utils.py
No OneTemporary
Actions

Subscribers

None

File Metadata


	import torch
	from torchvision import datasets, transforms
	from sklearn.preprocessing import normalize

	def load_data(dataset='EMNIST', batch_size=100000):
	if dataset=='EMNIST':
	trans = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.5,), (1.0,))])
	data = datasets.EMNIST('./datasets/', 'bymerge', transform=trans, download = True)
	data_loader = torch.utils.data.DataLoader(
	dataset=data,
	batch_size=batch_size,
	shuffle=False,
	drop_last=True)

	return data_loader

	def normalise_weightmatrix(W):
	return normalize(W)