Update app.py

app.py

@@ -373,15 +373,15 @@ def start(_, calibrate_prompts, user_id, request: gr.Request):
         # prep our calibration videos
         for im in [
             './first.mp4',
-            # './second.mp4',
-            # './third.mp4',
-            # './fourth.mp4',
-            # './fifth.mp4',
-            # './sixth.mp4',
-            # './seventh.mp4',
-            # './eigth.mp4',
-            # './ninth.mp4',
-            # './tenth.mp4',
+            './second.mp4',
+            './third.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]
@@ -500,11 +500,11 @@ Explore the latent space without text prompts based on your preferences. Learn m
     # calibration videos -- this is a misnomer now :D
     calibrate_prompts = gr.State([
     './first.mp4',
-    # './second.mp4',
-    # './third.mp4',
-    # './fourth.mp4',
-    # './fifth.mp4',
-    # './sixth.mp4',
+    './second.mp4',
+    './third.mp4',
+    './fourth.mp4',
+    './fifth.mp4',
+    './sixth.mp4',
     ])
     def l():
         return None
@@ -567,7 +567,7 @@ scheduler.start()
 #thread.start()
 
 # TODO shouldn't call this before gradio launch, yeah?
-@spaces.GPU(duration=40)
+@spaces.GPU()
 def encode_space(x):
     print('encode')
     im_emb, _ = pipe.encode_image(
@@ -577,7 +577,7 @@ def encode_space(x):
     print('encoded')
     
     print('pali_enc')
-    im = torchvision.transforms.ToTensor()(x).to('cuda').unsqueeze(0)
+    im = torchvision.transforms.ToTensor()(x).unsqueeze(0)
     im = torch.nn.functional.interpolate(im, (224, 224))
     im = (im - .5) * 2
     gemb = pali.vision_tower(im.to(dtype)).last_hidden_state