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a4d6840739
* add otter model for opencompass mmbench * add docs * add readme docs * debug for otter opencomass eval * delete unused folders * change to default data path * remove unused files * remove unused files * update * update config file * flake8 lint formated and add prompt generator * add prompt generator to config * add a specific postproecss * add post processor * add post processor * add post processor * update according to suggestions * remove unused redefinition
44 lines
1.4 KiB
Python
44 lines
1.4 KiB
Python
# dataloader settings
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from opencompass.multimodal.models.otter import (
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OTTERMMBenchPromptConstructor, OTTERMMBenchPostProcessor)
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val_pipeline = [
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dict(type="mmpretrain.torchvision/Resize", size=(224, 224), interpolation=3),
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dict(type="mmpretrain.torchvision/ToTensor"),
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dict(
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type="mmpretrain.torchvision/Normalize",
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mean=(0.48145466, 0.4578275, 0.40821073),
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std=(0.26862954, 0.26130258, 0.27577711),
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),
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dict(
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type="mmpretrain.PackInputs",
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algorithm_keys=["question", "answer", "options", "category", "l2-category", "context", "index", "options_dict"],
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),
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]
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dataset = dict(
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type="opencompass.MMBenchDataset", data_file="/path/to/mmbench/mmbench_test_20230712.tsv", pipeline=val_pipeline
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)
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otter_9b_mmbench_dataloader = dict(
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batch_size=1,
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num_workers=4,
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dataset=dataset,
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collate_fn=dict(type="pseudo_collate"),
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sampler=dict(type="DefaultSampler", shuffle=False),
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)
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# model settings
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otter_9b_mmbench_model = dict(
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type="otter-9b",
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model_path="/path/to/OTTER-Image-MPT7B/", # noqa
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load_bit="bf16",
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prompt_constructor=dict(type=OTTERMMBenchPromptConstructor,
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model_label='GPT',
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user_label='User'),
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post_processor=dict(type=OTTERMMBenchPostProcessor)
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)
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# evaluation settings
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otter_9b_mmbench_evaluator = [dict(type="opencompass.DumpResults", save_path="work_dirs/otter-9b-mmbench.xlsx")]
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