fix: remove outdated codes & add weights_only=True

infer/lib/rvcmd.py

@@ -198,44 +198,10 @@ def download_all_assets(tmpdir: str, version="0.2.5"):
     suffix = "zip" if is_win else "tar.gz"
     RVCMD_URL = BASE_URL + f"v{version}/rvcmd_{system_type}_{architecture}.{suffix}"
     cmdfile = os.path.join(tmpdir, "rvcmd")
-    try:
-        if is_win:
-            download_and_extract_zip(RVCMD_URL, tmpdir)
-            cmdfile += ".exe"
-        else:
-            download_and_extract_tar_gz(RVCMD_URL, tmpdir)
-            os.chmod(cmdfile, 0o755)
-        subprocess.run([cmdfile, "-notui", "-w", "0", "assets/rvc"])
-    except Exception:
-        BASE_URL = "https://raw.gitcode.com/u011570312/RVC-Models-Downloader/assets/"
-        suffix = {
-            "darwin_amd64": "555",
-            "darwin_arm64": "556",
-            "linux_386": "557",
-            "linux_amd64": "558",
-            "linux_arm64": "559",
-            "windows_386": "562",
-            "windows_amd64": "563",
-        }[f"{system_type}_{architecture}"]
-        RVCMD_URL = BASE_URL + suffix
-        download_dns_yaml(
-            "https://raw.gitcode.com/u011570312/RVC-Models-Downloader/raw/main/dns.yaml",
-            tmpdir,
-        )
-        if is_win:
-            download_and_extract_zip(RVCMD_URL, tmpdir)
-            cmdfile += ".exe"
-        else:
-            download_and_extract_tar_gz(RVCMD_URL, tmpdir)
-            os.chmod(cmdfile, 0o755)
-        subprocess.run(
-            [
-                cmdfile,
-                "-notui",
-                "-w",
-                "0",
-                "-dns",
-                os.path.join(tmpdir, "dns.yaml"),
-                "assets/rvc",
-            ]
-        )
+    if is_win:
+        download_and_extract_zip(RVCMD_URL, tmpdir)
+        cmdfile += ".exe"
+    else:
+        download_and_extract_tar_gz(RVCMD_URL, tmpdir)
+        os.chmod(cmdfile, 0o755)
+    subprocess.run([cmdfile, "-notui", "-w", "0", "assets/rvc"])

infer/lib/train/data_utils.py

@@ -303,7 +303,7 @@ class TextAudioLoader(torch.utils.data.Dataset):
         spec_filename = filename.replace(".wav", ".spec.pt")
         if os.path.exists(spec_filename):
             try:
-                spec = torch.load(spec_filename)
+                spec = torch.load(spec_filename, weights_only=True)
             except:
                 logger.warning("%s %s", spec_filename, traceback.format_exc())
                 spec = spectrogram_torch(

infer/lib/train/process_ckpt.py

@@ -59,7 +59,7 @@ def save_small_model(ckpt, sr, if_f0, name, epoch, version, hps):
 
 def extract_small_model(path, name, author, sr, if_f0, info, version):
     try:
-        ckpt = torch.load(path, map_location="cpu")
+        ckpt = torch.load(path, map_location="cpu", weights_only=True)
         if "model" in ckpt:
             ckpt = ckpt["model"]
         opt = OrderedDict()
@@ -196,7 +196,7 @@ def extract_small_model(path, name, author, sr, if_f0, info, version):
 
 def change_info(path, info, name):
     try:
-        ckpt = torch.load(path, map_location="cpu")
+        ckpt = torch.load(path, map_location="cpu", weights_only=True)
         ckpt["info"] = info
         if name == "":
             name = os.path.basename(path)
@@ -229,8 +229,8 @@ def merge(path1, path2, alpha1, sr, f0, info, name, version):
                 a2 = "Unknown"
             return f"{a1} & {a2}"
 
-        ckpt1 = torch.load(path1, map_location="cpu")
-        ckpt2 = torch.load(path2, map_location="cpu")
+        ckpt1 = torch.load(path1, map_location="cpu", weights_only=True)
+        ckpt2 = torch.load(path2, map_location="cpu", weights_only=True)
         cfg = ckpt1["config"]
         if "model" in ckpt1:
             ckpt1 = extract(ckpt1)

infer/modules/uvr5/vr.py

@@ -37,7 +37,7 @@ class AudioPre:
         else:
             mp = ModelParameters("infer/lib/uvr5_pack/lib_v5/modelparams/4band_v2.json")
             model = Nets.CascadedASPPNet(mp.param["bins"] * 2)
-        cpk = torch.load(model_path, map_location="cpu")
+        cpk = torch.load(model_path, map_location="cpu", weights_only=True)
         model.load_state_dict(cpk)
         model.eval()
         if is_half:

infer/modules/vc/hash.py

@@ -152,7 +152,7 @@ def model_hash_ckpt(cpt):
 
 
 def model_hash_from(path):
-    cpt = torch.load(path, map_location="cpu")
+    cpt = torch.load(path, map_location="cpu", weights_only=True)
     h = model_hash_ckpt(cpt)
     del cpt
     return h

infer/modules/vc/info.py

@@ -75,7 +75,7 @@ def show_info(path):
     try:
         if hasattr(path, "name"):
             path = path.name
-        a = torch.load(path, map_location="cpu")
+        a = torch.load(path, map_location="cpu", weights_only=True)
         txt = show_model_info(a, show_long_id=True)
         del a
     except: