docs: def single_lf_summary(Y_p, Y=None):
      """Calculates coverage, overlap, conflicts, and accuracy for a single LF
  
      Args:
          Y_p: a np.array or torch.Tensor of predicted labels
          Y: a np.array or torch.Tensor of true labels (if known)
      """
      L = sparse.csr_matrix(arraylike_to_numpy(Y_p).reshape(-1, 1))
      return lf_summary(L, Y)