46 lines
1020 B
Python
46 lines
1020 B
Python
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_base_ = [
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'../_base_/datasets/refcoco.py',
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'../_base_/default_runtime.py',
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]
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# model settings
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model = dict(
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type='OFA',
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task='refcoco',
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vocab_size=59457,
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embedding_dim=768,
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encoder_cfg=dict(
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embed_images=dict(type='OFAResNet', depth=101),
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num_layers=6,
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),
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decoder_cfg=dict(num_layers=6),
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generation_cfg=dict(use_cache=True),
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tokenizer=dict(type='OFATokenizer', name_or_path='OFA-Sys/OFA-base'),
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)
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# data settings
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data_preprocessor = dict(
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type='MultiModalDataPreprocessor',
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mean=[127.5, 127.5, 127.5],
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std=[127.5, 127.5, 127.5],
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to_rgb=True,
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)
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test_pipeline = [
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dict(type='LoadImageFromFile'),
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dict(type='Resize', scale=(512, 512)),
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dict(
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type='PackInputs',
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algorithm_keys=['text', 'gt_bboxes'],
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meta_keys=['image_id', 'scale_factor'],
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),
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]
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train_dataloader = None
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test_dataloader = dict(dataset=dict(pipeline=test_pipeline))
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# schedule settings
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train_cfg = None
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val_cfg = dict()
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test_cfg = dict()
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