code: def quantile_fi(input: torch.Tensor, q, epsilon):
      if input.dtype == torch.float64:
          if len(input.shape) == 1:
              return quantile.quantile_f64_ix1(
                  input.numpy(), q, epsilon
              )
          elif len(input.shape) == 2:
              return quantile.quantile_f64_ix2(
                  input.numpy(), q, epsilon
              )
      raise NotImplementedError()
  
file_path: FATE/python/fate/arch/tensor/inside/_op_quantile.py
imports: from typing import List, Union
  import numpy
  import torch
  from fate_utils import quantile
label_desc: Use image node_id 1 for calling a global function with example usage: quantile_fi(input, q, epsilon) and returns: quantile, quantile