59 lines
1.8 KiB
Python
59 lines
1.8 KiB
Python
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from typing import List
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from mmpretrain.structures import DataSample
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class MplugOwlMMBenchPromptConstructor:
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"""Prompt constructor for MplugOwl on MMBench.
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Args:
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image_prompt (str): Image prompt. Defaults to `''`.
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reply_prompt (str): Reply prompt. Defaults to `''`.
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"""
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def __init__(self, image_prompt: str = '', reply_prompt: str = '') -> None:
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self.image_prompt = image_prompt
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self.reply_prompt = reply_prompt
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def __call__(self, inputs: dict) -> dict:
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"""Construct prompt.
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Args:
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inputs (dict): Input data containing image and data_samples.
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Returns:
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dict: A dict containing prompt, images and data_samples.
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"""
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data_samples = inputs['data_samples']
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prompt = self._process(data_samples)
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inputs.update({'prompt': prompt})
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return inputs
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def _process(self, data_samples: List[DataSample]) -> str:
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"""Process data sample to prompt.
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Args:
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data_samples (List[DataSample]): A list of data_samples.
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Returns:
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str: Prompt.
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"""
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question = [
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data_sample.get('question') for data_sample in data_samples
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]
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options = [data_sample.get('options') for data_sample in data_samples]
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if data_samples[0].get('context') is not None:
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context = [
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data_sample.get('context') for data_sample in data_samples
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]
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else:
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context = [''] * len(data_samples)
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prompts = []
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for cur_context, cur_question, cur_options in zip(
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context, question, options):
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prompts.append(cur_context + ' ' + cur_question + ' ' +
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cur_options) # noqa
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return prompts
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