(k, dist)
return grouping_module.selection_sort(dist, k)
Input:
        k: int32, number of k SMALLEST elements selected
        dist: (b,m,n) float32 array, distance matrix, m query points, n dataset points
    Output:
        idx: (b,m,n) int32 array, first k in n are indices to the top k
        dist_out: (b,m,n) float32 array, first k in n are the top k
Input:
        k: int32, number of k SMALLEST elements selected
        dist: (b,m,n) float32 array, distance matrix, m query points, n dataset points
    Output:
        idx: (b,m,n) int32 array, first k in n are indices to the top k
        dist_out: (b,m,n) float32 array, first k in n are the top k
Input : k : int32 number of k SMALLEST elements selected dist : ( b m n ) float32 array distance matrix m query points n dataset points Output : idx : ( b m n ) int32 array first k in n are indices to the top k dist_out : ( b m n ) float32 array first k in n are the top k
def select_top_k(k, dist):
    """
    Input:
        k: int32, number of k SMALLEST elements selected
        dist: (b,m,n) float32 array, distance matrix, m query points, n dataset points
    Output:
        idx: (b,m,n) int32 array, first k in n are indices to the top k
        dist_out: (b,m,n) float32 array, first k in n are the top k
    """
    return grouping_module.selection_sort(dist, k)
def select_top_k ( k , dist ) : return grouping_module . selection_sort ( dist , k )