Upload finetune.py
Browse files- finetune.py +45 -0
finetune.py
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from model import PopMusicTransformer
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from glob import glob
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import os
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os.environ['CUDA_VISIBLE_DEVICES'] = '0'
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def main():
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# declare model
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model = PopMusicTransformer(
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checkpoint='REMI-tempo-checkpoint',
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is_training=True)
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# prepare data
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midi_paths = glob('YOUR PERSOANL FOLDER/*.midi') # you need to revise it
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training_data = model.prepare_data(midi_paths=midi_paths)
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# check output checkpoint folder
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####################################
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# if you use "REMI-tempo-chord-checkpoint" for the pre-trained checkpoint
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# please name your output folder as something with "chord"
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# for example: my-love-chord, cute-doggy-chord, ...
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# if use "REMI-tempo-checkpoint"
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# for example: my-love, cute-doggy, ...
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####################################
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output_checkpoint_folder = 'REMI-finetune' # your decision
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if not os.path.exists(output_checkpoint_folder):
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os.mkdir(output_checkpoint_folder)
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# finetune
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model.finetune(
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training_data=training_data,
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output_checkpoint_folder=output_checkpoint_folder)
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####################################
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# after finetuning, please choose which checkpoint you want to try
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# and change the checkpoint names you choose into "model"
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# and copy the "dictionary.pkl" into the your output_checkpoint_folder
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# ***** the same as the content format in "REMI-tempo-checkpoint" *****
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# and then, you can use "main.py" to generate your own music!
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# (do not forget to revise the checkpoint path to your own in "main.py")
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####################################
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# close
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model.close()
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if __name__ == '__main__':
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main()
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