Changed app.py

app.py

@@ -13,37 +13,30 @@ from PIL import Image
 network_pkl_a = 'stylegan3-r-afhqv2-512x512.pkl'
 network_pkl_d = 'network-snapshot.pkl'
 with open(network_pkl_d, 'rb') as f:
-    G = pickle.load(f)['G_ema']  # torch.nn.Module
+    G_d = pickle.load(f)['G_ema'].cpu()  # torch.nn.Module
 
 with open(network_pkl_a, 'rb') as f:
-    G_a = pickle.load(f)['G_ema']  # torch.nn.Module
+    G_a = pickle.load(f)['G_ema'].cpu()  # torch.nn.Module
     
 def gen_image(text):
     if text=='show me':
-        return gen_image_d()
+        return gen_image_helper(G_d)
     else:
-        return gen_image_a()
-        
-def gen_image_a():    
-    z = torch.randn([1, G_a.z_dim])  # latent codes
-    c = None  # class labels (not used in this example)
-    img = G_a(z, c)
-    img = (img.permute(0, 2, 3, 1) * 127.5 + 128).clamp(0, 255).to(torch.uint8)
-    image=PIL.Image.fromarray(img[0].numpy(), 'RGB')
-    transform = transforms.Resize((image.height * 2, image.width * 2), interpolation=transforms.InterpolationMode.BILINEAR)
-    upscaled_image = transform(image)
-    return upscaled_image
+        return gen_image_helper(G_a)
 
-def gen_image_d():    
-    z = torch.randn([1, G.z_dim])  # latent codes
+def gen_image_helper(model):
+    z = torch.randn([1, model.z_dim]).cpu()  # latent codes
     c = None  # class labels (not used in this example)
-    img = G(z, c)
+    img = model(z, c)
     img = (img.permute(0, 2, 3, 1) * 127.5 + 128).clamp(0, 255).to(torch.uint8)
-    image=PIL.Image.fromarray(img[0].numpy(), 'RGB')
+    #um = torch..nn.Upsample(scale_factor=2, mode='bilinear')
+    #img=um(img)
+    image=PIL.Image.fromarray(img[0].cpu().numpy(), 'RGB')
     transform = transforms.Resize((image.height * 2, image.width * 2), interpolation=transforms.InterpolationMode.BILINEAR)
-    upscaled_image = transform(image)
+    upscaled_image = transform(image)  
     return upscaled_image
-    
+          
+
 demo = gr.Interface(
     fn=gen_image,
     inputs=gr.Textbox(lines=2, placeholder="Prompt here..."),
@@ -52,5 +45,5 @@ demo = gr.Interface(
     description="Enter text to generate an image using a custom PyTorch model."
 )
 
-#if __name__ == "__main__":
-demo.launch()
+if __name__ == "__main__":
+    demo.launch()