forked from mrq/ai-voice-cloning
oops
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787b44807a
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5037752059
10
src/utils.py
10
src/utils.py
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@ -600,8 +600,10 @@ class TrainingState():
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self.it_rate = rate
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except Exception as e:
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pass
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message = f'[{self.epoch}/{self.epochs}, {self.it}/{self.its}, {step}/{steps}] [{self.epoch_rate}, {self.it_rate}] [Loss at it {self.losses[-1]["iteration"]}: {self.losses[-1]["loss"]}] [ETA: {self.eta_hhmmss}]'
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last_loss = ""
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if len(self.losses) > 0:
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last_loss = f'[Loss @ it. {self.losses[-1]["iteration"]}: {self.losses[-1]["loss"]}]'
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message = f'[{self.epoch}/{self.epochs}, {self.it}/{self.its}, {step}/{steps}] [{self.epoch_rate}, {self.it_rate}] {last_loss} [ETA: {self.eta_hhmmss}]'
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if lapsed:
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self.epoch = self.epoch + 1
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@ -1180,9 +1182,13 @@ def setup_args():
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if os.path.isfile('./config/exec.json'):
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with open(f'./config/exec.json', 'r', encoding="utf-8") as f:
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try:
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overrides = json.load(f)
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for k in overrides:
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default_arguments[k] = overrides[k]
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except Exception as e:
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print(e)
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pass
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parser = argparse.ArgumentParser()
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parser.add_argument("--share", action='store_true', default=default_arguments['share'], help="Lets Gradio return a public URL to use anywhere")
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@ -206,6 +206,7 @@ def import_training_settings_proxy( voice ):
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outdir = f'./training/{voice}-finetune/'
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in_config_path = f"{indir}/train.yaml"
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out_config_path = None
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out_configs = []
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if os.path.isdir(outdir):
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out_configs = sorted([d[:-5] for d in os.listdir(outdir) if d[-5:] == ".yaml" ])
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@ -240,6 +241,9 @@ def import_training_settings_proxy( voice ):
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save_rate = int(config['logger']['save_checkpoint_freq'] / steps_per_iteration)
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statedir = f'{outdir}/training_state/' # NOOO STOP MIXING YOUR CASES
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resumes = []
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resume_path = None
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if os.path.isdir(statedir):
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resumes = sorted([int(d[:-6]) for d in os.listdir(statedir) if d[-6:] == ".state" ])
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if len(resumes) > 0:
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@ -490,7 +494,7 @@ def setup_gradio():
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with gr.Row():
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refresh_dataset_list = gr.Button(value="Refresh Dataset List")
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import_dataset_button = gr.Button(value="Import Dataset")
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import_dataset_button = gr.Button(value="Reuse/Import Dataset")
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with gr.Column():
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save_yaml_output = gr.TextArea(label="Console Output", interactive=False, max_lines=8)
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with gr.Row():
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