a  d@s`ddlmZmZddlmZd eeeeeeeeefdddZd eeeeddd ZdS) )OptionalTuple)TensorN)xy zero_diagonalreturncCs||jdkrtd|j|durZ|jdks@|jd|jdkrHtd|durTdn|}n|}|durndn|}|||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 NzoExpected 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)rrrrq/var/www/html/stable-diffusion-webui/venv/lib/python3.9/site-packages/torchmetrics/functional/pairwise/helpers.py _check_inputs r)distmat reductionrcCsN|dkr|jddS|dkr(|jddS|dus8|dkr<|Std|dS)zReduction of distance matrix. Args: distmat: a ``[N,M]`` matrix reduction: string determining how to reduce along last dimension mean)ZdimsumNnonez@Expected reduction to be one of `['mean', 'sum', None]` but got )rrr )rrrrr_reduce_distance_matrix.s  r)NN)N) typingrrZtorchrboolrstrrrrrrs