Update app.py

app.py

@@ -163,7 +163,6 @@ def generate_pali(n_embs):
             descs += f'Description: {decoded}\n'
         else:
             prompt = f'en {descs} Describe a new image that is similar.'
-            print(prompt)
             model_inputs = processor(text=prompt, images=torch.zeros(1, 3, 224, 224), return_tensors="pt")
             input_len = model_inputs["input_ids"].shape[-1]
             input_embeds = to_wanted_embs(emb, 
@@ -200,7 +199,6 @@ def generate_gpu(in_im_embs, prompt='the scene'):
 def generate(in_im_embs, prompt='the scene'):
     output, im_emb, gemb = generate_gpu(in_im_embs, prompt)
     nsfw =maybe_nsfw(output.frames[0][len(output.frames[0])//2])
-    print(prompt)
     name = str(uuid.uuid4()).replace("-", "")
     path = f"/tmp/{name}.mp4"
     
@@ -342,12 +340,6 @@ def background_next_image():
 
 def pluck_embs_ys(user_id):
     rated_rows = prevs_df[[i[1]['user:rating'].get(user_id, None) != None for i in prevs_df.iterrows()]]
-    #not_rated_rows = prevs_df[[i[1]['user:rating'].get(user_id, None) == None for i in prevs_df.iterrows()]]
-    #while len(not_rated_rows) == 0:
-    #    not_rated_rows = prevs_df[[i[1]['user:rating'].get(user_id, None) == None for i in prevs_df.iterrows()]]
-    #    rated_rows = prevs_df[[i[1]['user:rating'].get(user_id, None) != None for i in prevs_df.iterrows()]]
-    #    time.sleep(.01)
-    #    print('current user has 0 not_rated_rows')
     
     embs = rated_rows['embeddings'].to_list()
     ys = [i[user_id] for i in rated_rows['user:rating'].to_list()]
@@ -400,7 +392,6 @@ def choose(img, choice, calibrate_prompts, user_id, request: gr.Request):
         print('NSFW -- choice is disliked')
         choice = 0
     
-    print(prevs_df['paths'].to_list(), img)
     row_mask = [p.split('/')[-1] in img for p in prevs_df['paths'].to_list()]
     # if it's still in the dataframe, add the choice
     if len(prevs_df.loc[row_mask, 'user:rating']) > 0: