OPENGIT/Retrieval-based-Voice-Conversion-WebUI
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add timestamp and epoch elapsed time

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Xerxes-2 2023-05-12 21:11:34 +10:00
parent ef016ae6a0
commit 93b8d4a7af
1 changed files with 14 additions and 1 deletions
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15
train_nsf_sim_cache_sid_load_pretrain.py
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@ -41,6 +41,18 @@ from mel_processing import mel_spectrogram_torch, spec_to_mel_torch
global_step = 0 global_step = 0
import datetime
class EpochRecorder:
def __init__(self):
self.last_time = ttime()
def record(self):
now_time = ttime()
elapsed_time = now_time - self.last_time
hr_and_min: str = str(datetime.timedelta(seconds=elapsed_time))
current_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
return f"[{current_time}] | ({hr_and_min})"
def main(): def main():
# n_gpus = torch.cuda.device_count() # n_gpus = torch.cuda.device_count()
@ -314,6 +326,7 @@ def train_and_evaluate(
data_iterator = enumerate(train_loader) data_iterator = enumerate(train_loader)
# Run steps # Run steps
epoch_recorder = EpochRecorder()
for batch_idx, info in data_iterator: for batch_idx, info in data_iterator:
# Data # Data
## Unpack ## Unpack
@ -513,7 +526,7 @@ def train_and_evaluate(
) )
if rank == 0: if rank == 0:
logger.info("====> Epoch: {}".format(epoch)) logger.info("====> Epoch: {} {}".format(epoch, epoch_recorder.record()))
if epoch >= hps.total_epoch and rank == 0: if epoch >= hps.total_epoch and rank == 0:
logger.info("Training is done. The program is closed.") logger.info("Training is done. The program is closed.")
from process_ckpt import savee # def savee(ckpt,sr,if_f0,name,epoch): from process_ckpt import savee # def savee(ckpt,sr,if_f0,name,epoch):