The input dimension of self-attention
dimensional images, for example, I want to input two-dimensional images composed of two sequences
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Hi,
If you want to apply self-attention to two-dimensional images composed of two sequences, you can reshape the image into a single sequence and then apply the self-attention mechanism. Here’s a general approach to accomplish this in MATLAB:
- Convert the two-dimensional images into sequences: If your two-dimensional images consist of two sequences, you can reshape each image into a single sequence. For example, if the image dimensions are M rows and N columns, you can reshape it into a sequence of length M*N.
- Apply self-attention to the reshaped sequences: Once you have reshaped the images into sequences, you can apply the self-attention mechanism. MATLAB does not provide a built-in function specifically for self-attention, but you can implement it using custom code or by utilizing deep learning frameworks like TensorFlow or PyTorch.
Here’s a high-level example of how you can implement self-attention for two-dimensional images composed of two sequences using TensorFlow in MATLAB:
% Import TensorFlow for MATLAB
import tensorflow.*% Reshape the images into sequences
sequence1 = reshape(image1, [], 1);
sequence2 = reshape(image2, [], 1);% Concatenate the sequences along the feature dimension
sequences = cat(2, sequence1, sequence2);
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