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github-actions[bot]
2023-09-08 16:13:28 +00:00
parent 1f3ee63a74
commit cfbb2fd8c9
1 changed files with 18 additions and 8 deletions
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26
train_ms.py
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@@ -173,20 +173,28 @@ def run():
try: try:
if net_dur_disc is not None: if net_dur_disc is not None:
_, _, dur_resume_lr, epoch_str = utils.load_checkpoint( _, _, dur_resume_lr, epoch_str = utils.load_checkpoint(
utils.latest_checkpoint_path(hps.model_dir, "DUR_*.pth"), net_dur_disc, optim_dur_disc, utils.latest_checkpoint_path(hps.model_dir, "DUR_*.pth"),
skip_optimizer=True) net_dur_disc,
optim_dur_disc,
skip_optimizer=True,
)
_, optim_g, g_resume_lr, epoch_str = utils.load_checkpoint( _, optim_g, g_resume_lr, epoch_str = utils.load_checkpoint(
utils.latest_checkpoint_path(hps.model_dir, "G_*.pth"), net_g, utils.latest_checkpoint_path(hps.model_dir, "G_*.pth"),
optim_g, skip_optimizer=True) net_g,
optim_g,
skip_optimizer=True,
)
_, optim_d, d_resume_lr, epoch_str = utils.load_checkpoint( _, optim_d, d_resume_lr, epoch_str = utils.load_checkpoint(
utils.latest_checkpoint_path(hps.model_dir, "D_*.pth"), net_d, utils.latest_checkpoint_path(hps.model_dir, "D_*.pth"),
optim_d, skip_optimizer=True) net_d,
optim_d,
skip_optimizer=True,
)
if not optim_g.param_groups[0].get("initial_lr"): if not optim_g.param_groups[0].get("initial_lr"):
optim_g.param_groups[0]["initial_lr"] = g_resume_lr optim_g.param_groups[0]["initial_lr"] = g_resume_lr
if not optim_d.param_groups[0].get("initial_lr"): if not optim_d.param_groups[0].get("initial_lr"):
optim_d.param_groups[0]["initial_lr"] = d_resume_lr optim_d.param_groups[0]["initial_lr"] = d_resume_lr
epoch_str = max(epoch_str, 1) epoch_str = max(epoch_str, 1)
global_step = (epoch_str - 1) * len(train_loader) global_step = (epoch_str - 1) * len(train_loader)
except Exception as e: except Exception as e:
@@ -203,7 +211,9 @@ def run():
if net_dur_disc is not None: if net_dur_disc is not None:
if not optim_dur_disc.param_groups[0].get("initial_lr"): if not optim_dur_disc.param_groups[0].get("initial_lr"):
optim_dur_disc.param_groups[0]["initial_lr"] = dur_resume_lr optim_dur_disc.param_groups[0]["initial_lr"] = dur_resume_lr
scheduler_dur_disc = torch.optim.lr_scheduler.ExponentialLR(optim_dur_disc, gamma=hps.train.lr_decay, last_epoch=epoch_str-2) scheduler_dur_disc = torch.optim.lr_scheduler.ExponentialLR(
optim_dur_disc, gamma=hps.train.lr_decay, last_epoch=epoch_str - 2
)
else: else:
scheduler_dur_disc = None scheduler_dur_disc = None
scaler = GradScaler(enabled=hps.train.fp16_run) scaler = GradScaler(enabled=hps.train.fp16_run)