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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
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