code: def convert_tf_pad_to_onnx(pads):
      pads = np.reshape(pads, -1).tolist()
      dims = len(pads)
      assert dims % 2 == 0
      ret = []
      for idx in range(0, dims, 2):
          ret.append(pads[idx])
      for idx in range(1, dims, 2):
          ret.append(pads[idx])
      return ret
  
file_path: MMdnn/mmdnn/conversion/common/utils.py
imports: from __future__ import division
  import os
  import sys
  import numpy
  from six import text_type, binary_type, integer_types
  import mmdnn.conversion.common.IR.graph_pb2
label_desc: Use image node_id 3 for calling a global function with example usage: convert_tf_pad_to_onnx(pads) and returns: ret