def create_position_ids_from_inputs_embeds(self, inputs_embeds):
        """ We are provided embeddings directly. We cannot infer which are padded so just generate
        sequential position ids.
        :param torch.Tensor inputs_embeds:
        :return torch.Tensor:
        """
        seq_length = shape_list(inputs_embeds)[1]

        position_ids = tf.range(self.padding_idx + 1, seq_length + self.padding_idx + 1, dtype=tf.int32)[tf.newaxis, :]
        return position_ids
 We are provided embeddings directly. We cannot infer which are padded so just generate
        sequential position ids.
        :param torch.Tensor inputs_embeds:
        :return torch.Tensor:
        
xtune/src/transformers/modeling_tf_roberta.py