docstr: :param input: ndarray or list of ndarray or JTensor or list of JTensor.
  :return: (list of JTensor, isTable)
docstr_tok: [":","param","input",":","ndarray","or","list","of","ndarray","or","JTensor","or","list","of","JTensor",".",":","return",":","(","list","of","JTensor",",","isTable",")"]
code: def check_input(input):
      """
      :param input: ndarray or list of ndarray or JTensor or list of JTensor.
      :return: (list of JTensor, isTable)
      """
  
      def to_jtensor(i):
          if isinstance(i, np.ndarray):
              return JTensor.from_ndarray(i)
          elif isinstance(i, JTensor):
              return i
          else:
              invalidInputError(
                  False, "Error unknown input type %s" % type(i)
              )
  
      if type(input) is list:
          if len(input) == 0:
              invalidInputError(
                  False, "Error when checking: empty input"
              )
          return list(map(lambda i: to_jtensor(i), input)), True
      else:
          return [to_jtensor(input)], False
  
imports: import os
  import sys
  import tempfile
  import numpy
  import six
  from pyspark import RDD
  from bigdl.dllib.nn.layer import Layer
  from bigdl.dllib.utils.file_utils import JTensor
  from bigdl.dllib.nncontext import getOrCreateSparkContext
  from bigdl.dllib.utils.file_utils import callZooFunc
  from bigdl.dllib.feature.image import ImageSet
  from bigdl.orca.tfpark.tf_dataset import TFImageDataset, TFDataset
  import logging
  from bigdl.dllib.utils.utils import to_sample_rdd
  from bigdl.dllib.utils.log4Error import *
label_desc: Use image node_id 2 for calling the TFNet obj's underlying member method code with example usage: obj.check_input(input) and returns: list,  True, list,  False, JTensor, i