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RVC-Boss 2023-10-10 17:10:18 +08:00 committed by GitHub
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@ -23,16 +23,14 @@ try:
if torch.xpu.is_available():
from infer.modules.ipex import ipex_init
ipex_init()
from torch.xpu.amp import autocast
from infer.modules.ipex.gradscaler import gradscaler_init
from torch.xpu.amp import autocast
GradScaler = gradscaler_init()
ipex_init()
else:
from torch.cuda.amp import GradScaler, autocast
except Exception: # pylint: disable=broad-exception-caught
except Exception:
from torch.cuda.amp import GradScaler, autocast
torch.backends.cudnn.deterministic = False
@ -106,11 +104,10 @@ def main():
os.environ["MASTER_ADDR"] = "localhost"
os.environ["MASTER_PORT"] = str(randint(20000, 55555))
children = []
logger = utils.get_logger(hps.model_dir)
for i in range(n_gpus):
subproc = mp.Process(
target=run,
args=(i, n_gpus, hps, logger),
args=(i, n_gpus, hps),
)
children.append(subproc)
subproc.start()
@ -119,10 +116,10 @@ def main():
children[i].join()
def run(rank, n_gpus, hps, logger: logging.Logger):
def run(rank, n_gpus, hps,):
global global_step
if rank == 0:
# logger = utils.get_logger(hps.model_dir)
logger = utils.get_logger(hps.model_dir)
logger.info(hps)
# utils.check_git_hash(hps.model_dir)
writer = SummaryWriter(log_dir=hps.model_dir)