Adding the "force_extract" feature.

hupd.py

@@ -81,6 +81,7 @@ class PatentsConfig(datasets.BuilderConfig):
         query_string: str = None,
         val_set_balancer=False,
         uniform_split=False,
+        force_extract=False,
         **kwargs
     ):
         """
@@ -99,6 +100,7 @@ class PatentsConfig(datasets.BuilderConfig):
             train_filing_end_date: End date for patents in train set
             val_filing_start_date: Start date for patents in val set
             val_filing_end_date: End date for patents in val set (and train set if random split is used)
+            force_extract: Extract only the relevant years if this parameter is used.
             **kwargs: keyword arguments forwarded to super
         """
         super().__init__(**kwargs)
@@ -114,6 +116,7 @@ class PatentsConfig(datasets.BuilderConfig):
         self.query_string = query_string
         self.val_set_balancer = val_set_balancer
         self.uniform_split = uniform_split
+        self.force_extract = force_extract
 
 
 class Patents(datasets.GeneratorBasedBuilder):
@@ -198,6 +201,29 @@ class Patents(datasets.GeneratorBasedBuilder):
         # Filter metadata based on arbitrary query string
         if self.config.query_string:
             df = df.query(self.config.query_string)
+            
+        if self.config.force_extract:
+            if self.config.name == 'all':
+                if self.config.train_filing_start_date and self.config.val_filing_end_date:
+                    if self.config.train_filing_end_date and self.config.val_filing_start_date:
+                        training_year_range = set(range(int(self.config.train_filing_start_date[:4]), int(self.config.train_filing_end_date[:4]) + 1))
+                        validation_year_range = set(range(int(self.config.val_filing_start_date[:4]), int(self.config.val_filing_end_date[:4]) + 1))
+                        full_year_range = training_year_range.union(validation_year_range)
+                    else:
+                        full_year_range = set(range(int(self.config.train_filing_start_date[:4]), int(self.config.val_filing_end_date[:4]) + 1))
+                else:
+                    full_year_range = set(range(2004, 2019))
+                
+
+                import tarfile
+                for year in full_year_range:
+                    tar_file_path = f'{json_dir}/{year}.tar.gz'
+                    print(f'Extracting {tar_file_path}')
+                    # open file
+                    tar_file = tarfile.open(tar_file_path)
+                    # extracting file
+                    tar_file.extractall(f'{json_dir}')
+                    tar_file.close()    
 
         # Train-validation split (either uniform or by date)
         if self.config.uniform_split:
@@ -291,7 +317,7 @@ class Patents(datasets.GeneratorBasedBuilder):
             decision = x.decision
             yield id_, {
                 "patent_number": application_number,
-                "decision": decision,
+                "decision": patent["decision"], # decision,
                 "title": patent["title"],
                 "abstract": patent["abstract"],
                 "claims": patent["claims"],