:j lddlmZddlmZ d dedeedeedeeeeffdZd d ed eedefd Zy))Optional)TensorNxy zero_diagonalreturnc |jdk7rtd|j|@|jdk7s|jd|jdk7r td|dn|}n|j}|dn|}|||fS)a6Check that input has the right dimensionality and sets the ``zero_diagonal`` argument if user has not set it. Args: x: tensor of shape ``[N,d]`` y: if provided, a tensor of shape ``[M,d]`` zero_diagonal: determines if the diagonal of the distance matrix should be set to zero zBExpected argument `x` to be a 2D tensor of shape `[N, d]` but got zoExpected argument `y` to be a 2D tensor of shape `[M, d]` where `d` should be same as the last dimension of `x`FT)ndim ValueErrorshapeclone)rrrs }/home/mcse/projects/srt_converter/srt-converter-venv/lib/python3.12/site-packages/torchmetrics/functional/pairwise/helpers.py _check_inputrs vv{]^_^e^e]fghh} 66Q;!''!* 2C "/!6M GGI - 5= a distmat reductionc|dk(r|jdS|dk(r|jdS||dk(r|Std|)zReduction of distance matrix. Args: distmat: a ``[N,M]`` matrix reduction: string determining how to reduce along last dimension mean)dimsumnonez@Expected reduction to be one of `['mean', 'sum', None]` but got )rrr )rrs r_reduce_distance_matrixr.s]F|||##E{{r{""I/ WXaWbc ddr)NN)N) typingrtorchrbooltuplerstrrrrr"sqLP 6":B4. 664  6eVe eQWer