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skip weight decay for BN and biases, some formatting

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Eren Golge
2019-09-28 01:09:28 +02:00
parent 53d658fb74
commit b76aaf8ad4
2 changed files with 72 additions and 45 deletions
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train.py
+6 -4
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@@ -20,7 +20,8 @@ from TTS.utils.generic_utils import (NoamLR, check_update, count_parameters,
load_config, remove_experiment_folder,
save_best_model, save_checkpoint, weight_decay,
set_init_dict, copy_config_file, setup_model,
split_dataset, gradual_training_scheduler, KeepAverage)
split_dataset, gradual_training_scheduler, KeepAverage,
set_weight_decay)
from TTS.utils.logger import Logger
from TTS.utils.speakers import load_speaker_mapping, save_speaker_mapping, \
get_speakers
@@ -186,7 +187,7 @@ def train(model, criterion, criterion_st, optimizer, optimizer_st, scheduler,
loss += stop_loss
loss.backward()
optimizer, current_lr = weight_decay(optimizer, c.wd)
optimizer, current_lr = weight_decay(optimizer)
grad_norm, _ = check_update(model, c.grad_clip)
optimizer.step()
@@ -197,7 +198,7 @@ def train(model, criterion, criterion_st, optimizer, optimizer_st, scheduler,
# backpass and check the grad norm for stop loss
if c.separate_stopnet:
stop_loss.backward()
optimizer_st, _ = weight_decay(optimizer_st, c.wd)
optimizer_st, _ = weight_decay(optimizer_st)
grad_norm_st, _ = check_update(model.decoder.stopnet, 1.0)
optimizer_st.step()
else:
@@ -511,7 +512,8 @@ def main(args): # pylint: disable=redefined-outer-name
print(" | > Num output units : {}".format(ap.num_freq), flush=True)
optimizer = RAdam(model.parameters(), lr=c.lr, weight_decay=0)
params = set_weight_decay(model, c.wd)
optimizer = RAdam(params, lr=c.lr, weight_decay=0)
if c.stopnet and c.separate_stopnet:
optimizer_st = RAdam(
model.decoder.stopnet.parameters(), lr=c.lr, weight_decay=0)