# Load the data
(train_size=1)
| 24 | if not mirror.startswith("http://yann.lecun.com")] |
| 25 | |
| 26 | def load(train_size=1): |
| 27 | """ |
| 28 | # Load the data |
| 29 | """ |
| 30 | |
| 31 | # the data, split between train and test sets |
| 32 | train = torchvision.datasets.MNIST("./", train=True, download=True) |
| 33 | |
| 34 | (x_train, y_train) = (train.data, train.targets) |
| 35 | |
| 36 | # split off a validation set for hyperparameter tuning |
| 37 | x_train = x_train[:train_size].clone() |
| 38 | |
| 39 | y_train = y_train[:train_size].clone() |
| 40 | |
| 41 | training_set = TensorDataset(x_train, y_train) |
| 42 | |
| 43 | datasets = [training_set] |
| 44 | |
| 45 | return datasets |
| 46 | |
| 47 | |
| 48 | def preprocess(dataset, normalize=True, expand_dims=True): |
no outgoing calls