forked from mrq/ai-voice-cloning
now there should be feature parity between trainers
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fd9b2e082c
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12
src/utils.py
12
src/utils.py
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@ -726,18 +726,21 @@ class TrainingState():
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else:
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return
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if 'elapsed_time' in self.info:
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self.info['iteration_rate'] = self.info['elapsed_time']
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del self.info['elapsed_time']
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self.info = data
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if 'epoch' in self.info:
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self.epoch = int(self.info['epoch'])
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if 'it' in self.info:
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self.it = int(self.info['it'])
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if 'iteration' in self.info:
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self.it = int(self.info['iteration'])
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if 'step' in self.info:
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self.step = int(self.info['step'])
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if 'steps' in self.info:
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self.steps = int(self.info['steps'])
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if 'iteration_rate' in self.info:
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it_rate = self.info['iteration_rate']
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self.it_rate = f'{"{:.3f}".format(1/it_rate)}it/s' if 0 < it_rate and it_rate < 1 else f'{"{:.3f}".format(it_rate)}s/it'
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@ -905,14 +908,9 @@ class TrainingState():
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else:
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continue
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if args.tts_backend == "tortoise":
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if "it" not in data:
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continue
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it = data['it']
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else:
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if "iteration" not in data:
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continue
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it = data['iteration']
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# this method should have it at least
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unq[f'{it}'] = data
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