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best model ever changes

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This commit is contained in:
Eren Golge
2018-03-07 06:58:51 -08:00
parent 405fbc434e
commit b4032e8dff
6 changed files with 80 additions and 79 deletions
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train.py
+11 -9
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@@ -199,7 +199,7 @@ def evaluate(model, criterion, data_loader, current_step):
model = model.train()
epoch_time = 0
print("\n | > Validation")
print(" | > Validation")
n_priority_freq = int(3000 / (c.sample_rate * 0.5) * c.num_freq)
progbar = Progbar(len(data_loader.dataset) / c.batch_size)
@@ -246,10 +246,10 @@ def evaluate(model, criterion, data_loader, current_step):
('mel_loss', mel_loss.data[0])])
avg_linear_loss += linear_loss.data[0]
avg_mel_loss += avg_mel_loss.data[0]
avg_mel_loss += mel_loss.data[0]
# Diagnostic visualizations
idx = np.random.randint(c.batch_size)
idx = np.random.randint(mel_input.shape[0])
const_spec = linear_output[idx].data.cpu().numpy()
gt_spec = linear_spec_var[idx].data.cpu().numpy()
align_img = alignments[idx].data.cpu().numpy()
@@ -270,7 +270,7 @@ def evaluate(model, criterion, data_loader, current_step):
tb.add_audio('ValSampleAudio', audio_signal, current_step,
sample_rate=c.sample_rate)
except:
print("\n > Error at audio signal on TB!!")
print(" | > Error at audio signal on TB!!")
print(audio_signal.max())
print(audio_signal.min())
@@ -305,8 +305,8 @@ def main(args):
)
train_loader = DataLoader(train_dataset, batch_size=c.batch_size,
shuffle=True, collate_fn=train_dataset.collate_fn,
drop_last=True, num_workers=c.num_loader_workers,
shuffle=False, collate_fn=train_dataset.collate_fn,
drop_last=False, num_workers=c.num_loader_workers,
pin_memory=True)
val_dataset = LJSpeechDataset(os.path.join(c.data_path, 'metadata_val.csv'),
@@ -325,15 +325,16 @@ def main(args):
)
val_loader = DataLoader(val_dataset, batch_size=c.batch_size,
shuffle=True, collate_fn=val_dataset.collate_fn,
drop_last=True, num_workers= 4,
shuffle=False, collate_fn=val_dataset.collate_fn,
drop_last=False, num_workers= 4,
pin_memory=True)
model = Tacotron(c.embedding_size,
c.hidden_size,
c.num_mels,
c.num_freq,
c.r)
c.r,
use_atten_mask=True)
optimizer = optim.Adam(model.parameters(), lr=c.lr)
@@ -352,6 +353,7 @@ def main(args):
start_epoch = 0
args.restore_step = checkpoint['step']
else:
args.restore_step = 0
print("\n > Starting a new training")
if use_cuda: