src/transformers/pipelines/text2text_generation.py/Text2TextGenerationPipeline/__call__
class Text2TextGenerationPipeline:    def __call__(self, *args, **kwargs):
        r"""
        Generate the output text(s) using text(s) given as inputs.

        Args:
            args (:obj:`str` or :obj:`List[str]`):
                Input text for the encoder.
            return_tensors (:obj:`bool`, `optional`, defaults to :obj:`False`):
                Whether or not to include the tensors of predictions (as token indices) in the outputs.
            return_text (:obj:`bool`, `optional`, defaults to :obj:`True`):
                Whether or not to include the decoded texts in the outputs.
            clean_up_tokenization_spaces (:obj:`bool`, `optional`, defaults to :obj:`False`):
                Whether or not to clean up the potential extra spaces in the text output.
            truncation (:obj:`TruncationStrategy`, `optional`, defaults to :obj:`TruncationStrategy.DO_NOT_TRUNCATE`):
                The truncation strategy for the tokenization within the pipeline.
                :obj:`TruncationStrategy.DO_NOT_TRUNCATE` (default) will never truncate, but it is sometimes desirable
                to truncate the input to fit the model's max_length instead of throwing an error down the line.
            generate_kwargs:
                Additional keyword arguments to pass along to the generate method of the model (see the generate method
                corresponding to your framework `here <./model.html#generative-models>`__).

        Return:
            A list or a list of list of :obj:`dict`: Each result comes as a dictionary with the following keys:

            - **generated_text** (:obj:`str`, present when ``return_text=True``) -- The generated text.
            - **generated_token_ids** (:obj:`torch.Tensor` or :obj:`tf.Tensor`, present when ``return_tensors=True``)
              -- The token ids of the generated text.
        """

        result = super().__call__(*args, **kwargs)
        if isinstance(result, dict):
            return [result]
        return result