[BUG] Training unstable in examples/gng_iris.py
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"""Growing Neural Gas example using the Iris dataset."""
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import argparse
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import prototorch as pt
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@ -13,12 +15,15 @@ if __name__ == "__main__":
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parser = pl.Trainer.add_argparse_args(parser)
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args = parser.parse_args()
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# Reproducibility
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pl.utilities.seed.seed_everything(seed=42)
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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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train_loader = DataLoader(train_ds, batch_size=8)
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# Hyperparameters
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hparams = dict(num_prototypes=2,
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hparams = dict(num_prototypes=5,
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lr=0.1,
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prototype_initializer=SelectionInitializer(train_ds.data))
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