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from opencompass.multimodal.models.instructblip import (
InstructBlipMMBenchPromptConstructor, InstructBlipMMBenchPostProcessor)
# dataloader settings
val_pipeline = [
dict(type='mmpretrain.torchvision/Resize',
size=(224, 224),
interpolation=3),
dict(type='mmpretrain.torchvision/ToTensor'),
dict(type='mmpretrain.torchvision/Normalize',
mean=(0.48145466, 0.4578275, 0.40821073),
std=(0.26862954, 0.26130258, 0.27577711)),
dict(type='mmpretrain.PackInputs',
algorithm_keys=[
'question', 'category', 'l2-category', 'context', 'index',
'options_dict', 'options', 'split'
])
]
dataset = dict(type='opencompass.MMBenchDataset',
data_file='data/mmbench/mmbench_test_20230712.tsv',
pipeline=val_pipeline)
instruct_blip_dataloader = dict(batch_size=1,
num_workers=4,
dataset=dataset,
collate_fn=dict(type='pseudo_collate'),
sampler=dict(type='DefaultSampler',
shuffle=False))
# model settings
instruct_blip_model = dict(
type='blip2-vicuna-instruct',
prompt_constructor=dict(type=InstructBlipMMBenchPromptConstructor),
post_processor=dict(type=InstructBlipMMBenchPostProcessor),
freeze_vit=True,
low_resource=False,
llm_model='/path/to/vicuna-7b/',
sys_prompt= # noqa: E251
'###Human: What is the capital of China? There are several options:\nA. Beijing\nB. Shanghai\nC. Guangzhou\nD. Shenzhen\n###Assistant: A\n'
)
# evaluation settings
instruct_blip_evaluator = [
dict(
type='opencompass.DumpResults',
save_path= # noqa: E251
'work_dirs/instructblip_vicuna7b/instructblipvicuna_mmbench.xlsx')
]
instruct_blip_load_from = '/path/to/instruct_blip_vicuna7b_trimmed'
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