Update app.py

app.py

@@ -376,13 +376,13 @@ def start(_, calibrate_prompts, user_id, request: gr.Request):
             './first.mp4',
             './second.mp4',
             './third.mp4',
-            './fourth.mp4',
-            './fifth.mp4',
-            './sixth.mp4',
-            './seventh.mp4',
-            './eigth.mp4',
-            './ninth.mp4',
-            './tenth.mp4',
+            # './fourth.mp4',
+            # './fifth.mp4',
+            # './sixth.mp4',
+            # './seventh.mp4',
+            # './eigth.mp4',
+            # './ninth.mp4',
+            # './tenth.mp4',
             ]:
             tmp_df = pd.DataFrame(columns=['paths', 'embeddings', 'ips', 'user:rating', 'text', 'gemb'])
             tmp_df['paths'] = [im]
@@ -508,9 +508,9 @@ Explore the latent space without text prompts based on your preferences. Learn m
     './first.mp4',
     './second.mp4',
     './third.mp4',
-    './fourth.mp4',
-    './fifth.mp4',
-    './sixth.mp4',
+    # './fourth.mp4',
+    # './fifth.mp4',
+    # './sixth.mp4',
     ])
     def l():
         return None
@@ -573,7 +573,7 @@ scheduler.start()
 #thread.start()
 
 # TODO shouldn't call this before gradio launch, yeah?
-@spaces.GPU(duration=20)
+@spaces.GPU(duration=100)
 def encode_space(x, im):
     with torch.no_grad():
         print('encode')