44 lines
924 B
Python
44 lines
924 B
Python
_base_ = [
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'../_base_/datasets/coco_vqa.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='vqa',
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vocab_size=59457,
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embedding_dim=1024,
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encoder_cfg=dict(
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embed_images=dict(type='OFAResNet', depth=152),
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num_layers=12,
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num_heads=16,
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),
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decoder_cfg=dict(
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num_layers=12,
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num_heads=16,
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),
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generation_cfg=dict(
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num_beams=20,
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max_new_tokens=200,
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length_penalty=0., # VQA doesn't require longer answer.
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use_cache=True,
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),
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tokenizer=dict(type='OFATokenizer', name_or_path='OFA-Sys/OFA-large'),
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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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train_dataloader = None # Eval only
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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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