Input format for T5 model in Question Answering task

Hi, everyone. I am working with the T5 model for fine-tuning question-answering tasks with the custom dataset. My dataset contains 3 parts (question, question_context, answer_text). According to my understanding, we can encode the question + question_context into input_ids and feed it to the model, likewise, the answer_text will be labels for evaluating the model generation. I looked around the implementation of T5ForConditionalGeneration and realized that if the users input the labels and do not define the decoder_input_ids, they will assign it by the labels and shift it right for performing autoregressive internally. Here is the implementation for the code. However, in my case, I want to feed the model with the question as input_ids, question_context as decoder_input_ids, and answer_text as labels, so does the T5ForConditionalGeneration will shift right the decoder_input_ids for me internally or I have to do it by my self externally?

Hope you guys help me clear this situation. Thank you in advance!