ca39aa00d5
Pass the component initializer as an hparam slows down the script very much. The API has now been changed to pass it as a kwarg to the models instead. The example scripts have also been updated to reflect the new changes. Also, ImageGMLVQ and an example script `gmlvq_mnist.py` that uses it have also been added.
54 lines
1.4 KiB
Python
54 lines
1.4 KiB
Python
"""GLVQ example using the spiral dataset."""
|
|
|
|
import prototorch as pt
|
|
import pytorch_lightning as pl
|
|
import torch
|
|
|
|
|
|
class StopOnNaN(pl.Callback):
|
|
def __init__(self, param):
|
|
super().__init__()
|
|
self.param = param
|
|
|
|
def on_epoch_end(self, trainer, pl_module, logs={}):
|
|
if torch.isnan(self.param).any():
|
|
raise ValueError("NaN encountered. Stopping.")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
# Dataset
|
|
train_ds = pt.datasets.Spiral(n_samples=600, noise=0.6)
|
|
|
|
# Dataloaders
|
|
train_loader = torch.utils.data.DataLoader(train_ds,
|
|
num_workers=0,
|
|
batch_size=256)
|
|
|
|
# Hyperparameters
|
|
nclasses = 2
|
|
prototypes_per_class = 20
|
|
hparams = dict(
|
|
distribution=(nclasses, prototypes_per_class),
|
|
transfer_function="sigmoid_beta",
|
|
transfer_beta=10.0,
|
|
lr=0.01,
|
|
)
|
|
|
|
# Initialize the model
|
|
model = pt.models.GLVQ(hparams,
|
|
prototype_initializer=pt.components.SSI(train_ds,
|
|
noise=1e-1))
|
|
|
|
# Callbacks
|
|
vis = pt.models.VisGLVQ2D(train_ds, show_last_only=True, block=True)
|
|
snan = StopOnNaN(model.proto_layer.components)
|
|
|
|
# Setup trainer
|
|
trainer = pl.Trainer(
|
|
max_epochs=200,
|
|
callbacks=[vis, snan],
|
|
)
|
|
|
|
# Training loop
|
|
trainer.fit(model, train_loader)
|