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Official repository of OFA (ICML 2022). Paper: OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework

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Requirements

  • python 3.7.4
  • pytorch 1.8.1
  • torchvision 0.9.1
  • JAVA 1.8 (for COCO evaluation)

Installation

pip install -r requirements.txt



Evaluate on Visual Question Answering

Data are released here

To run the evaluate code of inference:

To get a fast but not that accuracy:

cd run_scripts/vqa
bash evaluate_vqa_beam.sh val # specify 'val' or 'test'

For the best evaluation result at the cost of much slower speed:

# run on each worker after the distributed configs have been correctly set following the guide in evaluate_vqa_allcand_distributed.sh
cd run_scripts/vqa
bash evaluate_vqa_allcand_distributed.sh val # specify 'val' or 'test'



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Official repository of OFA (ICML 2022). Paper: OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework

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