Update modelisation_seq2seq_tab.py

tabs/modelisation_seq2seq_tab.py

@@ -275,7 +275,7 @@ n1 = 0
 df_data_en, df_data_fr, translation_en_fr, translation_fr_en, lang_classifier, model_speech, rnn_en_fr, rnn_fr_en,\
     transformer_en_fr, transformer_fr_en, finetuned_translation_en_fr = load_all_data() 
 
-'''
+
 def display_translation(n1, Lang,model_type):
     global df_data_src, df_data_tgt, placeholder
     
@@ -305,43 +305,7 @@ def display_translation(n1, Lang,model_type):
     with placeholder:
         st.write("<p style='text-align:center;background-color:red; color:white')>Score Bleu = "+str(int(round(corpus_bleu(s_trad,[s_trad_ref]).score,0)))+"%</p>", \
             unsafe_allow_html=True)
-'''
-'''
-def display_translation(n1, Lang,model_type):
-    global df_data_src, df_data_tgt, placeholder
-    
-    async def decode_seq_all(model_type,s, target):
-        s_trad = []
-        for i in range(3):      
-            params = {"lang_tgt": target, "texte": s[i]}
-            if model_type==1:
-                # URL de votre endpoint FastAPI avec les paramètres de requête
-                url = "https://demosthene-or-api-avr23-cds-translation.hf.space/small_vocab/rnn"
-            else:
-                # URL de votre endpoint FastAPI avec les paramètres de requête
-                url = "https://demosthene-or-api-avr23-cds-translation.hf.space/small_vocab/transformer"
 
-            # Envoie d'une requête GET avec les paramètres de requête
-            await  s_trad.append(requests.get(url, params=params).json())
-        # await (len(s_trad) == 3)
-        return s_trad
-            
-    placeholder = st.empty()
-    with st.status(":sunglasses:", expanded=True):
-        s = df_data_src.iloc[n1:n1+5][0].tolist()
-        s_trad = []
-        s_trad_ref = df_data_tgt.iloc[n1:n1+5][0].tolist()
-        source = Lang[:2]
-        target = Lang[-2:]
-        s_trad = decode_seq_all(model_type,s, target)
-        for i in range(3):
-            st.write("**"+source+"   :**  :blue["+ s[i]+"]")
-            st.write("**"+target+"   :**  "+s_trad[i])
-            st.write("**ref. :** "+s_trad_ref[i])
-            st.write("")
-    with placeholder:
-        st.write("<p style='text-align:center;background-color:red; color:white')>Score Bleu = "+str(int(round(corpus_bleu(s_trad,[s_trad_ref]).score,0)))+"%</p>", \
-            unsafe_allow_html=True)
 '''
 async def fetch_translation(url, params):
     a = str(time.time())
@@ -387,7 +351,7 @@ async def display_translation(n1, Lang, model_type):
     with placeholder:
         st.write("<p style='text-align:center;background-color:red; color:white')>Score Bleu = "+str(int(round(corpus_bleu(s_trad,[s_trad_ref]).score,0)))+"%</p>", \
             unsafe_allow_html=True)
-
+'''
 
         
 @st.cache_data        
@@ -493,15 +457,15 @@ def run():
         if (chosen_id == "tab1"):
             t0 = time.time()
             # Exécuter la fonction asynchrone
-            asyncio.run(display_translation(n1, Lang, 1))
-            # display_translation(n1, Lang,1)
+            # asyncio.run(display_translation(n1, Lang, 1))
+            display_translation(n1, Lang,1)
             t1 = time.time()
             st.write("Durée: "+str(t1-t0))
         else: 
             t0 = time.time()
             # Exécuter la fonction asynchrone
-            asyncio.run(display_translation(n1, Lang, 2))
-            # display_translation(n1, Lang,2)
+            # asyncio.run(display_translation(n1, Lang, 2))
+            display_translation(n1, Lang,2)
             t1 = time.time()
             st.write("Durée: "+str(t1-t0))