Medix-AI/coqui-tts
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coqui-tts
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remove merge conflicts

This commit is contained in:
erogol 2020-10-08 01:35:27 +02:00
parent c5074cfd8e
commit c2c4126a18
1 changed files with 0 additions and 14 deletions
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TTS/tts/layers/losses.py
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@ -254,17 +254,9 @@ class TacotronLoss(torch.nn.Module):
torch.flip(decoder_b_output, dims=(1, )), mel_input, torch.flip(decoder_b_output, dims=(1, )), mel_input,
output_lens) output_lens)
else: else:
<<<<<<< HEAD
decoder_b_loss = self.criterion(
torch.flip(decoder_b_output, dims=(1, )), mel_input)
decoder_c_loss = torch.nn.functional.l1_loss(
torch.flip(decoder_b_output, dims=(1, )), decoder_output)
loss += decoder_b_loss + decoder_c_loss
=======
decoder_b_loss = self.criterion(torch.flip(decoder_b_output, dims=(1, )), mel_input) decoder_b_loss = self.criterion(torch.flip(decoder_b_output, dims=(1, )), mel_input)
decoder_c_loss = torch.nn.functional.l1_loss(torch.flip(decoder_b_output, dims=(1, )), decoder_output) decoder_c_loss = torch.nn.functional.l1_loss(torch.flip(decoder_b_output, dims=(1, )), decoder_output)
loss += self.decoder_alpha * (decoder_b_loss + decoder_c_loss) loss += self.decoder_alpha * (decoder_b_loss + decoder_c_loss)
>>>>>>> differential spectral loss
return_dict['decoder_b_loss'] = decoder_b_loss return_dict['decoder_b_loss'] = decoder_b_loss
return_dict['decoder_c_loss'] = decoder_c_loss return_dict['decoder_c_loss'] = decoder_c_loss
@ -273,14 +265,8 @@ class TacotronLoss(torch.nn.Module):
decoder_b_loss = self.criterion(decoder_b_output, mel_input, decoder_b_loss = self.criterion(decoder_b_output, mel_input,
output_lens) output_lens)
# decoder_c_loss = torch.nn.functional.l1_loss(decoder_b_output, decoder_output) # decoder_c_loss = torch.nn.functional.l1_loss(decoder_b_output, decoder_output)
<<<<<<< HEAD
attention_c_loss = torch.nn.functional.l1_loss(
alignments, alignments_backwards)
loss += decoder_b_loss + attention_c_loss
=======
attention_c_loss = torch.nn.functional.l1_loss(alignments, alignments_backwards) attention_c_loss = torch.nn.functional.l1_loss(alignments, alignments_backwards)
loss += self.decoder_alpha * (decoder_b_loss + attention_c_loss) loss += self.decoder_alpha * (decoder_b_loss + attention_c_loss)
>>>>>>> differential spectral loss
return_dict['decoder_coarse_loss'] = decoder_b_loss return_dict['decoder_coarse_loss'] = decoder_b_loss
return_dict['decoder_ddc_loss'] = attention_c_loss return_dict['decoder_ddc_loss'] = attention_c_loss