fix: fix support for NumPy 2.0.0

pyannote · Jun 19, 2024 · 50b21d4 · 50b21d4
1 parent cd3f550
commit 50b21d4
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Showing 5 changed files with 10 additions and 4 deletions.
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,5 +1,11 @@
 # Changelog
 
+## develop
+
+### Fixes
+
+- fix: fix support for `numpy==2.x` ([@ibevers](https://github.com/ibevers/))
+
 ## Version 3.3.0 (2024-06-14)
 
 ### TL;DR

diff --git a/pyannote/audio/core/inference.py b/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

diff --git a/pyannote/audio/tasks/segmentation/mixins.py b/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])

diff --git a/pyannote/audio/tasks/segmentation/speaker_diarization.py b/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])

diff --git a/pyannote/audio/tasks/separation/PixIT.py b/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])