Add

tabs/data_viz_tab.py

@@ -247,7 +247,7 @@ def proximite():
     tokens = []
 
     nb_words = st.slider(tr('Nombre de mots à afficher')+' :',10,50, value=20)
-    df = pd.read_csv('../data/dict_we_en_fr',header=0,index_col=0, encoding ="utf-8", keep_default_na=False)
+    df = pd.read_csv(dataPath+'/data/dict_we_en_fr',header=0,index_col=0, encoding ="utf-8", keep_default_na=False)
     words_en = df.index.to_list()[:nb_words]
     words_fr = df['Francais'].to_list()[:nb_words]
 

tabs/game_tab.py

@@ -133,7 +133,7 @@ def run():
             stat = top_stats[k]
             print("%s memory blocks: %.1f KiB" % (stat.count, stat.size / 1024))
             for line in stat.traceback.format():
-                print(line)
+                print('   >'+line)
         total_mem = sum(stat.size for stat in top_stats)
         print("Total allocated size: %.1f KiB" % (total_mem / 1024))
         return

tabs/id_lang_tab.py

@@ -98,7 +98,7 @@ def init_dl_identifier():
     list_lan = read_list_lan()
     lan_identified = [lan_to_language[l] for l in list_lan]
     label_encoder.fit(list_lan)
-    merge = Merge(dataPath+"/dl_id_lang_split",  "../data", "dl_tiktoken_id_language_model.h5").merge(cleanup=False)
+    merge = Merge(dataPath+"/dl_id_lang_split",  dataPath, "dl_tiktoken_id_language_model.h5").merge(cleanup=False)
     dl_model = keras.models.load_model(dataPath+"/dl_tiktoken_id_language_model.h5")
     return dl_model, label_encoder, list_lan, lan_identified
 

tabs/modelisation_seq2seq_tab.py

@@ -413,8 +413,8 @@ def run():
                 """)
                 , unsafe_allow_html=True)
         st.write("<center><h5>"+tr("Architecture du modèle utilisé")+":</h5>", unsafe_allow_html=True)
-        plot_model(translation_model, show_shapes=True, show_layer_names=True, show_layer_activations=True,rankdir='TB',to_file='../images/model_plot.png')
-        st.image('../images/model_plot.png',use_column_width=True)
+        plot_model(translation_model, show_shapes=True, show_layer_names=True, show_layer_activations=True,rankdir='TB',to_file=st.session_state.ImagePath+'/model_plot.png')
+        st.image(st.session_state.ImagePath+'/model_plot.png',use_column_width=True)
         st.write("</center>", unsafe_allow_html=True)