o .wi @spddlmZddlZddlmZmZddlmZddlmZ d deded e d eee eeefffd d Z dS))UnionN)Tensorlinalg)_check_same_shape)rank_zero_warnF point_cloud1 point_cloud2 return_allreturnc Csrt|||jdkrtd|jd||jddd}||jddd}|tj|ddgdd}|tj|ddgdd}ztjt| dd| dddd \}}}Wn/t y}z#t d |d t t d t|jd t|jdfWYd}~Sd}~wwt||}|jddd}|dddft|| dd}||jddgd} |r| ||fS| S)aZRuns procrustrus analysis on a batch of data points. Works similar ``scipy.spatial.procrustes`` but for batches of data points. Args: point_cloud1: The first set of data points point_cloud2: The second set of data points return_all: If True, returns the scale and rotation matrices along with the disparity zExpected both datasets to be 3D tensors of shape (N, M, D), where N is the batch size, M is the number of data points and D is the dimensionality of the data points, but got z dimensions.T)dimkeepdimF) full_matricesz>SVD calculation in procrustes_disparity failed with exception z4. Returning 0 disparity and identity scale/rotation.grN)r)r )rndim ValueErrormeanrnormsvdtorchmatmul transpose Exceptionr UserWarningtensoronesshapeeyesumsquare) rrr uwvexrotationscale disparityr(e/home/ubuntu/sommelier/.venv/lib/python3.10/site-packages/torchmetrics/functional/shape/procrustes.pyprocrustes_disparitys<  4 $ r*)F) typingrrrrtorchmetrics.utilities.checksrtorchmetrics.utilities.printsrbooltupler*r(r(r(r)s