What is the function patches layer?

The function patches layer, often found in deep learning models, is used to divide input data (like images) into smaller, manageable sections or "patches." This allows the model to focus on localized features and patterns within the data, which can improve its ability to learn and make predictions. In vision Transformers, for instance, these patches are then flattened and linearly embedded to be processed further in the model. Overall, the patches layer enhances the model's efficiency and effectiveness in handling high-dimensional inputs.