140 lines
4.9 KiB
Python
140 lines
4.9 KiB
Python
import importlib
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DEFAULT_IMAGE_TOKEN = '<image>'
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DEFAULT_IMAGE_PATCH_TOKEN = '<im_patch>'
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DEFAULT_IM_START_TOKEN = '<im_start>'
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DEFAULT_IM_END_TOKEN = '<im_end>'
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class LLaVABasePromptConstructor:
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"""Base prompt constructor for LLaVA.
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Args:
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conv_mode (str): Version control args for different version of LLaVA.
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mm_use_im_start_end (bool):
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Config arg. Use start and end token when build prompt or not.
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reply_prompt (str): Reply prompt added at the end. (Default: '')
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"""
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def __init__(self,
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conv_mode: str,
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mm_use_im_start_end: bool,
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reply_prompt: str = '') -> None:
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conversation = importlib.import_module('llava.conversation')
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self.conv_templates = conversation.conv_templates
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self.conv_mode = conv_mode
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self.mm_use_im_start_end = mm_use_im_start_end
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self.SeparatorStyle = conversation.SeparatorStyle
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self.reply_prompt = reply_prompt
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def __call__(self, inputs: dict) -> tuple:
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"""Construct prompt.
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Args:
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inputs (dict): Input data containing images and data_samples.
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Returns:
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tuple: A tuple containing prompt, images and data_samples.
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"""
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data_samples = inputs['data_samples']
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assert len(data_samples) == 1
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prompt = self._build_prompt(data_samples[0])
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if self.mm_use_im_start_end:
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prompt = (DEFAULT_IM_START_TOKEN + DEFAULT_IMAGE_TOKEN +
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DEFAULT_IM_END_TOKEN + '\n' + prompt)
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else:
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prompt = DEFAULT_IMAGE_TOKEN + '\n' + prompt # noqa
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conv = self.conv_templates[self.conv_mode].copy()
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conv.append_message(conv.roles[0], prompt)
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conv.append_message(conv.roles[1], None)
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output_prompt = conv.get_prompt()
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stop_str = conv.sep if conv.sep_style != self.SeparatorStyle.TWO else conv.sep2 # noqa
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return output_prompt, stop_str
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def _build_prompt(self, data_sample):
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return self.reply_prompt
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class LLaVAMMBenchPromptConstructor(LLaVABasePromptConstructor):
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"""MMBench prompt constructor for LLaVA.
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Args:
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conv_mode (str): Version control args for different version of LLaVA.
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mm_use_im_start_end (bool):
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Config arg. Use start and end token when build prompt or not.
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reply_prompt (str): Reply prompt added at the end. (Default: '')
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"""
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def __init__(self,
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conv_mode: str,
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mm_use_im_start_end: bool,
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reply_prompt: str = '') -> None:
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super().__init__(conv_mode, mm_use_im_start_end, reply_prompt)
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def _build_prompt(self, data_sample):
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question = data_sample.get('question')
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options = data_sample.get('options')
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context = data_sample.get('context')
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if context is not None:
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prompt = context + ' ' + question + ' ' + options
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else:
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prompt = question + ' ' + options
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prompt += self.reply_prompt
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return prompt
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class LLaVAVQAPromptConstructor(LLaVABasePromptConstructor):
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"""VQA prompt constructor for LLaVA.
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Args:
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conv_mode (str): Version control args for different version of LLaVA.
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mm_use_im_start_end (bool):
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Config arg. Use start and end token when build prompt or not.
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reply_prompt (str): Reply prompt added at the end. (Default: '')
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"""
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def __init__(self,
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conv_mode: str,
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mm_use_im_start_end: bool,
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reply_prompt: str = '') -> None:
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super().__init__(conv_mode, mm_use_im_start_end, reply_prompt)
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def _build_prompt(self, data_sample):
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prompt = data_sample.get('question')
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prompt += self.reply_prompt
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return prompt
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class LLaVAScienceQAPromptConstructor(LLaVABasePromptConstructor):
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"""ScienceQA prompt constructor for LLaVA.
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Args:
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conv_mode (str): Version control args for different version of LLaVA.
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mm_use_im_start_end (bool):
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Config arg. Use start and end token when build prompt or not.
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reply_prompt (str): Reply prompt added at the end. (Default: '')
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"""
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choice_mapping = {0: 'A', 1: 'B', 2: 'C', 3: 'D', 4: 'E', 5: 'F'}
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def __init__(self,
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conv_mode: str,
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mm_use_im_start_end: bool,
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reply_prompt: str = '') -> None:
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super().__init__(conv_mode, mm_use_im_start_end, reply_prompt)
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def _build_prompt(self, data_sample):
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question = data_sample.get('question')
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choices = data_sample.get('choices')
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choices = [
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f'({self.choice_mapping[i]}) ' + item
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for i, item in enumerate(choices)
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]
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choices = 'Choices: ' + ' '.join(choices) + '\n'
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context = 'Context: ' + data_sample.get('hint') + '\n'
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prompt = context + question + choices + self.reply_prompt
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return prompt
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