(x, image_size)
| 171 | |
| 172 | |
| 173 | def resize_dataset(x, image_size): |
| 174 | num_data = x.shape[0] |
| 175 | dim = x.shape[1] |
| 176 | X = np.zeros(shape=(num_data, dim, image_size, image_size), dtype=np.float32) |
| 177 | for n in range(0, num_data): |
| 178 | for d in range(0, dim): |
| 179 | X[n, d, :, :] = np.array( |
| 180 | Image.fromarray(x[n, d, :, :]).resize((image_size, image_size), Image.BILINEAR), |
| 181 | dtype=np.float32, |
| 182 | ) |
| 183 | return X |
| 184 | |
| 185 | |
| 186 | def get_data(data, data_dist="iid", device_id=None): |