Update Mimic4Dataset.py

Mimic4Dataset.py

@@ -11,7 +11,7 @@ _DESCRIPTION = """\
 Dataset for mimic4 data, by default for the Mortality task.
 Available tasks are: Mortality, Length of Stay, Readmission, Phenotype.
 The data is extracted from the mimic4 database using this pipeline: 'https://github.com/healthylaife/MIMIC-IV-Data-Pipeline/tree/main'
-mimic path should have this form : 
+mimic path should have this form : "absolute/path/to/mimic4data/mimiciv/2.2"
 """
 
 _HOMEPAGE = "https://huggingface.co/datasets/thbndi/Mimic4Dataset"
@@ -142,20 +142,24 @@ class Mimic4Dataset(datasets.GeneratorBasedBuilder):
             self.config_path = './config/los.config'
         elif self.config_path is None and self.name == 'Mortality':
             self.config_path = './config/mortality.config'
-        repodir = os.getcwd()
-        path_bench = repodir+'/MIMIC-IV-Data-Pipeline-main'
+
         repo_url='https://github.com/healthylaife/MIMIC-IV-Data-Pipeline'
+        if os.path.exists(os.path.dirname(os.path.abspath('MIMIC-IV-Data-Pipeline-main'))):
+            path_bench = os.path.dirname(os.path.abspath('MIMIC-IV-Data-Pipeline-main'))+'/MIMIC-IV-Data-Pipeline-main'
+        else:
+            repodir = os.getcwd()
+            path_bench = repodir+'/MIMIC-IV-Data-Pipeline-main'
+            subprocess.run(["git", "clone", repo_url, path_bench])
+
         data_dir = path_bench + "/data/dataDic"
-        if not os.path.exists(path_bench):
-            #subprocess.run(["git", "clone", repo_url, path_bench])
-            print("Please clone the repo")
+        print(data_dir)
         #task_cohort(self.name,self.mimic_path, path_bench, self.config_path)
         return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_dir, "benchmark": path_bench}),
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_dir}),
         ]
 
 
-    def _generate_examples(self, filepath,benchmark):
+    def _generate_examples(self, filepath):
         with open(filepath, 'rb') as fp:
             dataDic = pickle.load(fp)
         for hid, data in dataDic.items():