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This commit is contained in:
litagin02
2024-03-11 09:47:47 +09:00
parent 42ee7d7608
commit c776c08235
31 changed files with 463 additions and 298 deletions
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66
train_ms_jp_extra.py
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@@ -288,28 +288,28 @@ def run():
mas_noise_scale_initial=mas_noise_scale_initial,
noise_scale_delta=noise_scale_delta,
# hps.model 以下のすべての値を引数に渡す
use_spk_conditioned_encoder = hps.model.use_spk_conditioned_encoder,
use_noise_scaled_mas = hps.model.use_noise_scaled_mas,
use_mel_posterior_encoder = hps.model.use_mel_posterior_encoder,
use_duration_discriminator = hps.model.use_duration_discriminator,
use_wavlm_discriminator = hps.model.use_wavlm_discriminator,
inter_channels = hps.model.inter_channels,
hidden_channels = hps.model.hidden_channels,
filter_channels = hps.model.filter_channels,
n_heads = hps.model.n_heads,
n_layers = hps.model.n_layers,
kernel_size = hps.model.kernel_size,
p_dropout = hps.model.p_dropout,
resblock = hps.model.resblock,
resblock_kernel_sizes = hps.model.resblock_kernel_sizes,
resblock_dilation_sizes = hps.model.resblock_dilation_sizes,
upsample_rates = hps.model.upsample_rates,
upsample_initial_channel = hps.model.upsample_initial_channel,
upsample_kernel_sizes = hps.model.upsample_kernel_sizes,
n_layers_q = hps.model.n_layers_q,
use_spectral_norm = hps.model.use_spectral_norm,
gin_channels = hps.model.gin_channels,
slm = hps.model.slm,
use_spk_conditioned_encoder=hps.model.use_spk_conditioned_encoder,
use_noise_scaled_mas=hps.model.use_noise_scaled_mas,
use_mel_posterior_encoder=hps.model.use_mel_posterior_encoder,
use_duration_discriminator=hps.model.use_duration_discriminator,
use_wavlm_discriminator=hps.model.use_wavlm_discriminator,
inter_channels=hps.model.inter_channels,
hidden_channels=hps.model.hidden_channels,
filter_channels=hps.model.filter_channels,
n_heads=hps.model.n_heads,
n_layers=hps.model.n_layers,
kernel_size=hps.model.kernel_size,
p_dropout=hps.model.p_dropout,
resblock=hps.model.resblock,
resblock_kernel_sizes=hps.model.resblock_kernel_sizes,
resblock_dilation_sizes=hps.model.resblock_dilation_sizes,
upsample_rates=hps.model.upsample_rates,
upsample_initial_channel=hps.model.upsample_initial_channel,
upsample_kernel_sizes=hps.model.upsample_kernel_sizes,
n_layers_q=hps.model.n_layers_q,
use_spectral_norm=hps.model.use_spectral_norm,
gin_channels=hps.model.gin_channels,
slm=hps.model.slm,
).cuda(local_rank)
if getattr(hps.train, "freeze_JP_bert", False):
logger.info("Freezing (JP) bert encoder !!!")
@@ -383,7 +383,9 @@ def run():
if net_dur_disc is not None:
try:
_, _, dur_resume_lr, epoch_str = utils.checkpoints.load_checkpoint(
utils.checkpoints.get_latest_checkpoint_path(model_dir, "DUR_*.pth"),
utils.checkpoints.get_latest_checkpoint_path(
model_dir, "DUR_*.pth"
),
net_dur_disc,
optim_dur_disc,
skip_optimizer=hps.train.skip_optimizer,
@@ -396,11 +398,15 @@ def run():
print("Initialize dur_disc")
if net_wd is not None:
try:
_, optim_wd, wd_resume_lr, epoch_str = utils.checkpoints.load_checkpoint(
utils.checkpoints.get_latest_checkpoint_path(model_dir, "WD_*.pth"),
net_wd,
optim_wd,
skip_optimizer=hps.train.skip_optimizer,
_, optim_wd, wd_resume_lr, epoch_str = (
utils.checkpoints.load_checkpoint(
utils.checkpoints.get_latest_checkpoint_path(
model_dir, "WD_*.pth"
),
net_wd,
optim_wd,
skip_optimizer=hps.train.skip_optimizer,
)
)
if not optim_wd.param_groups[0].get("initial_lr"):
optim_wd.param_groups[0]["initial_lr"] = wd_resume_lr
@@ -430,7 +436,9 @@ def run():
epoch_str = max(epoch_str, 1)
# global_step = (epoch_str - 1) * len(train_loader)
global_step = int(
utils.get_steps(utils.checkpoints.get_latest_checkpoint_path(model_dir, "G_*.pth"))
utils.get_steps(
utils.checkpoints.get_latest_checkpoint_path(model_dir, "G_*.pth")
)
)
logger.info(
f"******************Found the model. Current epoch is {epoch_str}, gloabl step is {global_step}*********************"