| import numpy as np | |
| import torch | |
| from huggan.pytorch.lightweight_gan.lightweight_gan import LightweightGAN | |
| def cargar_mdoel(model_name = "ceyda/butterfly_cropped_uniq1K_512", model_version = None): | |
| gan = LightweightGAN.from_pretrained(model_name, version = model_version) | |
| gan.eval() | |
| return gan | |
| def general(gan, bach_size=1): | |
| with torch.no_grad(): | |
| ims = gan.G(torch.rand(bach_size, gan.latent_dim)).clamp_(0.0,1.0) * 255 | |
| ims = ims.permute(0,2,3,1).detach().cpu().numpy().astype(np.unit8) | |
| return ims | |