transformed_batch[c] = [None] * len(transformed_batch[first_col])
                    transformed_batch = self.features.decode_batch(transformed_batch)
                # the new key is the concatenation of the examples keys from the batch
                new_key = "_".join(str(key) for key in keys)
                # yield one example at a time from the transformed batch
                for example in _batch_to_examples(transformed_batch):
                    current_idx += 1
                    if self._state_dict:
                        self._state_dict["num_examples_since_previous_state"] += 1
                    if num_examples_to_skip > 0:
                        num_examples_to_skip -= 1
                        continue
                    yield new_key, example
                if self._state_dict:
                    self._state_dict["previous_state"] = self.ex_iterable.state_dict()
                    self._state_dict["num_examples_since_previous_state"] = 0