Restore the trained generator and discriminator.
(self, resume_iters)
| 96 | print("The number of parameters: {}".format(num_params)) |
| 97 | |
| 98 | def restore_model(self, resume_iters): |
| 99 | """Restore the trained generator and discriminator.""" |
| 100 | print('Loading the trained models from step {}...'.format(resume_iters)) |
| 101 | G_path = os.path.join(self.model_save_dir, '{}-G.ckpt'.format(resume_iters)) |
| 102 | D_path = os.path.join(self.model_save_dir, '{}-D.ckpt'.format(resume_iters)) |
| 103 | self.G.load_state_dict(torch.load(G_path, map_location=lambda storage, loc: storage)) |
| 104 | self.D.load_state_dict(torch.load(D_path, map_location=lambda storage, loc: storage)) |
| 105 | |
| 106 | def build_tensorboard(self): |
| 107 | """Build a tensorboard logger.""" |
no outgoing calls