code: def export_checkpoint(checkpoint_path):
      """
      Export variable tensors from the checkpoint files.
  
      :param checkpoint_path: tensorflow checkpoint path
      :return: dictionary of tensor. The key is the variable name and the value is the numpy
      """
      reader = tf.train.NewCheckpointReader(checkpoint_path)
  
      # Get tensor name list
      tensor_names = filter(
          lambda n: n != "global_step",
          reader.get_variable_to_shape_map().keys(),
      )
      # Prepare key-value dictionary
      tensors = {}
      for tn in tensor_names:
          tensors[tn] = reader.get_tensor(tn)
  
      return tensors
  
file_path: BigDL/python/dllib/src/bigdl/dllib/utils/tf_utils.py
imports: import tempfile
  import tensorflow
  import shutil
  from google.protobuf import text_format
  from tensorflow.core.framework import graph_pb2
  from tensorflow.python.client import session
  from tensorflow.python.framework import graph_util
  from tensorflow.python.framework import importer
  from tensorflow.python.platform import gfile
  from bigdl.dllib.nn.layer import Model
  from bigdl.dllib.utils.common import JTensor
  from bigdl.dllib.utils.common import callBigDlFunc
  from bigdl.dllib.utils.log4Error import *
  import os
label_desc: Use image node_id 3 for calling a global function with example usage: export_checkpoint(checkpoint_path) and returns: tensors