Update Mimic4Dataset.py

Mimic4Dataset.py

@@ -274,7 +274,7 @@ def getXY_deep(data,task,feat_cond,feat_proc,feat_out,feat_chart,feat_meds):
     stat=stat.to_numpy()
     stat=stat.tolist()
 
-    y = demo['label']
+    y = int(demo['label'])
     
     demo["gender"].replace(gender_vocab, inplace=True)
     demo["ethnicity"].replace(eth_vocab, inplace=True)
@@ -366,7 +366,7 @@ def generate_split_deep(path,task,feat_cond,feat_chart,feat_proc, feat_meds, fea
     taskf=task.replace(" ","_")
     for hid, data in tqdm(X.iterrows(),desc='Encoding Splits Data for '+task+' task'):
         stat, demo, meds, chart, out, proc, lab, y = getXY_deep(data, taskf, feat_cond, feat_proc, feat_out, feat_chart,feat_meds)
-        X_dict[hid] = {'stat': stat, 'demo': demo, 'meds': meds, 'chart': chart, 'out': out, 'proc': proc, 'lab': lab, 'y': y}
+        X_dict[hid] = {'stat': stat, 'demo': demo, 'meds': meds, 'chart': chart, 'out': out, 'proc': proc, 'lab': lab, 'label': y}
         
     return X_dict
 
@@ -746,10 +746,10 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
         for i, row in df.iterrows():
             yield i, row.to_dict()
 ######################################################DEEP###############################################################
-    def _info_deep(self,X_encoded):
+    def _info_deep(self):
         features = datasets.Features(
             {
-                
+                "label": datasets.ClassLabel(num_classes=2,names=["0", "1"]),
                 "DEMO": datasets.Sequence(datasets.Sequence(datasets.Value("int32"))),
                 "COND" : datasets.Sequence(datasets.Sequence(datasets.Value("float64"))) ,
                 "MEDS" : datasets.Sequence(datasets.Sequence(datasets.Value("float64"))) ,
@@ -786,7 +786,7 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
                 out_features = data['out']
                 cond_features = data['stat']
                 demo= data['demo']
-                label = data['y']
+                label = data['label']
                 lab=data['lab']
 
                 yield int(key), {
@@ -826,7 +826,7 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
             with open(self.path+"/X_val_deep.pkl", 'wb') as f:
                 pickle.dump(X_val_deep, f)
 
-            return self._info_deep(X_train_deep)
+            return self._info_deep()
         
         else:
             return self._info_raw()