(x, image_size)
| 82 | |
| 83 | |
| 84 | def resize_dataset(x, image_size): |
| 85 | num_data = x.shape[0] |
| 86 | dim = x.shape[1] |
| 87 | X = np.zeros(shape=(num_data, dim, image_size, image_size), |
| 88 | dtype=np.float32) |
| 89 | for n in range(0, num_data): |
| 90 | for d in range(0, dim): |
| 91 | X[n, d, :, :] = np.array(Image.fromarray(x[n, d, :, :]).resize( |
| 92 | (image_size, image_size), Image.BILINEAR), |
| 93 | dtype=np.float32) |
| 94 | return X |
| 95 | |
| 96 | |
| 97 | def run(global_rank, |