42 lines
1.1 KiB
Python
42 lines
1.1 KiB
Python
"""GLVQ example using the Iris dataset."""
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import pytorch_lightning as pl
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import torch
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from prototorch.components import initializers as cinit
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from prototorch.datasets.abstract import NumpyDataset
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from sklearn.datasets import load_iris
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from torch.utils.data import DataLoader
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from prototorch.models.callbacks.visualization import VisGLVQ2D
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from prototorch.models.glvq import GLVQ
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if __name__ == "__main__":
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# Dataset
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x_train, y_train = load_iris(return_X_y=True)
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x_train = x_train[:, [0, 2]]
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train_ds = NumpyDataset(x_train, y_train)
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# Dataloaders
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train_loader = DataLoader(train_ds, num_workers=0, batch_size=150)
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# Hyperparameters
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hparams = dict(
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nclasses=3,
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prototypes_per_class=2,
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prototype_initializer=cinit.StratifiedMeanInitializer(
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torch.Tensor(x_train), torch.Tensor(y_train)),
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lr=0.01,
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)
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# Initialize the model
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model = GLVQ(hparams)
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# Setup trainer
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trainer = pl.Trainer(
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max_epochs=50,
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callbacks=[VisGLVQ2D(x_train, y_train)],
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)
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# Training loop
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trainer.fit(model, train_loader)
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