mmpretrain/configs/ofa/ofa-base_finetuned_caption.py

42 lines
942 B
Python

_base_ = [
'../_base_/datasets/coco_caption.py',
'../_base_/default_runtime.py',
]
# model settings
model = dict(
type='OFA',
task='caption',
vocab_size=59457,
embedding_dim=768,
encoder_cfg=dict(
embed_images=dict(type='OFAResNet', depth=101),
num_layers=6,
),
decoder_cfg=dict(num_layers=6),
generation_cfg=dict(use_cache=True),
tokenizer=dict(type='OFATokenizer', name_or_path='OFA-Sys/OFA-base'),
)
# data settings
data_preprocessor = dict(
type='MultiModalDataPreprocessor',
mean=[127.5, 127.5, 127.5],
std=[127.5, 127.5, 127.5],
to_rgb=True,
)
test_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='Resize', scale=(480, 480)),
dict(type='PackInputs', meta_keys=('image_id', )),
]
train_dataloader = None
test_dataloader = dict(dataset=dict(pipeline=test_pipeline))
# schedule settings
train_cfg = None
val_cfg = dict()
test_cfg = dict()