sed device to cpu if cuda is not there

app.py

@@ -27,7 +27,7 @@ from PIL import Image
 opts_args = ['--no_fine_mapper']
 opts = GradioTestOptions().parse(opts_args)
 device = 'cuda' if torch.cuda.is_available() else 'cpu'
-opts.device= device if opts.device is None else opts.device
+opts.device= device
 
 mapper_dict = {
     'afro':'./pretrained_models/styleCLIP_mappers/afro_hairstyle.pt',

models/stylegan2/op/fused_act.py

@@ -5,6 +5,7 @@ from torch import nn
 from torch.nn import functional as F
 
 module_path = os.path.dirname(__file__)
+device = 'cuda' if torch.cuda.is_available() else 'cpu'
 
 
 
@@ -22,7 +23,7 @@ class FusedLeakyReLU(nn.Module):
 
 def fused_leaky_relu(input, bias, negative_slope=0.2, scale=2 ** 0.5):
     rest_dim = [1] * (input.ndim - bias.ndim - 1)
-    input = input.cuda()
+    input = input.to(device)
     if input.ndim == 3:
         return (
             F.leaky_relu(