utils.py

import numpy as np
import torch 
from huggan.pytorch.lightweight_gan.ligthweight_gan import LightweightGAN

def carga_modelo(model_name="ceyda/butterfly_cropped_uniq1K_512", model_version=None):
        gan = LightweightGAN.from_pretrained(model_name, version=model_version,  use_auth_token=None)
        gan.eval()
        return gan

def genera(gan, batch_size=1):
        with torch.no_grad():
                ims = gan.G(torch.randn(batch_size, gan.latent_dim)).clamp_(0.0, 1.0) * 255
                ims = ims.permute(0, 2, 3, 1).deatch().cpu().numpy().astype(np.uint8)

        return ims