Update dataset_utils.py

dataset_utils.py

@@ -246,59 +246,35 @@ def generate_deep(data,task,feat_cond,feat_proc,feat_out,feat_chart,feat_meds,fe
     stat = []
     demo = []
     
-    
     size_cond, size_proc, size_meds, size_out, size_chart, size_lab, eth_vocab,gender_vocab,age_vocab,ins_vocab=vocab(task.replace(" ","_"),feat_cond,feat_proc,feat_out,feat_chart,feat_meds,False)
     dyn,cond_df,demo=concat_data(data,task.replace(" ","_"),feat_cond,feat_proc,feat_out,feat_chart,feat_meds,feat_lab)
     if feat_chart:
         charts = dyn['CHART'].values
-        #charts=charts.to_numpy()
-        #charts = torch.tensor(charts, dtype=torch.long)
-        #charts = charts.tolist()
-        
+   
     if feat_meds:
         meds = dyn['MEDS'].values
 
     if feat_proc:
-        proc = dyn['PROC']
+        proc = dyn['PROC'].values
 
     if feat_out:
-        out = dyn['OUT']
+        out = dyn['OUT'].values
 
     if feat_lab:
-        lab = dyn['LAB']
+        lab = dyn['LAB'].values
 
     if feat_cond:
         stat=cond_df.values[0]
-        #stat = stat.to_numpy()
-        
-        #stat = torch.tensor(stat)
-        #if stat_df[0].nelement():
-        #    stat_df = torch.cat((stat_df,stat),0)
-        #else:
-        #    stat_df = stat 
-
-        #stat_df = torch.tensor(stat_df)
-        #stat_df = stat_df.type(torch.LongTensor)
-        #stat_df = stat_df.squeeze()
-
-        
+  
     y = int(demo['label'])
     
     demo["gender"].replace(gender_vocab, inplace=True)
     demo["ethnicity"].replace(eth_vocab, inplace=True)
     demo["insurance"].replace(ins_vocab, inplace=True)
     demo["Age"].replace(age_vocab, inplace=True)
-    demo=demo[["gender","ethnicity","insurance","Age"]]
-    demo = demo.values[0]
-    #demo = torch.tensor(demo)
-    #if demo_df[0].nelement():
-     #   demo_df = torch.cat((demo_df,demo),0)
-    #else:
-     #   demo_df = demo
-    #demo_df = torch.tensor(demo_df)
-    #demo_df = demo_df.type(torch.LongTensor)
-    #demo_df=demo_df.squeeze()
-
+    demo=demo["gender","ethnicity","insurance","Age"]
+    demo = demo.values
+    
     return stat, demo, meds, charts, out, proc, lab, y