Medix-AI/coqui-tts
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coqui-tts
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add DDC loss

This commit is contained in:
erogol 2020-06-04 14:27:40 +02:00
parent 1ca078ae7e
commit b4ac68df7b
1 changed files with 10 additions and 1 deletions
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11
layers/losses.py
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@ -184,7 +184,7 @@ class TacotronLoss(torch.nn.Module):
def forward(self, postnet_output, decoder_output, mel_input, linear_input,
stopnet_output, stopnet_target, output_lens, decoder_b_output,
alignments, alignment_lens, input_lens):
alignments, alignment_lens, alignments_backwards, input_lens):
return_dict = {}
# decoder and postnet losses
@ -226,6 +226,15 @@ class TacotronLoss(torch.nn.Module):
return_dict['decoder_b_loss'] = decoder_b_loss
return_dict['decoder_c_loss'] = decoder_c_loss
# double decoder consistency loss (if enabled)
if self.config.double_decoder_consistency:
decoder_b_loss = self.criterion(decoder_b_output, mel_input, output_lens)
# decoder_c_loss = torch.nn.functional.l1_loss(decoder_b_output, decoder_output)
attention_c_loss = torch.nn.functional.l1_loss(alignments, alignments_backwards)
loss += decoder_b_loss + attention_c_loss
return_dict['decoder_coarse_loss'] = decoder_b_loss
return_dict['decoder_ddc_loss'] = attention_c_loss
# guided attention loss (if enabled)
if self.config.ga_alpha > 0:
ga_loss = self.criterion_ga(alignments, input_lens, alignment_lens)