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fix: handle numpy object_ dtype from ctranslate2 encoder (#337)

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This commit is contained in:
Quentin Fuxa 2026-02-19 22:18:00 +01:00
parent 4c7706e2cf
commit b8d9d7d289
1 changed files with 6 additions and 6 deletions
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12
whisperlivekit/simul_whisper/simul_whisper.py
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@ -280,13 +280,13 @@ class AlignAtt(AlignAttBase):
if self.device == 'cpu': if self.device == 'cpu':
encoder_feature_ctranslate = np.array(encoder_feature_ctranslate) encoder_feature_ctranslate = np.array(encoder_feature_ctranslate)
try: try:
encoder_feature = torch.as_tensor( encoder_feature = torch.as_tensor(encoder_feature_ctranslate, device=self.device)
encoder_feature_ctranslate, device=self.device,
)
except TypeError: except TypeError:
encoder_feature = torch.as_tensor( # Some numpy/ctranslate2 versions produce object_ dtype arrays; force float32
np.array(encoder_feature_ctranslate), device=self.device, arr = np.array(encoder_feature_ctranslate)
) if arr.dtype == np.object_:
arr = np.array(arr.tolist(), dtype=np.float32)
encoder_feature = torch.as_tensor(arr, device=self.device)
else: else:
mel_padded = log_mel_spectrogram( mel_padded = log_mel_spectrogram(
input_segments, n_mels=self.model.dims.n_mels, input_segments, n_mels=self.model.dims.n_mels,