prototorch_models/examples/knn_iris.py

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"""k-NN example using 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)
x_train = x_train[:, [0, 2]]
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
hparams = dict(k=20)
# Initialize the model
model = pt.models.KNN(hparams, data=train_ds)
# Callbacks
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vis = pt.models.VisGLVQ2D(data=(x_train, y_train), resolution=200)
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# Setup trainer
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trainer = pl.Trainer(max_epochs=1, callbacks=[vis], gpus=0)
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# Training loop
# This is only for visualization. k-NN has no training phase.
trainer.fit(model, train_loader)
# Recall
y_pred = model.predict(torch.tensor(x_train))
print(y_pred)