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View Code? Open in Web Editor NEWA PyTorch implementation of the 1d and 2d Sinusoidal positional encoding/embedding.
A PyTorch implementation of the 1d and 2d Sinusoidal positional encoding/embedding.
https://github.com/wzlxjtu/PositionalEncoding2D/blob/master/positionalembedding2d.py#L16
dim_term = 1 / np.power(10000, (2 * (i//2)) / np.float32(d_model))
why not use the above code is clearer
can u clarify in a example of when we are tryin to train a model with 3 different attribute of length 10 with 8head attention which one is which?
Hi, I think this work for 2D positional encoding is beautiful and helpful for when dealing with image data. I wonder if the 2D positional encoding is your original work or from a published paper? Thanks a lot!
I know this is kind of a dumb question as original positional encoding was designed to be only applicable for even number of tokens. But still is there absolutely no way to solve this?
The layout of 2d is interleaving in the matrix.
However, I would like to ask whether 3D is applicable?
Thanks,
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