Merge pull request #13 from mobiusml/fw_compliance

making default vad_device same as asr model device

faster_whisper/transcribe.py

@@ -137,7 +137,7 @@ def __init__(
         options: Optional[NamedTuple] = None,
         tokenizer=None,
         device: Union[int, str, "torch.device"] = -1,
-        vad_device: Union[int, str, "torch.device"] = "cuda",
+        vad_device: Union[int, str, "torch.device"] = "auto",
         framework="pt",
         language: Optional[str] = None,
         **kwargs,
@@ -168,7 +168,6 @@ def __init__(
             self.device = device
 
         if self.use_vad_model:
-            # Separate vad_device from pipeline self.device
             self.vad_device = self.get_device(vad_device)
 
             # load vad model and perform VAD preprocessing if needed
@@ -185,10 +184,24 @@ def _sanitize_parameters(self, **kwargs):
             preprocess_kwargs["maybe_arg"] = kwargs["maybe_arg"]
         return preprocess_kwargs, {}, {}
 
-    def get_device(self, device):
+    def get_device(self, device: Union[int, str, "torch.device"]):
+        """
+        Converts the input device into a torch.device object.
+
+        The input can be an integer, a string, or a `torch.device` object.
+
+        The function handles a special case where the input device is "auto".
+        When "auto" is specified, the device will default to the
+        device of the model (self.model.device). If the model's device is also "auto",
+        it selects "cuda" if a CUDA-capable device is available; otherwise, it selects "cpu".
+        """
         if isinstance(device, torch.device):
             return device
         elif isinstance(device, str):
+            if device == "auto" and self.model.device == "auto":
+                device = "cuda" if torch.cuda.is_available() else "cpu"
+            elif device == "auto":
+                device = self.model.device
             return torch.device(device)
         elif device < 0:
             return torch.device("cpu")
@@ -683,12 +696,12 @@ def __init__(
                 local_files_only=local_files_only,
                 cache_dir=download_root,
             )
-
+        self.device = device
         # set the random seed to make sure consistency across runs
         ctranslate2.set_random_seed(42)
         self.model = ctranslate2.models.Whisper(
             model_path,
-            device=device,
+            device=self.device,
             device_index=device_index,
             compute_type=compute_type,
             intra_threads=cpu_threads,