prototorch_models/examples/glvq_spiral.py

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"""GLVQ example using the spiral dataset."""
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import argparse
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import prototorch as pt
import pytorch_lightning as pl
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import torch
if __name__ == "__main__":
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# Command-line arguments
parser = argparse.ArgumentParser()
parser = pl.Trainer.add_argparse_args(parser)
args = parser.parse_args()
# Dataset
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train_ds = pt.datasets.Spiral(num_samples=600, noise=0.6)
# Dataloaders
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train_loader = torch.utils.data.DataLoader(train_ds,
num_workers=0,
batch_size=256)
# Hyperparameters
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num_classes = 2
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prototypes_per_class = 20
hparams = dict(
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distribution=(num_classes, prototypes_per_class),
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transfer_function="sigmoid_beta",
transfer_beta=10.0,
lr=0.01,
)
# Initialize the model
model = pt.models.GLVQ(hparams,
prototype_initializer=pt.components.SSI(train_ds,
noise=1e-1))
# Callbacks
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vis = pt.models.VisGLVQ2D(train_ds, show_last_only=True, block=True)
# Setup trainer
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trainer = pl.Trainer.from_argparse_args(
args,
callbacks=[vis],
terminate_on_nan=True,
)
# Training loop
trainer.fit(model, train_loader)