Update Mimic4Dataset.py

Mimic4Dataset.py

@@ -473,11 +473,13 @@ def task_cohort(task, mimic_path, config_path):
     include=int(timeW.split()[1])
     bucket = config['timebucket']
     radimp = config['radimp']
+
     diag_flag = config['diagnosis']
     out_flag = config['output']
     chart_flag = config['chart']
     proc_flag= config['proc']
     med_flag = config['meds']
+
     disease_filter = config['disease_filter']
     icu_no_icu = config['icu_no_icu']
     groupingICD = config['groupingICD']
@@ -681,14 +683,10 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
         if not os.path.exists('./config'):
             os.makedirs('config')
         #save config file in config folder
-        conf='./config/'+file_path.split('/')[-1]
-        if not os.path.exists(conf):
+        self.conf='./config/'+file_path.split('/')[-1]
+        if not os.path.exists(self.conf):
             shutil.move(file_path,'./config')
-        with open(conf) as f:
-            config = yaml.safe_load(f)
-        feat_cond, feat_chart, feat_proc, feat_meds, feat_out = config['diagnosis'], config['chart'], config['proc'],  config['meds'], config['output']
-
-
+        
         #####################downloads modules from hub
         if not os.path.exists('./model/data_generation_icu_modify.py'):
             file_path, head = urlretrieve(_DATA_GEN, "data_generation_icu_modify.py")
@@ -731,7 +729,7 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
         with open(test_path, 'wb') as f:
             pickle.dump(test_dic, f)
 
-        return feat_cond, feat_chart, feat_proc, feat_meds, feat_out, dict_dir
+        return dict_dir
   
 ###########################################################RAW##################################################################
 
@@ -980,7 +978,10 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
     
 #############################################################################################################################
     def _info(self):
-        self.feat_cond, self.feat_chart, self.feat_proc, self.feat_meds, self.feat_out,self.path = self.create_cohort()
+        with open(self.conf) as f:
+            config = yaml.safe_load(f)
+        self.feat_cond, self.feat_chart, self.feat_proc, self.feat_meds, self.feat_out = config['diagnosis'], config['chart'], config['proc'],  config['meds'], config['output']
+        self.path = self.create_cohort()
         if self.encoding == 'onehot' :
             return self._info_encoded()