forked from mrq/ai-voice-cloning
oops
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bc0d9ab3ed
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@ -543,7 +543,7 @@ class TrainingState():
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print("Removing", path)
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print("Removing", path)
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os.remove(path)
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os.remove(path)
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def parse(self, line, verbose=False, buffer_size=8, progress=None ):
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def parse(self, line, verbose=False, buffer_size=8, keep_x_past_datasets=0, progress=None ):
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self.buffer.append(f'{line}')
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self.buffer.append(f'{line}')
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# rip out iteration info
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# rip out iteration info
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@ -646,7 +646,7 @@ class TrainingState():
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print(f'{"{:.3f}".format(percent*100)}% {message}')
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print(f'{"{:.3f}".format(percent*100)}% {message}')
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self.buffer.append(f'{"{:.3f}".format(percent*100)}% {message}')
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self.buffer.append(f'{"{:.3f}".format(percent*100)}% {message}')
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self.cleanup_old()
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self.cleanup_old(keep=keep_x_past_datasets)
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self.buffer = self.buffer[-buffer_size:]
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self.buffer = self.buffer[-buffer_size:]
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if verbose or not self.training_started:
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if verbose or not self.training_started:
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@ -668,7 +668,7 @@ def run_training(config_path, verbose=False, buffer_size=8, keep_x_past_datasets
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for line in iter(training_state.process.stdout.readline, ""):
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for line in iter(training_state.process.stdout.readline, ""):
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res = training_state.parse( line=line, verbose=verbose, buffer_size=buffer_size, progress=progress )
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res = training_state.parse( line=line, verbose=verbose, buffer_size=buffer_size, keep_x_past_datasets=keep_x_past_datasets, progress=progress )
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print(f"[Training] [{datetime.now().isoformat()}] {line[:-1]}")
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print(f"[Training] [{datetime.now().isoformat()}] {line[:-1]}")
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if res:
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if res:
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yield res
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yield res
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