(x, image_size)
| 264 | |
| 265 | |
| 266 | def resize_dataset(x, image_size): |
| 267 | num_data = x.shape[0] |
| 268 | dim = x.shape[1] |
| 269 | X = np.zeros(shape=(num_data, dim, image_size, image_size), |
| 270 | dtype=np.float32) |
| 271 | for n in range(0, num_data): |
| 272 | for d in range(0, dim): |
| 273 | X[n, d, :, :] = np.array(Image.fromarray(x[n, d, :, :]).resize( |
| 274 | (image_size, image_size), Image.BILINEAR), |
| 275 | dtype=np.float32) |
| 276 | return X |
| 277 | |
| 278 | |
| 279 | def run(global_rank, |