U h@s|ddlmZddlZddlmmZddlmZdeeeee dddZ de e e ed d d Z deee d ddZ dS))OptionalN)Tensorbilinear)img absolute_gridmode align_cornersc Cs||jdd\}}|jddgdd\}}d||dd}|dkrXd||dd}tj||gdd}tj||||dS)z_Same as torch's grid_sample, with absolute pixel coordinates instead of normalized coordinates.Ndim)rr)shapesplittorchcatF grid_sample) rrrrhwZxgridZygridZnormalized_gridrX/var/www/html/venv/lib/python3.8/site-packages/torchvision/models/optical_flow/_utils.pyrsrcpu) batch_sizerrdevicecCs^t|}tjtj||dtj||ddd}tj|ddddd}|d|dddS)N)rZij)Zindexingr rr r )rrZmeshgridZarangestackfloatrepeat)rrrrZcoordsrrrmake_coords_grids $r)up_maskfactorc Cs|j\}}}}||||}}|dkrB|tj|||fdddS||dd||||}tj|dd}tj||d dd ||ddd||} tj|| dd} | d dd dd d  ||||S)a,Upsample flow by the input factor (default 8). If up_mask is None we just interpolate. If up_mask is specified, we upsample using a convex combination of its weights. See paper page 8 and appendix B. Note that in appendix B the picture assumes a downsample factor of 4 instead of 8. NrT)sizerrr rr )Z kernel_sizepaddingr) rrZ interpolateviewrZsoftmaxZunfoldsumZpermuteZreshape) Zflowr!r"rZ num_channelsrrZnew_hZnew_wZupsampled_flowrrr upsample_flows&r+)rN)r)Nr )typingrrZtorch.nn.functionalnnZ functionalrrstrboolrintrr+rrrrs