Update README.md

README.md

@@ -22,7 +22,7 @@ def process_row(row: List, row_index: int):
   row_cell_values = []
   for cell_value in row:
       if isinstance(cell_value, int) or isinstance(cell_value, float):
-          cell_value = self.convert_engDigit_to_bengali(str(cell_value))
+          cell_value = convert_engDigit_to_bengali(str(cell_value))
           row_cell_values.append(str(cell_value))
       else:
           row_cell_values.append(cell_value)
@@ -35,7 +35,7 @@ def process_row(row: List, row_index: int):
 def process_table(table_content: Dict):
   table_str = process_header(table_content["header"]) + " "
   for i, row_example in enumerate(table_content["rows"]):
-      table_str += self.process_row(row_example, row_index=i + 1) + " "
+      table_str += process_row(row_example, row_index=i + 1) + " "
   return table_str.strip()
 
 # load the dataset
@@ -49,7 +49,7 @@ for sample in banglatableQA['train']:
   # create the input sequence: query + linearized input table
   table_content = {"header": list(input_table.columns)[1:], "rows": [list(row.values)[1:] for i, row in input_table.iterrows()]}
   linearized_inp_table = process_table(table_content)
-  linearized_output_table = process_table({"name": None, "header": [self.translate_column(col) for col in list(answer.columns)], 
+  linearized_output_table = process_table({"name": None, "header": [translate_column(col) for col in list(answer.columns)], 
                              "rows": [list(row.values) for i, row in answer.iterrows()]})
   source = query + " " + linearized_inp_table
   target = linearized_output_table