| 503 | |
| 504 | |
| 505 | def celeb(): |
| 506 | X = util.get_celeb() |
| 507 | # just loads a list of filenames, we will load them in dynamically |
| 508 | # because there are many |
| 509 | dim = 64 |
| 510 | colors = 3 |
| 511 | |
| 512 | # for celeb |
| 513 | d_sizes = { |
| 514 | 'conv_layers': [ |
| 515 | (64, 5, 2, False), |
| 516 | (128, 5, 2, True), |
| 517 | (256, 5, 2, True), |
| 518 | (512, 5, 2, True) |
| 519 | ], |
| 520 | 'dense_layers': [], |
| 521 | } |
| 522 | g_sizes = { |
| 523 | 'z': 100, |
| 524 | 'projection': 512, |
| 525 | 'bn_after_project': True, |
| 526 | 'conv_layers': [ |
| 527 | (256, 5, 2, True), |
| 528 | (128, 5, 2, True), |
| 529 | (64, 5, 2, True), |
| 530 | (colors, 5, 2, False) |
| 531 | ], |
| 532 | 'dense_layers': [], |
| 533 | 'output_activation': tf.tanh, |
| 534 | } |
| 535 | |
| 536 | # setup gan |
| 537 | # note: assume square images, so only need 1 dim |
| 538 | gan = DCGAN(dim, colors, d_sizes, g_sizes) |
| 539 | gan.fit(X) |
| 540 | |
| 541 | |
| 542 | def mnist(): |