         epsilon: float = 1e-12,
         hamming: bool = False,
-        missing: float = np.NaN,
+        missing: float = np.nan,
         skip_average: bool = False,
     ) -> SlidingWindowFeature:
         """Aggregation

pyannote/audio/pipelines/speaker_verification.py

@@ -40,7 +40,7 @@
 from pyannote.audio.pipelines.utils import PipelineModel, get_model
 
 try:
-    from speechbrain.pretrained import (
+    from speechbrain.inference import (
         EncoderClassifier as SpeechBrain_EncoderClassifier,
     )
 

pyannote/audio/tasks/segmentation/mixins.py

@@ -401,7 +401,7 @@ def validation_step(self, batch, batch_idx: int):
         )
 
         # reshape target so that there is one line per class when plotting it
-        y[y == 0] = np.NaN
+        y[y == 0] = np.nan
         if len(y.shape) == 2:
             y = y[:, :, np.newaxis]
         y *= np.arange(y.shape[2])

pyannote/audio/tasks/segmentation/speaker_diarization.py

@@ -818,7 +818,7 @@ def validation_step(self, batch, batch_idx: int):
         )
 
         # reshape target so that there is one line per class when plotting it
-        y[y == 0] = np.NaN
+        y[y == 0] = np.nan
         if len(y.shape) == 2:
             y = y[:, :, np.newaxis]
         y *= np.arange(y.shape[2])

pyannote/audio/tasks/separation/PixIT.py

@@ -1136,7 +1136,7 @@ def validation_step(self, batch, batch_idx: int):
         )
 
         # reshape target so that there is one line per class when plotting it
-        y[y == 0] = np.NaN
+        y[y == 0] = np.nan
         if len(y.shape) == 2:
             y = y[:, :, np.newaxis]
         y *= np.arange(y.shape[2])

requirements.txt

@@ -11,7 +11,7 @@ pytorch_metric_learning >= 2.1.0
 rich >= 12.0.0
 semver >= 3.0.0
 soundfile >= 0.12.1
-speechbrain >= 0.5.14
+speechbrain >= 1.0.0
 tensorboardX >= 2.6
 torch >= 2.0.0
 torch_audiomentations >= 0.11.0

setup.cfg

@@ -27,7 +27,7 @@ setup_requires = pyscaffold>=3.2a0,<3.3a0
 # Add here dependencies of your project (semicolon/line-separated), e.g.
 # install_requires = numpy; scipy
 # Require a specific Python version, e.g. Python 2.7 or >= 3.4
-python_requires = >=3.7
+python_requires = >=3.9
 
 [options.packages.find]
 where = .

setup.py

@@ -56,9 +56,9 @@
             "Intended Audience :: Science/Research",
             "License :: OSI Approved :: MIT License",
             "Natural Language :: English",
-            "Programming Language :: Python :: 3.8",
             "Programming Language :: Python :: 3.9",
             "Programming Language :: Python :: 3.10",
+            "Programming Language :: Python :: 3.11",
             "Topic :: Scientific/Engineering",
         ],
     )

tests/test_speechbrain.py

@@ -0,0 +1,20 @@
+import tempfile
+import pytest
+from speechbrain.inference import EncoderClassifier
+
+
+@pytest.fixture()
+def cache():
+    return tempfile.mkdtemp()
+
+def test_import_speechbrain_encoder_classifier(cache):
+    """This is a simple test that check if speechbrain
+    EncoderClassifier can be imported. It does not check
+    if the model is working properly. 
+    """
+
+    model = EncoderClassifier.from_hparams(
+        source="speechbrain/spkrec-ecapa-voxceleb", 
+        savedir=cache,
+    )
+    assert isinstance(model, EncoderClassifier)

version.txt

@@ -1 +1 @@
-3.3.0
+3.3.1