54 lines
1.3 KiB
Python
54 lines
1.3 KiB
Python
"""CBC example using the Iris dataset."""
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import argparse
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import prototorch as pt
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import pytorch_lightning as pl
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import torch
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if __name__ == "__main__":
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# Command-line arguments
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parser = argparse.ArgumentParser()
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parser = pl.Trainer.add_argparse_args(parser)
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args = parser.parse_args()
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# Dataset
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train_ds = pt.datasets.Iris(dims=[0, 2])
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# Reproducibility
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pl.utilities.seed.seed_everything(seed=42)
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# Dataloaders
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train_loader = torch.utils.data.DataLoader(train_ds, batch_size=32)
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# Hyperparameters
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hparams = dict(
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distribution=[1, 0, 3],
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margin=0.1,
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proto_lr=0.01,
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bb_lr=0.01,
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)
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# Initialize the model
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model = pt.models.CBC(
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hparams,
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components_initializer=pt.initializers.SSCI(train_ds, noise=0.01),
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reasonings_iniitializer=pt.initializers.
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PurePositiveReasoningsInitializer(),
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)
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# Callbacks
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vis = pt.models.VisCBC2D(data=train_ds,
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title="CBC Iris Example",
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resolution=100,
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axis_off=True)
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# Setup trainer
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trainer = pl.Trainer.from_argparse_args(
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args,
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callbacks=[vis],
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)
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# Training loop
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trainer.fit(model, train_loader)
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