src/transformers/pipelines/text2text_generation.py/Text2TextGenerationPipeline/_forward
class Text2TextGenerationPipeline:    def _forward(self, model_inputs, **generate_kwargs):
        if self.framework == "pt":
            in_b, input_length = model_inputs["input_ids"].shape
        elif self.framework == "tf":
            in_b, input_length = tf.shape(model_inputs["input_ids"]).numpy()

        generate_kwargs["min_length"] = generate_kwargs.get("min_length", self.model.config.min_length)
        generate_kwargs["max_length"] = generate_kwargs.get("max_length", self.model.config.max_length)
        self.check_inputs(input_length, generate_kwargs["min_length"], generate_kwargs["max_length"])
        output_ids = self.model.generate(**model_inputs, **generate_kwargs)
        out_b = output_ids.shape[0]
        if self.framework == "pt":
            output_ids = output_ids.reshape(in_b, out_b // in_b, *output_ids.shape[1:])
        elif self.framework == "tf":
            output_ids = tf.reshape(output_ids, (in_b, out_b // in_b, *output_ids.shape[1:]))
        return {"output_ids": output_ids}