46 lines
1.1 KiB
Python
46 lines
1.1 KiB
Python
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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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from prototorch.components.initializers import SelectionInitializer
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from prototorch.datasets import Iris
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from prototorch.models.unsupervised import GrowingNeuralGas
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from torch.utils.data import DataLoader
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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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# Prepare the data
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train_ds = Iris(dims=[0, 2])
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train_loader = DataLoader(train_ds, batch_size=32)
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# Hyperparameters
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hparams = dict(num_prototypes=2,
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lr=0.1,
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prototype_initializer=SelectionInitializer(train_ds.data))
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# Initialize the model
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model = GrowingNeuralGas(hparams)
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# Model summary
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print(model)
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# Callbacks
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vis = pt.models.VisNG2D(data=train_loader)
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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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max_epochs=100,
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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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# Model summary
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print(model)
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