[FEATURE] Add Growing Neural Gas

examples/gng_iris.py

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+import argparse
+
+import prototorch as pt
+import pytorch_lightning as pl
+from prototorch.components.initializers import SelectionInitializer
+from prototorch.datasets import Iris
+from prototorch.models.unsupervised import GrowingNeuralGas
+from torch.utils.data import DataLoader
+
+if __name__ == "__main__":
+    # Command-line arguments
+    parser = argparse.ArgumentParser()
+    parser = pl.Trainer.add_argparse_args(parser)
+    args = parser.parse_args()
+
+    # Prepare the data
+    train_ds = Iris(dims=[0, 2])
+    train_loader = DataLoader(train_ds, batch_size=32)
+
+    # Hyperparameters
+    hparams = dict(num_prototypes=2,
+                   lr=0.1,
+                   prototype_initializer=SelectionInitializer(train_ds.data))
+
+    # Initialize the model
+    model = GrowingNeuralGas(hparams)
+
+    # Model summary
+    print(model)
+
+    # Callbacks
+    vis = pt.models.VisNG2D(data=train_loader)
+
+    # Setup trainer
+    trainer = pl.Trainer.from_argparse_args(
+        args,
+        max_epochs=100,
+        callbacks=[vis],
+    )
+
+    # Training loop
+    trainer.fit(model, train_loader)
+
+    # Model summary
+    print(model)