jshiffer/Retrieval-based-Voice-Conversion
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Optimization of conditional branching

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This commit is contained in:
Ftps
2023-11-17 18:22:33 +09:00
parent 6d3d30aa64
commit a8fbbdad18
1 changed files with 19 additions and 72 deletions
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91
rvc/configs/config.py
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@@ -49,7 +49,6 @@ class Config:
self.noautoopen, self.noautoopen,
self.dml, self.dml,
) = self.arg_parse() ) = self.arg_parse()
self.instead = ""
self.x_pad, self.x_query, self.x_center, self.x_max = self.device_config() self.x_pad, self.x_query, self.x_center, self.x_max = self.device_config()
@staticmethod @staticmethod
@@ -144,92 +143,40 @@ class Config:
/ 1024 / 1024
+ 0.4 + 0.4
) )
if self.gpu_mem <= 4:
with open("infer/modules/train/preprocess.py", "r") as f:
strr = f.read().replace("3.7", "3.0")
with open("infer/modules/train/preprocess.py", "w") as f:
f.write(strr)
elif self.has_mps(): elif self.has_mps():
logger.info("No supported Nvidia GPU found") logger.info("No supported Nvidia GPU found")
self.device = self.instead = "mps" self.device = self.instead = "mps"
self.is_half = False self.is_half = False
self.use_fp32_config() self.use_fp32_config()
elif self.dml:
import torch_directml
self.device = torch_directml.device(torch_directml.default_device())
self.is_half = False
else: else:
logger.info("No supported Nvidia GPU found") logger.info("No supported Nvidia GPU found")
self.device = self.instead = "cpu" self.device = self.instead = "cpu"
self.is_half = False self.is_half = False
self.use_fp32_config() self.use_fp32_config()
if self.n_cpu == 0:
self.n_cpu = cpu_count()
if self.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 self.gpu_mem is not None and self.gpu_mem <= 4: if self.gpu_mem is not None and self.gpu_mem <= 4:
x_pad = 1 x_pad = 1
x_query = 5 x_query = 5
x_center = 30 x_center = 30
x_max = 32 x_max = 32
if self.dml: elif self.is_half:
logger.info("Use DirectML instead") # 6G PU_RAM conf
if ( x_pad = 3
os.path.exists( x_query = 10
"runtime\Lib\site-packages\onnxruntime\capi\DirectML.dll" x_center = 60
) x_max = 65
== False
):
try:
os.rename(
"runtime\Lib\site-packages\onnxruntime",
"runtime\Lib\site-packages\onnxruntime-cuda",
)
except:
pass
try:
os.rename(
"runtime\Lib\site-packages\onnxruntime-dml",
"runtime\Lib\site-packages\onnxruntime",
)
except:
pass
# if self.device != "cpu":
import torch_directml
self.device = torch_directml.device(torch_directml.default_device())
self.is_half = False
else: else:
if self.instead: # 5G GPU_RAM conf
logger.info(f"Use {self.instead} instead") x_pad = 1
if ( x_query = 6
os.path.exists( x_center = 38
"runtime\Lib\site-packages\onnxruntime\capi\onnxruntime_providers_cuda.dll" x_max = 41
)
== False logger.info(f"Use {self.dml or self.instead} instead")
): logger.info(f"is_half:{self.is_half}, device:{self.device}")
try:
os.rename(
"runtime\Lib\site-packages\onnxruntime",
"runtime\Lib\site-packages\onnxruntime-dml",
)
except:
pass
try:
os.rename(
"runtime\Lib\site-packages\onnxruntime-cuda",
"runtie\Lib\site-packages\onnxruntime",
)
except:
pass
print("is_half:%s, device:%s" % (self.is_half, self.device))
return x_pad, x_query, x_center, x_max return x_pad, x_query, x_center, x_max