fixes #112 : add support for intel arc gpus

whisper_timestamped/transcribe.py

@@ -15,6 +15,13 @@
 import torch
 import torch.nn.functional as F
 
+from importlib.util import find_spec
+if find_spec("intel_extension_for_pytorch") is not None:
+    try:
+        import intel_extension_for_pytorch
+    except ImportError:
+        pass
+
 # For alignment
 import numpy as np
 import dtw
@@ -2046,9 +2053,18 @@ def write_csv(transcript, file, sep = ",", text_first=True, format_timestamps=No
 # CUDA initialization may fail on old GPU card
 def force_cudnn_initialization(device=None, s=32):
     if device is None:
-        device = torch.device('cuda')
+        device = get_default_device()
     torch.nn.functional.conv2d(torch.zeros(s, s, s, s, device=device), torch.zeros(s, s, s, s, device=device))
 
+def get_default_device():
+    if torch.cuda.is_available():
+        device = "cuda"
+    elif find_spec('torch.xpu') is not None and torch.xpu.is_available():
+        device = "xpu"
+    else:
+        device = "cpu"
+    return device
+
 # base85-encoded (n_layers, n_heads) boolean arrays indicating the cross-attention heads that are
 # highly correlated to the word-level timing, i.e. the alignment between audio and text tokens.
 _ALIGNMENT_HEADS = {
@@ -2242,7 +2258,7 @@ def get_do_write(output_format):
     parser.add_argument('audio', help="audio file(s) to transcribe", nargs='+')
     parser.add_argument('--model', help=f"name of the Whisper model to use. Examples: {', '.join(whisper.available_models())}", default="small")
     parser.add_argument("--model_dir", default=None, help="the path to save model files; uses ~/.cache/whisper by default", type=str)
-    parser.add_argument("--device", default="cuda:0" if torch.cuda.is_available() else "cpu", help="device to use for PyTorch inference")
+    parser.add_argument("--device", default=get_default_device(), help="device to use for PyTorch inference")
     parser.add_argument("--output_dir", "-o", default=None, help="directory to save the outputs", type=str)
     valid_formats = ["txt", "vtt", "srt", "tsv", "csv", "json"]
     def str2output_formats(string):