Explanation of “resample_patchemb” function in flexiViT

[lsjAI]

def resample_patchemb(old, new_hw):
  """Resample the weights of the patch embedding kernel to target resolution.

  We resample the patch embedding kernel by approximately inverting the effect
  of patch resizing. Colab with detailed explanation:
  (internal link)
  With this resizing, we can for example load a B/8 filter into a B/16 model
  and, on 2x larger input image, the result will match.
  See (internal link)
  Args:
    old: original parameter to be resized.
    new_hw: target shape (height, width)-only.
  Returns:
    Resized patch embedding kernel.
  """

Can you provide a link to a Colab that explains this function?