Fix issue

sdv/multi_table/base.py

@@ -341,18 +341,14 @@ def update_transformers(self, table_name, column_name_to_transformer):
     def _store_and_convert_original_cols(self, data):
         list_of_changed_tables = []
         for table, dataframe in data.items():
-            data_columns = dataframe.columns
-            col_name_mapping = {str(col): col for col in data_columns}
-            reverse_col_name_mapping = {col: str(col) for col in data_columns}
-            self._original_table_columns[table] = col_name_mapping
-            dataframe = dataframe.rename(columns=reverse_col_name_mapping)
-            for column in data_columns:
+            self._original_table_columns[table] = dataframe.columns
+            for column in dataframe.columns:
                 if isinstance(column, int):
+                    dataframe.columns = dataframe.columns.astype(str)
                     list_of_changed_tables.append(table)
                     break
 
             data[table] = dataframe
-
         return list_of_changed_tables
 
     def _transform_helper(self, data):
@@ -396,7 +392,7 @@ def preprocess(self, data):
                 raise e
 
         for table in list_of_changed_tables:
-            data[table] = data[table].rename(columns=self._original_table_columns[table])
+            data[table].columns = self._original_table_columns[table]
 
         return processed_data
 
@@ -481,6 +477,19 @@ def fit(self, data):
         processed_data = self.preprocess(data)
         self._print(text='\n', end='')
         self.fit_processed_data(processed_data)
+        from rdt.transformers import AnonymizedFaker
+        for table, synthesizer in self._table_synthesizers.items():
+            for column, transformer in synthesizer._data_processor._hyper_transformer.field_transformers.items():
+                if isinstance(transformer, AnonymizedFaker):
+                    new_seed = self._set_faker_seed(column, table)
+                    self._table_synthesizers[table]._data_processor._hyper_transformer.field_transformers[column].faker.seed_instance(new_seed)
+
+    def _set_faker_seed(self, column_name, table):
+        import hashlib
+        print(column_name, table)
+        hash_value = column_name + table
+        hash_value = int(hashlib.sha256(hash_value.encode('utf-8')).hexdigest(), 16)
+        return hash_value % ((2**32) - 1)  # maximum value for a seed
 
     def reset_sampling(self):
         """Reset the sampling to the state that was left right after fitting."""
@@ -528,16 +537,9 @@ def sample(self, scale=1.0):
             total_columns += len(table.columns)
 
         table_columns = getattr(self, '_original_table_columns', {})
-
         for table in sampled_data:
-            table_data = sampled_data[table][self.get_metadata().get_column_names(table)]
             if table in table_columns:
-                if isinstance(table_columns[table], dict):
-                    table_data = table_data.rename(columns=table_columns[table])
-                else:
-                    table_data.columns = table_columns[table]
-
-            sampled_data[table] = table_data
+                sampled_data[table].columns = table_columns[table]
 
         SYNTHESIZER_LOGGER.info({
             'EVENT': 'Sample',