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import torch
import json
import os
version_config_paths = [
os.path.join("v1", "32000.json"),
os.path.join("v1", "40000.json"),
os.path.join("v1", "48000.json"),
os.path.join("v2", "48000.json"),
os.path.join("v2", "40000.json"),
os.path.join("v2", "32000.json"),
]
def singleton(cls):
instances = {}
def get_instance(*args, **kwargs):
if cls not in instances:
instances[cls] = cls(*args, **kwargs)
return instances[cls]
return get_instance
@singleton
class Config:
def __init__(self):
self.device = "cuda:0" if torch.cuda.is_available() else "cpu"
self.is_half = self.device != "cpu"
self.gpu_name = (
torch.cuda.get_device_name(int(self.device.split(":")[-1]))
if self.device.startswith("cuda")
else None
)
self.gpu_mem = None
self.x_pad, self.x_query, self.x_center, self.x_max = self.device_config()
def has_mps(self) -> bool:
# Check if Metal Performance Shaders are available - for macOS 12.3+.
return torch.backends.mps.is_available()
def set_precision(self, precision):
if precision not in ["fp32", "fp16"]:
raise ValueError("Invalid precision type. Must be 'fp32' or 'fp16'.")
fp16_run_value = precision == "fp16"
preprocess_target_version = "3.7" if precision == "fp16" else "3.0"
preprocess_path = os.path.join(
os.path.dirname(__file__),
os.pardir,
"rvc",
"train",
"preprocess",
"preprocess.py",
)
for config_path in version_config_paths:
full_config_path = os.path.join("rvc", "configs", config_path)
try:
with open(full_config_path, "r") as f:
config = json.load(f)
config["train"]["fp16_run"] = fp16_run_value
with open(full_config_path, "w") as f:
json.dump(config, f, indent=4)
except FileNotFoundError:
print(f"File not found: {full_config_path}")
if os.path.exists(preprocess_path):
with open(preprocess_path, "r") as f:
preprocess_content = f.read()
preprocess_content = preprocess_content.replace(
"3.0" if precision == "fp16" else "3.7", preprocess_target_version
)
with open(preprocess_path, "w") as f:
f.write(preprocess_content)
return f"Overwritten preprocess and config.json to use {precision}."
def device_config(self) -> tuple:
if self.device.startswith("cuda"):
self.set_cuda_config()
elif self.has_mps():
self.device = "mps"
self.is_half = False
self.set_precision("fp32")
else:
self.device = "cpu"
self.is_half = False
self.set_precision("fp32")
# Configuration for 6GB GPU memory
x_pad, x_query, x_center, x_max = (
(3, 10, 60, 65) if self.is_half else (1, 6, 38, 41)
)
if self.gpu_mem is not None and self.gpu_mem <= 4:
# Configuration for 5GB GPU memory
x_pad, x_query, x_center, x_max = (1, 5, 30, 32)
return x_pad, x_query, x_center, x_max
def set_cuda_config(self):
i_device = int(self.device.split(":")[-1])
self.gpu_name = torch.cuda.get_device_name(i_device)
low_end_gpus = ["16", "P40", "P10", "1060", "1070", "1080"]
if (
any(gpu in self.gpu_name for gpu in low_end_gpus)
and "V100" not in self.gpu_name.upper()
):
self.is_half = False
self.set_precision("fp32")
self.gpu_mem = torch.cuda.get_device_properties(i_device).total_memory // (
1024**3
)
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