o yi @slddlmZmZddlmZ ddedeedeedeeeeffdd Zdd ed eedefd d ZdS))OptionalTuple)TensorNxy zero_diagonalreturncCs||jdkr td|j|dur-|jdks |jd|jdkr$td|dur*dn|}n |}|dur7dn|}|||fS)aICheck that input has the right dimensionality and sets the ``zero_diagonal`` argument if user has not provided import module. 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)rrrr\/home/ubuntu/.local/lib/python3.10/site-packages/torchmetrics/functional/pairwise/helpers.py _check_inputs  rdistmat reductioncCsJ|dkr |jddS|dkr|jddS|dus|dkr|Std|)zFinal reduction of distance matrix. Args: distmat: a ``[N,M]`` matrix reduction: string determining how to reduce along last dimension mean)dimsumNnonez@Expected reduction to be one of `['mean', 'sum', None]` but got )rrr )rrrrr_reduce_distance_matrix.s  r)NN)N) typingrrtorchrboolrstrrrrrrs