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Merge pull request #2224 from pipecat-ai/khk/mps

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Add MPS backend auto-detection to local smart-turn v2
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Kwindla Hultman Kramer
2025-07-21 09:24:51 -07:00
committed by GitHub
parent 28cab5a606 b20d020bea
commit a20915caa7
1 changed files with 6 additions and 2 deletions
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8
src/pipecat/audio/turn/smart_turn/local_smart_turn_v2.py
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@@ -62,8 +62,12 @@ class LocalSmartTurnAnalyzerV2(BaseSmartTurn):
self._turn_model = _Wav2Vec2ForEndpointing.from_pretrained(smart_turn_model_path) self._turn_model = _Wav2Vec2ForEndpointing.from_pretrained(smart_turn_model_path)
# Load the corresponding feature extractor for preprocessing audio # Load the corresponding feature extractor for preprocessing audio
self._turn_processor = Wav2Vec2Processor.from_pretrained(smart_turn_model_path) self._turn_processor = Wav2Vec2Processor.from_pretrained(smart_turn_model_path)
# Set device to GPU if available, else CPU # Use platform-optimized backend if available (MPS for Apple silicon, CUDA for NVIDIA)
self._device = torch.device("cuda" if torch.cuda.is_available() else "cpu") self._device = "cpu"
if torch.backends.mps.is_available():
self._device = "mps"
elif torch.cuda.is_available():
self._device = "cuda"
# Move model to selected device and set it to evaluation mode # Move model to selected device and set it to evaluation mode
self._turn_model = self._turn_model.to(self._device) self._turn_model = self._turn_model.to(self._device)
self._turn_model.eval() self._turn_model.eval()