Support MPS on Apple Silicon (#132)

See https://pytorch.org/docs/stable/notes/mps.html

Testing this with one image using a Mac Studio (M1 Max) the processing time decreased from ~21 minutes to ~2 minutes.

I'm not sure if the change in `utils.py` is necessary, nor if there should be changes in other places - it looks like the report in `infer.py` should be updated if this is accepted.

Also updated `.gitignore` for more Mac (and PyCharm) friendliness.

.gitignore

@@ -167,4 +167,7 @@ cython_debug/
 #  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
-#.idea/
+.idea/
+
+# Extras
+.DS_Store

wsinfer/_modellib/run_inference.py

@@ -327,9 +327,16 @@ def run_inference(
     model = weights.load_model()
     model.eval()
 
-    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-    if torch.cuda.device_count() > 1:
-        model = torch.nn.DataParallel(model)
+    if torch.cuda.is_available():
+        device = torch.device("cuda")
+        if torch.cuda.device_count() > 1:
+            model = torch.nn.DataParallel(model)
+    elif torch.backends.mps.is_available() and torch.backends.mps.is_built():
+        device = torch.device("mps")
+    else:
+        device = torch.device("cpu")
+    print(f'Using device "{device}"')
+
     model.to(device)
 
     if speedup:

wsinfer/_patchlib/utils/utils.py

@@ -14,8 +14,12 @@
 import math
 import collections
 
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-
+if torch.cuda.is_available():
+    device = torch.device("cuda")
+elif torch.backends.mps.is_available() and torch.backends.mps.is_built():
+    device = torch.device("mps")
+else:
+    device = torch.device("cpu")
 
 class SubsetSequentialSampler(Sampler):
     """Samples elements sequentially from a given list of indices, without replacement.