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config.py

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+########################硬件参数########################
+
+# 填写cuda:x, cpu 或 mps, x指代第几张卡，只支持 N卡 / Apple Silicon 加速
+device = "cuda:0"
+
+# 9-10-20-30-40系显卡无脑True，不影响质量，>=20显卡开启有加速
+is_half = True
+
+# 默认0用上所有线程，写数字限制CPU资源使用
+n_cpu = 0
+
+########################硬件参数########################
+
+
+##################下为参数处理逻辑，勿动##################
+
+########################命令行参数########################
+import argparse
+
+parser = argparse.ArgumentParser()
+parser.add_argument("--port", type=int, default=7865, help="Listen port")
+parser.add_argument("--pycmd", type=str, default="python", help="Python command")
+parser.add_argument("--colab", action="store_true", help="Launch in colab")
+parser.add_argument(
+    "--noparallel", action="store_true", help="Disable parallel processing"
+)
+parser.add_argument(
+    "--noautoopen", action="store_true", help="Do not open in browser automatically"
+)
+cmd_opts = parser.parse_args()
+
+python_cmd = cmd_opts.pycmd
+listen_port = cmd_opts.port if 0 <= cmd_opts.port <= 65535 else 7865
+iscolab = cmd_opts.colab
+noparallel = cmd_opts.noparallel
+noautoopen = cmd_opts.noautoopen
+########################命令行参数########################
+
+import sys
+import torch
+
+
+# has_mps is only available in nightly pytorch (for now) and MasOS 12.3+.
+# check `getattr` and try it for compatibility
+def has_mps() -> bool:
+    if sys.platform != "darwin":
+        return False
+    else:
+        if not getattr(torch, "has_mps", False):
+            return False
+        try:
+            torch.zeros(1).to(torch.device("mps"))
+            return True
+        except Exception:
+            return False
+
+
+if not torch.cuda.is_available():
+    if has_mps():
+        print("没有发现支持的N卡, 使用MPS进行推理")
+        device = "mps"
+    else:
+        print("没有发现支持的N卡, 使用CPU进行推理")
+        device = "cpu"
+        is_half = False
+
+gpu_mem=None
+if device not in ["cpu", "mps"]:
+    i_device=int(device.split(":")[-1])
+    gpu_name = torch.cuda.get_device_name(i_device)
+    if "16" in gpu_name or "P40"in gpu_name.upper() or "1070"in gpu_name or "1080"in gpu_name:
+        print("16系显卡强制单精度")
+        is_half = False
+        with open("configs/32k.json","r")as f:strr=f.read().replace("true","false")
+        with open("configs/32k.json","w")as f:f.write(strr)
+        with open("configs/40k.json","r")as f:strr=f.read().replace("true","false")
+        with open("configs/40k.json","w")as f:f.write(strr)
+        with open("configs/48k.json","r")as f:strr=f.read().replace("true","false")
+        with open("configs/48k.json","w")as f:f.write(strr)
+        with open("trainset_preprocess_pipeline_print.py","r")as f:strr=f.read().replace("3.7","3.0")
+        with open("trainset_preprocess_pipeline_print.py","w")as f:f.write(strr)
+    gpu_mem=int(torch.cuda.get_device_properties(i_device).total_memory/1024/1024/1024+0.4)
+    if(gpu_mem<=4):
+        with open("trainset_preprocess_pipeline_print.py","r")as f:strr=f.read().replace("3.7","3.0")
+        with open("trainset_preprocess_pipeline_print.py","w")as f:f.write(strr)
+from multiprocessing import cpu_count
+
+if n_cpu == 0:
+    n_cpu = cpu_count()
+if is_half:
+    # 6G显存配置
+    x_pad = 3
+    x_query = 10
+    x_center = 60
+    x_max = 65
+else:
+    # 5G显存配置
+    x_pad = 1
+    x_query = 6
+    x_center = 38
+    x_max = 41
+if(gpu_mem!=None and gpu_mem<=4):
+    x_pad = 1
+    x_query = 5
+    x_center = 30
+    x_max = 32

hubert_base.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f54b40fd2802423a5643779c4861af1e9ee9c1564dc9d32f54f20b5ffba7db96
+size 189507909

rmvpe.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6d62215f4306e3ca278246188607209f09af3dc77ed4232efdd069798c4ec193
+size 181184272