I do not find the code for the following description
Given a concatenation of features Fin = fFigL i=1 from
L different levels in a feature pyramid, we can resize consecutive
level features towards the scale of the median level
feature using up-sampling or down-sampling. The re-scaled
feature pyramid can be denoted as a 4-dimensional tensor
F 2 RLHWC, where L represents the number of levels
in the pyramid, H, W, and C represent height, width,
and the number of channels of the median level feature respectively.
I do not find the code for the following description
Given a concatenation of features Fin = fFigL i=1 from L different levels in a feature pyramid, we can resize consecutive level features towards the scale of the median level feature using up-sampling or down-sampling. The re-scaled feature pyramid can be denoted as a 4-dimensional tensor F 2 RLHWC, where L represents the number of levels in the pyramid, H, W, and C represent height, width, and the number of channels of the median level feature respectively.