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DF KK!+VaZ ?E EVaZ'ekk):A>A [[%!)+UQY BF KK*EAIu =E EUQY&U[[(91=A UB UB rB rB    eU #B eV $B fe $B ff %BK B B B B B B B B r'BG b2g %R /C Jr"ctjr9|jr-|jtjk7r|j S|Sr)ris_autocast_enabledis_cudar=doublefloat)tensors r maybe_castrYes4   "v~~&,,%,,:V||~ r"T)dynamicc |j}t|}t|}|j\}}} } tj||j } tj||j } |dddfj } |rdnd}|dddf|z|z }|dddf|z|z }|dddf|z|z }|dddf|z|z }||z }||z }|s.tj|d }tj|d }||z }||z }|dkD}|r|ntj||z }|r|ntj||z } |rVt||zd}tj||j }tj||j }d}d}ntj||zd }tj| |j }tj| |j }|dddf|dddfk}|dddf|dddfk}d }||| ddddf||zz|ddddfdzj|j|||z zz} ||| ddddf||zz|ddddfdzj|j|||z zz}!t|| | |!||}"|sHtj|ddddddddf|"d}"tj|ddddddddf|"d}"|"jd }#t|tjr|#|dddddfz}#n|#|z}#|#j|}#|#S) Nr+rg?grr r)r'c|ddddfSrr$)ts r from_Kz_roi_align..from_KsD$r"))r=rYr9rr.r,r;r:ceilmaxr<rRr-sum isinstancer)$r2rois spatial_scale pooled_height pooled_widthsampling_ratioaligned orig_dtyper>r?r@phpwr3offset roi_start_w roi_start_h roi_end_w roi_end_h roi_width roi_height bin_size_h bin_size_wexact_samplingroi_bin_grid_hroi_bin_grid_wcountiyixr5r4r`r/r0rQoutputs$ r _roi_alignrrsJ u E d D**,Aq&% mELL 9B l5<< 8B AJNN$MSFq!t*},v5Kq!t*},v5KQT ]*V3IQT ]*V3IK'I[(J KK s3 [[5 m+J\)J#a'N'5^5::jS`F`;aN'5^5::iR^F^;_NN^3Q7 \\. > \\. > N^;C \\& 6 \\% 547 nQW5547 nQW55  { T1d] fZ0 0 1 dD!m s " & &u{{ 3fZ.=X6Y Y Z { T1d] fZ0 0 1 dD!m s " & &u{{ 3fZ.=X6Y Y Z }aE5 IC kk%4tQ <=sAFkk%4tT1 <=sAF WWX F%&%4t+,,% YYz "F Mr"r2boxes output_sizerhrkrlreturnc tjjs-tjjst t t ||}t|}t|tjs t|}tjjsxtr8tjrZ|js|js |jr6t!|j"j$rt'||||d|d||St)tj*j,j ||||d|d||S)aj Performs Region of Interest (RoI) Align operator with average pooling, as described in Mask R-CNN. Args: input (Tensor[N, C, H, W]): The input tensor, i.e. a batch with ``N`` elements. Each element contains ``C`` feature maps of dimensions ``H x W``. If the tensor is quantized, we expect a batch size of ``N == 1``. boxes (Tensor[K, 5] or List[Tensor[L, 4]]): the box coordinates in (x1, y1, x2, y2) format where the regions will be taken from. The coordinate must satisfy ``0 <= x1 < x2`` and ``0 <= y1 < y2``. If a single Tensor is passed, then the first column should contain the index of the corresponding element in the batch, i.e. a number in ``[0, N - 1]``. If a list of Tensors is passed, then each Tensor will correspond to the boxes for an element i in the batch. output_size (int or Tuple[int, int]): the size of the output (in bins or pixels) after the pooling is performed, as (height, width). spatial_scale (float): a scaling factor that maps the box coordinates to the input coordinates. For example, if your boxes are defined on the scale of a 224x224 image and your input is a 112x112 feature map (resulting from a 0.5x scaling of the original image), you'll want to set this to 0.5. Default: 1.0 sampling_ratio (int): number of sampling points in the interpolation grid used to compute the output value of each pooled output bin. If > 0, then exactly ``sampling_ratio x sampling_ratio`` sampling points per bin are used. If <= 0, then an adaptive number of grid points are used (computed as ``ceil(roi_width / output_width)``, and likewise for height). Default: -1 aligned (bool): If False, use the legacy implementation. If True, pixel shift the box coordinates it by -0.5 for a better alignment with the two neighboring pixel indices. This version is used in Detectron2 Returns: Tensor[K, C, output_size[0], output_size[1]]: The pooled RoIs. rr)rjit is_scripting is_tracingr roi_alignrr rfrrr $are_deterministic_algorithms_enabledrUis_mpsis_xpurr,typerr ops torchvision)r2rrrhrkrlrgs r rrsR 99 ! ! #EII,@,@,BI&% D $K dELL )*40 99 ! ! # ::<%--SXS_S_chcoco"5<<#4#45eT=+a.+VW.Zhjqr r 99 * * t]KNKNNT[ r"c neZdZdZ d deedededeffd Zde de e e e fd e fd Z d e fd ZxZS) RoIAlignz See :func:`roi_align`. rrhrkrlcpt|t|||_||_||_||_yr)super__init__r rrhrkrl)selfrrhrkrl __class__s r rzRoIAlign.__init__ s7 D!&*, r"r2rgrcrt|||j|j|j|jSr)rrrhrkrl)rr2rgs r forwardzRoIAlign.forwards0d&6&68J8JDL_L_aeamamnnr"c |jjd|jd|jd|jd|j d }|S)Nz (output_size=z, spatial_scale=z, sampling_ratio=z , aligned=))rrrrhrkrl)rss r __repr__zRoIAlign.__repr__s^~~&&'(++,t112 3 34   r")F)r __module__ __qualname____doc__rr;rWboolrrrrrstrr __classcell__)rs@r rrsu &s+     oVo5f1E+Fo6o # r"r)r)raF)"rtypingrrrtorch.fxrrtorch._dynamo.utilsrtorch.jit.annotationsrtorch.nn.modules.utilsr torchvision.extensionr r utilsr _utilsrrr%rRrYrfxwrapr;rWrrModulerr$r"r rs 43(;'F&=DdUUp  8 8 f% &8#3'8 8  8  8 88vryyr"