prototorch_models/examples/gmlvq_iris.py
2021-05-15 12:43:00 +02:00

39 lines
1.1 KiB
Python

"""GMLVQ example using all four dimensions of the Iris dataset."""
import prototorch as pt
import pytorch_lightning as pl
import torch
if __name__ == "__main__":
# Dataset
from sklearn.datasets import load_iris
x_train, y_train = load_iris(return_X_y=True)
train_ds = pt.datasets.NumpyDataset(x_train, y_train)
# Dataloaders
train_loader = torch.utils.data.DataLoader(train_ds,
num_workers=0,
batch_size=150)
# Hyperparameters
nclasses = 3
prototypes_per_class = 1
hparams = dict(
distribution=(nclasses, prototypes_per_class),
input_dim=x_train.shape[1],
latent_dim=x_train.shape[1],
lr=0.01,
)
# Initialize the model
model = pt.models.GMLVQ(hparams,
prototype_initializer=pt.components.SMI(train_ds))
# Setup trainer
trainer = pl.Trainer(max_epochs=100, gpus=0)
# Training loop
trainer.fit(model, train_loader)
# Display the Lambda matrix
model.show_lambda()