

 BridgeTower architecture. Taken from the original paper. 
This model was contributed by Anahita Bhiwandiwalla, Tiep Le and Shaoyen Tseng. The original code can be found here.
Usage tips and examples
BridgeTower consists of a visual encoder, a textual encoder and cross-modal encoder with multiple lightweight bridge layers.
The goal of this approach was to build a bridge between each uni-modal encoder and the cross-modal encoder to enable comprehensive and detailed interaction at each layer of the cross-modal encoder.
In principle, one can apply any visual, textual or cross-modal encoder in the proposed architecture.
The [BridgeTowerProcessor] wraps [RobertaTokenizer] and [BridgeTowerImageProcessor] into a single instance to both
encode the text and prepare the images respectively.
The following example shows how to run contrastive learning using [BridgeTowerProcessor] and [BridgeTowerForContrastiveLearning].
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