(pil_image, resolution)
| 19 | return torch.log(x/(1-x)) |
| 20 | |
| 21 | def PILtoTorch(pil_image, resolution): |
| 22 | resized_image_PIL = pil_image.resize(resolution) |
| 23 | resized_image = torch.from_numpy(np.array(resized_image_PIL)) / 255.0 |
| 24 | if len(resized_image.shape) == 3: |
| 25 | return resized_image.permute(2, 0, 1) |
| 26 | else: |
| 27 | return resized_image.unsqueeze(dim=-1).permute(2, 0, 1) |
| 28 | |
| 29 | def get_expon_lr_func( |
| 30 | lr_init, lr_final, lr_delay_steps=0, lr_delay_mult=1.0, max_steps=1000000 |