diff --git a/latent.ipynb b/latent.ipynb
index 90e5d45..915471a 100644
--- a/latent.ipynb
+++ b/latent.ipynb
@@ -1076,7 +1076,7 @@
         "                                    im.save(temp_file, format = \"PNG\")\n",
         "                                    init = Image.open(fetch(temp_file)).convert('RGB')\n",
         "                                    init = TF.to_tensor(init).to(device).unsqueeze(0)\n",
-        "                                    opt.H, opt.W = opt.H*scale_factor, opt.W*scale_factor\n",
+        "                                    opt.H, opt.W = int(opt.H*scale_factor), int(opt.W*scale_factor)\n",
         "                                    init = resize(init,out_shape = [opt.n_samples,3,opt.H, opt.W], antialiasing=True)\n",
         "                                    init = init.mul(2).sub(1).half()\n",
         "                                    x_T =  (model.first_stage_model.encode(init).sample()*init_magnitude)\n",
@@ -1103,7 +1103,7 @@
         "                                      progress.value = output.getvalue()\n",
         "                                    init = Image.open(fetch(f\"GFPGAN/results/restored_imgs/{temp_file_name}\")).convert('RGB')\n",
         "                                    init = TF.to_tensor(init).to(device).unsqueeze(0)\n",
-        "                                    opt.H, opt.W = opt.H*scale_factor, opt.W*scale_factor\n",
+        "                                    opt.H, opt.W = int(opt.H*scale_factor), int(opt.W*scale_factor)\n",
         "                                    init = resize(init,out_shape = [opt.n_samples,3,opt.H, opt.W], antialiasing=True)\n",
         "                                    init = init.mul(2).sub(1).half()\n",
         "                                    x_T =  (model.first_stage_model.encode(init).sample()*init_magnitude)\n",