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9aacd2ee0a
8
train.py
8
train.py
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@ -368,13 +368,13 @@ def evaluate(model, criterion, criterion_st, ap, global_step, epoch):
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stop_tokens, stop_targets) if c.stopnet else torch.zeros(1)
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stop_tokens, stop_targets) if c.stopnet else torch.zeros(1)
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if c.loss_masking:
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if c.loss_masking:
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decoder_loss = criterion(decoder_output, mel_input,
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decoder_loss = criterion(decoder_output, mel_input,
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mel_lengths)
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mel_lengths)
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if c.model in ["Tacotron", "TacotronGST"]:
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if c.model in ["Tacotron", "TacotronGST"]:
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postnet_loss = criterion(postnet_output, linear_input,
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postnet_loss = criterion(postnet_output, linear_input,
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mel_lengths)
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mel_lengths)
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else:
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else:
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postnet_loss = criterion(postnet_output, mel_input,
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postnet_loss = criterion(postnet_output, mel_input,
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mel_lengths)
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mel_lengths)
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else:
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else:
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decoder_loss = criterion(decoder_output, mel_input)
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decoder_loss = criterion(decoder_output, mel_input)
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if c.model in ["Tacotron", "TacotronGST"]:
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if c.model in ["Tacotron", "TacotronGST"]:
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@ -449,7 +449,7 @@ def evaluate(model, criterion, criterion_st, ap, global_step, epoch):
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else:
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else:
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eval_audio = ap.inv_mel_spectrogram(const_spec.T)
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eval_audio = ap.inv_mel_spectrogram(const_spec.T)
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tb_logger.tb_eval_audios(global_step, {"ValAudio": eval_audio},
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tb_logger.tb_eval_audios(global_step, {"ValAudio": eval_audio},
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c.audio["sample_rate"])
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c.audio["sample_rate"])
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# Plot Validation Stats
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# Plot Validation Stats
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epoch_stats = {
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epoch_stats = {
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