Update app.py

app.py

@@ -12,13 +12,13 @@ from utils import load_models, save_model_w2w, save_model_for_diffusers
 from sampling import sample_weights
 from huggingface_hub import snapshot_download
 
-#global device
-#global generator 
-#global unet
-#global vae 
-#global text_encoder
-#global tokenizer
-#global noise_scheduler
+global device
+global generator 
+global unet
+global vae 
+global text_encoder
+global tokenizer
+global noise_scheduler
 device = "cuda:0"
 
 models_path = snapshot_download(repo_id="Snapchat/w2w")
@@ -34,20 +34,20 @@ unet, vae, text_encoder, tokenizer, noise_scheduler = load_models(device)
 network = sample_weights(unet, proj, mean, std, v[:, :1000], device, factor = 1.00)
 #global network
 
-#def sample_model():
-#    global unet
-#    del unet
-#    global network
-#    unet, _, _, _, _ = load_models(device)
+def sample_model():
+   global unet
+   del unet
+   global network
+   unet, _, _, _, _ = load_models(device)
 
 def inference(prompt, negative_prompt, guidance_scale, ddim_steps, seed):
-    #global device
-    #global generator 
-    #global unet
-    #global vae 
-    #global text_encoder
-    #global tokenizer
-    #global noise_scheduler
+    global device
+    global generator 
+    global unet
+    global vae 
+    global text_encoder
+    global tokenizer
+    global noise_scheduler
     generator = torch.Generator(device=device).manual_seed(seed)
     latents = torch.randn(
         (1, unet.in_channels, 512 // 8, 512 // 8),