54 lines
		
	
	
		
			1.3 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			54 lines
		
	
	
		
			1.3 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| """CBC example using the Iris dataset."""
 | |
| 
 | |
| import argparse
 | |
| 
 | |
| import pytorch_lightning as pl
 | |
| import torch
 | |
| 
 | |
| import prototorch as pt
 | |
| 
 | |
| if __name__ == "__main__":
 | |
|     # Command-line arguments
 | |
|     parser = argparse.ArgumentParser()
 | |
|     parser = pl.Trainer.add_argparse_args(parser)
 | |
|     args = parser.parse_args()
 | |
| 
 | |
|     # Dataset
 | |
|     train_ds = pt.datasets.Iris(dims=[0, 2])
 | |
| 
 | |
|     # Reproducibility
 | |
|     pl.utilities.seed.seed_everything(seed=3)
 | |
| 
 | |
|     # Dataloaders
 | |
|     train_loader = torch.utils.data.DataLoader(train_ds,
 | |
|                                                num_workers=0,
 | |
|                                                batch_size=150)
 | |
| 
 | |
|     # Hyperparameters
 | |
|     hparams = dict(
 | |
|         distribution=[3, 2, 2],
 | |
|         proto_lr=0.01,
 | |
|         bb_lr=0.01,
 | |
|     )
 | |
| 
 | |
|     # Initialize the model
 | |
|     model = pt.models.CBC(
 | |
|         hparams,
 | |
|         prototype_initializer=pt.components.SSI(train_ds, noise=0.01),
 | |
|     )
 | |
| 
 | |
|     # Callbacks
 | |
|     vis = pt.models.VisCBC2D(data=train_ds,
 | |
|                              title="CBC Iris Example",
 | |
|                              resolution=300,
 | |
|                              axis_off=True)
 | |
| 
 | |
|     # Setup trainer
 | |
|     trainer = pl.Trainer.from_argparse_args(
 | |
|         args,
 | |
|         callbacks=[vis],
 | |
|     )
 | |
| 
 | |
|     # Training loop
 | |
|     trainer.fit(model, train_loader)
 |