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utils.py
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utils.py
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import torch
import torchvision.transforms as transforms
import torchvision.datasets as dset
# Directory containing the data.
root = 'data/celeba'
def get_celeba(params):
"""
Loads the dataset and applies proproccesing steps to it.
Returns a PyTorch DataLoader.
"""
# Data proprecessing.
transform = transforms.Compose([
transforms.Resize(params['imsize']),
transforms.CenterCrop(params['imsize']),
transforms.ToTensor(),
transforms.Normalize((0.5, 0.5, 0.5),
(0.5, 0.5, 0.5))])
# Create the dataset.
dataset = dset.ImageFolder(root=root, transform=transform)
# Create the dataloader.
dataloader = torch.utils.data.DataLoader(dataset,
batch_size=params['bsize'],
shuffle=True)
return dataloader