AVhI:dZddlmZddlmZddlmZddlmZddlmZddlmZejdd ejfd Z ejd d ejfd Z ejd ejddZejdd ejfdZejdd ejfdZdZejdd ejfdZy)z*Contains Gradient functions for image ops.)dtypes)ops) array_ops)array_ops_stack) gen_image_ops)math_opsResizeNearestNeighboropc0|jd}|jddjr|jdd}ntj|dd}t j |||jd|jd}|dgS)zThe derivatives for nearest neighbor resizing. Args: op: The ResizeNearestNeighbor op. grad: The tensor representing the gradient w.r.t. the output. Returns: The gradients w.r.t. the input and the output. r align_cornershalf_pixel_centersrrN)inputs get_shapeis_fully_definedrshaperresize_nearest_neighbor_gradget_attr)r gradimage image_shapegradss P/home/dcms/DCMS/lib/python3.12/site-packages/tensorflow/python/ops/image_grad.py_ResizeNearestNeighborGradrs ))A,% __q,,.//#Aa(K//%(1-K  4 4 KK0%9:  <% ResizeBilinearctj||jd|jd|jd}|dgS)zThe derivatives for bilinear resizing. Args: op: The ResizeBilinear op. grad: The tensor representing the gradient w.r.t. the output. Returns: The gradients w.r.t. the input. rrrrN)rresize_bilinear_gradrrr rgrad0s r_ResizeBilinearGradr#2sG  , , iilKK0%9:  <% rResizeBilinearGradScaleAndTranslatec tj||jd|jd|jd|jd|jd}|dddgS)zThe derivatives for ScaleAndTranslate transformation op. Args: op: The ScaleAndTranslate op. grad: The tensor representing the gradient w.r.t. the output. Returns: The gradients w.r.t. the input. rr kernel_type antialias)r(r)N)rscale_and_translate_gradrrr!s r_ScaleAndTranslateGradr+Hsa  0 0 iiliiliil++m, K(  *% tT ""r ResizeBicubicc tjtjg}d}|jdj|vrDt j ||jd|jd|jd}|dgS)zThe derivatives for bicubic resizing. Args: op: The ResizeBicubic op. grad: The tensor representing the gradient w.r.t. the output. Returns: The gradients w.r.t. the input. Nrrrr)rfloat32float64rdtyperresize_bicubic_gradr)r r allowed_typesr"s r_ResizeBicubicGradr3^st>>6>>2- %YYq\=(  - -  ! kk/2;;';<  >E r CropAndResizec |jd}|jjr|jj}nt j |}t jt jt jg}|jdj|vrTtj||jd|jd||jd|jd}nd}tj||jd|jd|jd}||ddgS)aThe derivatives for crop_and_resize. We back-propagate to the image only when the input image tensor has floating point dtype but we always back-propagate to the input boxes tensor. Args: op: The CropAndResize op. grad: The tensor representing the gradient w.r.t. the output. Returns: The gradients w.r.t. the input image, boxes, as well as the always-None gradients w.r.t. box_ind and crop_size. rr r'Tmethod)r6r7N)rrras_listrrrfloat16r.r/r0rcrop_and_resize_grad_imagercrop_and_resize_grad_boxes)r rrrr2r"grad1s r_CropAndResizeGradr=ts ))A,% __'')//#++-K//%(K>>6>>6>>B-YYq\=(  4 4 biilBIIaL+S9I{{8$ &E E  2 2 BIIaL"))A, !  6% d ##rcjtjtjd|j|S)zWrapper function around `math_ops.div_no_nan()` to perform a "safe" reciprocal incase the input is zero. Avoids divide by zero and NaNs. Input: x -> input tensor to be reciprocat-ed. Returns: x_reciprocal -> reciprocal of x without NaNs. g?)r div_no_nancastr0)xs r_CustomReciprocalrBs&   X]]38! < #$)+,u &= "#(*,==&D.e^"%&+-.--$VO!%&+-- % % % --q% (8<<HLL&!8-%:OPP(//$/012>2C/L54HIJ3K,L L% -- E *X\\hll<$#6 8MNN/012@22Et+ u0DEF3G.H H% -- 5 )HLLX\\.6"9<$;NOO(//%0123@23E/K$4FGH4I-J J%6 mmD1He${2R7 ~*8??:+FGH./0 1' mmFQJ&6E v~*8??4&=+IJK L' mmFQJ&6FK'( )' mmEAIu% 4|C v~*8??54<+HIJ K' mmEAIu% 4~E'( )' G g % /' 9% #+%. mmFQJ&6; t|()DEF./0 1' mmD1He${2^C e|()GHI J' mmD1He${2]Bu %& '' mmEAIu% 4~E e|()HIJ K' mmEAIu% 4|CbH %& '' G g % /' 9% #+%, mmEAIu% 4r9 f})(//**EFG./0 1' mmD1He${2]B })(//$,*GHI J' mmD1He${2^CbHv &' (' mmFQJ&6F })(//&5.*IJK L' mmFQJ&6E &' (' G g % /' 9% #+%  ! ! F|eT&\E14<%3GH  '  ! ! F|eT&\E14<%3GH  '  ! ! F|eT&\E14<%3GH  '<< Wg >H. rN)__doc__tensorflow.python.frameworkrrtensorflow.python.opsrrrrRegisterGradient Operationrr#NotDifferentiabler+r3r=rBrsrrr{s81.++1/*-.3==/0&'CMM($*+)*#+#*o&3=='*o&'$3=='$''$T=j!RcmmR"Rr