support cpu training, use cpu training on mac

GPT_SoVITS/prepare_datasets/1-get-text.py

@@ -49,8 +49,8 @@ if os.path.exists(txt_path) == False:
     os.makedirs(bert_dir, exist_ok=True)
     if torch.cuda.is_available():
         device = "cuda:0"
-    elif torch.backends.mps.is_available():
-        device = "mps"
+    # elif torch.backends.mps.is_available():
+    #     device = "mps"
     else:
         device = "cpu"
     tokenizer = AutoTokenizer.from_pretrained(bert_pretrained_dir)

GPT_SoVITS/prepare_datasets/2-get-hubert-wav32k.py

@@ -50,8 +50,8 @@ maxx=0.95
 alpha=0.5
 if torch.cuda.is_available():
     device = "cuda:0"
-elif torch.backends.mps.is_available():
-    device = "mps"
+# elif torch.backends.mps.is_available():
+#     device = "mps"
 else:
     device = "cpu"
 model=cnhubert.get_model()

GPT_SoVITS/prepare_datasets/3-get-semantic.py

@@ -40,8 +40,8 @@ if os.path.exists(semantic_path) == False:
 
     if torch.cuda.is_available():
         device = "cuda"
-    elif torch.backends.mps.is_available():
-        device = "mps"
+    # elif torch.backends.mps.is_available():
+    #     device = "mps"
     else:
         device = "cpu"
     hps = utils.get_hparams_from_file(s2config_path)