src/transformers/pipelines/image_to_text.py/ImageToTextPipeline/_forward
class ImageToTextPipeline:    def _forward(self, model_inputs, generate_kwargs=None):
        if generate_kwargs is None:
            generate_kwargs = {}
        # FIXME: We need to pop here due to a difference in how `generation.py` and `generation.tf_utils.py`
        #  parse inputs. In the Tensorflow version, `generate` raises an error if we don't use `input_ids` whereas
        #  the PyTorch version matches it with `self.model.main_input_name` or `self.model.encoder.main_input_name`
        #  in the `_prepare_model_inputs` method.
        inputs = model_inputs.pop(self.model.main_input_name)
        model_outputs = self.model.generate(inputs, **model_inputs, **generate_kwargs)
        return model_outputs