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Readme.md

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# Structure
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- clients: templates for SuperCollider, Bela (C++), Pure Data, ...
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- osc:
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- notepredictor: python package for offline pytorch models
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- pytorch-osc: app with OSC server + event loops
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- notepredictor: python package for defining+training pytorch RNN models
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- notebooks: jupyter notebooks
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- scripts: helper scripts for training, data preprocessing etc
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```
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conda env create -f environment.yml
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conda activate pytorch-osc
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pip install -e pytorch-osc
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pip install -e notepredictor
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```
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# Train a model
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```
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python scipts/lakh_prep.py --data_path /path/to/midi/files --dest_path /path/to/data/storage
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python scripts/train_pitch.py --data_dir /path/to/data/storage --log_dir /path/for/tensorboard logs --model_dir /path/for/checkpoints train
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```
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# Run OSC app
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```
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python pytorch-osc/pytorch-osc.py --checkpoint /path/to/my/model.ckpt
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```
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# Develop

clients/pytorch-osc.scd

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o.free; // remove the OSCFunc when you are done.
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n = NetAddr("127.0.0.1", NetAddr.langPort);
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n.sendMsg('/prediction', 1)
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// n = NetAddr("127.0.0.1", NetAddr.langPort);
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// n.sendMsg('/prediction', 1)
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// OSCdef.trace(true)
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