coqui-ai
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TTS
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Weight decay

pull/10/head
Eren 2018-09-18 12:56:07 +02:00
parent a165cd7bda
commit 9b29b4e281
2 changed files with 10 additions and 8 deletions

1
config.json
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@ -23,6 +23,7 @@
"batch_size": 32, "batch_size": 32,
"eval_batch_size":-1, "eval_batch_size":-1,
"r": 5, "r": 5,
"wd": 0.0001,
"griffin_lim_iters": 60, "griffin_lim_iters": 60,
"power": 1.5, "power": 1.5,

17
train.py
View File

@ -22,7 +22,6 @@ from models.tacotron import Tacotron
from layers.losses import L1LossMasked from layers.losses import L1LossMasked
from utils.audio import AudioProcessor from utils.audio import AudioProcessor
torch.manual_seed(1) torch.manual_seed(1)
# torch.set_num_threads(4) # torch.set_num_threads(4)
use_cuda = torch.cuda.is_available() use_cuda = torch.cuda.is_available()
@ -278,7 +277,7 @@ def evaluate(model, criterion, criterion_st, data_loader, ap, current_step):
tb.add_figure('ValVisual/Reconstruction', const_spec, current_step) tb.add_figure('ValVisual/Reconstruction', const_spec, current_step)
tb.add_figure('ValVisual/GroundTruth', gt_spec, current_step) tb.add_figure('ValVisual/GroundTruth', gt_spec, current_step)
tb.add_figure('ValVisual/ValidationAlignment', align_img, tb.add_figure('ValVisual/ValidationAlignment', align_img,
current_step) current_step)
# Sample audio # Sample audio
audio_signal = linear_output[idx].data.cpu().numpy() audio_signal = linear_output[idx].data.cpu().numpy()
@ -318,7 +317,8 @@ def evaluate(model, criterion, criterion_st, data_loader, ap, current_step):
file_path = os.path.join(AUDIO_PATH, str(current_step)) file_path = os.path.join(AUDIO_PATH, str(current_step))
os.makedirs(file_path, exist_ok=True) os.makedirs(file_path, exist_ok=True)
file_path = os.path.join(file_path, "TestSentence_{}.wav".format(idx)) file_path = os.path.join(file_path,
"TestSentence_{}.wav".format(idx))
ap.save_wav(wav, file_path) ap.save_wav(wav, file_path)
wav_name = 'TestSentences/{}'.format(idx) wav_name = 'TestSentences/{}'.format(idx)
@ -327,10 +327,10 @@ def evaluate(model, criterion, criterion_st, data_loader, ap, current_step):
align_img = alignments[0].data.cpu().numpy() align_img = alignments[0].data.cpu().numpy()
linear_spec = plot_spectrogram(linear_spec, ap) linear_spec = plot_spectrogram(linear_spec, ap)
align_img = plot_alignment(align_img) align_img = plot_alignment(align_img)
tb.add_figure('TestSentences/{}_Spectrogram'.format(idx), linear_spec, tb.add_figure('TestSentences/{}_Spectrogram'.format(idx),
current_step) linear_spec, current_step)
tb.add_figure('TestSentences/{}_Alignment'.format(idx), align_img, tb.add_figure('TestSentences/{}_Alignment'.format(idx), align_img,
current_step) current_step)
except: except:
print(" !! Error as creating Test Sentence -", idx) print(" !! Error as creating Test Sentence -", idx)
pass pass
@ -390,8 +390,9 @@ def main(args):
model = Tacotron(c.embedding_size, ap.num_freq, c.num_mels, c.r) model = Tacotron(c.embedding_size, ap.num_freq, c.num_mels, c.r)
print(" | > Num output units : {}".format(ap.num_freq), flush=True) print(" | > Num output units : {}".format(ap.num_freq), flush=True)
optimizer = optim.Adam(model.parameters(), lr=c.lr) optimizer = optim.Adam(model.parameters(), lr=c.lr, weight_decay=c.wd)
optimizer_st = optim.Adam(model.decoder.stopnet.parameters(), lr=c.lr) optimizer_st = optim.Adam(
model.decoder.stopnet.parameters(), lr=c.lr, weight_decay=c.wd)
criterion = L1LossMasked() criterion = L1LossMasked()
criterion_st = nn.BCELoss() criterion_st = nn.BCELoss()