from typing import List from mmpretrain.structures import DataSample class MiniGPT4MMBenchPromptConstructor: """Prompt constructor for MiniGPT-4 on MMBench. Args: image_prompt (str): Image prompt. reply_prompt (str): Reply prompt. """ def __init__(self, image_prompt: str = '', reply_prompt: str = '') -> None: self.image_prompt = image_prompt self.reply_prompt = reply_prompt def __call__(self, inputs: dict) -> dict: """Construct prompt. Args: inputs (dict): Input data containing image and data_samples. Returns: dict: A dict containing prompt, images and data_samples. """ data_samples = inputs['data_samples'] prompt = self._process(data_samples) inputs.update({'prompt': prompt}) return inputs def _process(self, data_samples: List[DataSample]) -> str: """Process data sample to prompt. Args: data_samples (List[DataSample]): A list of data_samples. Returns: str: Prompt. """ assert len(data_samples) == 1, 'Only support batch size 1.' questions = [ data_sample.get('question') for data_sample in data_samples ] options = [data_sample.get('options') for data_sample in data_samples] contexts = [data_sample.get('context') for data_sample in data_samples] question = questions[0] option = options[0] context = contexts[0] if context is not None: prompt = self.image_prompt + ' ' + context + ' ' + question + ' ' + option + ' ' + self.reply_prompt # noqa else: prompt = self.image_prompt + ' ' + question + ' ' + option + ' ' + self.reply_prompt # noqa return prompt