Example:
class load_data(Dataset):
def __init__(self, dataset):
self.x = np.loadtxt('data/{}.txt'.format(dataset), dtype=float)
self.y = np.loadtxt('data/{}_label.txt'.format(dataset), dtype=int)
def __len__(self):
return self.x.shape[0]
def __getitem__(self, idx):
return torch.from_numpy(np.array(self.x[idx])),\
torch.from_numpy(np.array(self.y[idx])),\
torch.from_numpy(np.array(idx))
if __name__ =='__main__':
dataname = 'dblp'
dataset = load_data(dataname)
train_loader = DataLoader(dataset, batch_size=256, shuffle=True)
for x,y,idx in train_loader:
print(x.shape)
print(y.shape)
print(idx.shape)