bug fix: plot linear spec if tacotron is the model

This commit is contained in:
Eren Golge
2019-03-12 10:46:48 +01:00
parent 4f89029577
commit abc7b8e366
+2 -2
View File
@@ -187,7 +187,7 @@ def train(model, criterion, criterion_st, optimizer, optimizer_st, scheduler,
# Diagnostic visualizations
const_spec = postnet_output[0].data.cpu().numpy()
gt_spec = mel_input[0].data.cpu().numpy()
gt_spec = linear_input[0].data.cpu().numpy() if c.model == "Tacotron" else mel_input[0].data.cpu().numpy()
align_img = alignments[0].data.cpu().numpy()
figures = {
@@ -315,7 +315,7 @@ def evaluate(model, criterion, criterion_st, ap, current_step, epoch):
# Diagnostic visualizations
idx = np.random.randint(mel_input.shape[0])
const_spec = postnet_output[idx].data.cpu().numpy()
gt_spec = mel_input[idx].data.cpu().numpy()
gt_spec = linear_input[idx].data.cpu().numpy() if c.model == "Tacotron" else mel_input[idx].data.cpu().numpy()
align_img = alignments[idx].data.cpu().numpy()
eval_figures = {