forked from mrq/ai-voice-cloning
oops
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b989123bd4
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5a41db978e
12
src/utils.py
12
src/utils.py
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@ -546,9 +546,9 @@ class TrainingState():
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for k in infos:
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if 'loss_gpt_total' in infos[k]:
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self.losses.append({ "step": int(k), "value": infos[k]['loss_text_ce'], "type": "text_ce" })
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self.losses.append({ "step": int(k), "value": infos[k]['loss_mel_ce'], "type": "mel_ce" })
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self.losses.append({ "step": int(k), "value": infos[k]['loss_gpt_total'], "type": "gpt_total" })
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self.losses.append({ "step": int(k), "value": infos[k]['loss_text_ce'], "type": "loss_text_ce" })
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self.losses.append({ "step": int(k), "value": infos[k]['loss_mel_ce'], "type": "loss_mel_ce" })
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self.losses.append({ "step": int(k), "value": infos[k]['loss_gpt_total'], "type": "loss_gpt_total" })
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def cleanup_old(self, keep=2):
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if keep <= 0:
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@ -663,9 +663,9 @@ class TrainingState():
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if 'loss_gpt_total' in self.info:
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self.status = f"Total loss at epoch {self.epoch}: {self.info['loss_gpt_total']}"
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self.losses.append({ "step": self.it, "value": self.info['loss_text_ce'], "type": "text_ce" })
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self.losses.append({ "step": self.it, "value": self.info['loss_mel_ce'], "type": "mel_ce" })
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self.losses.append({ "step": self.it, "value": self.info['loss_gpt_total'], "type": "gpt_total" })
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self.losses.append({ "step": self.it, "value": self.info['loss_text_ce'], "type": "loss_text_ce" })
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self.losses.append({ "step": self.it, "value": self.info['loss_mel_ce'], "type": "loss_mel_ce" })
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self.losses.append({ "step": self.it, "value": self.info['loss_gpt_total'], "type": "loss_gpt_total" })
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should_return = True
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elif line.find('Saving models and training states') >= 0:
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