class_docstr: a Transformer that converts an Array[_] or Seq[_] or ML Vector to several tensors.
  :param size, list of int list, dimensions of target Tensors, e.g. [[2],[4]]
class_docstr_tok: ["a","Transformer","that","converts","an","Array","[","_","]","or","Seq","[","_","]","or","ML","Vector","to","several","tensors",".",":","param","size",",","list","of","int","list",",","dimensions","of","target","Tensors",",","e.g",".","[","[","2","]",",","[","4","]","]"]
code: def __init__(self, size=[], bigdl_type="float"):
      super(SeqToMultipleTensors, self).__init__(bigdl_type, size)
  
imports: from bigdl.util.common import *
  from zoo.common.utils import callZooFunc
  from bigdl.dataset.dataset import DataSet
  from pyspark.serializers import CloudPickleSerializer
  import sys
  import math
  import warnings
label_desc: Use image node_id 1 to create a new SeqToMultipleTensors object from inherited base classes: Preprocessing with example: obj = SeqToMultipleTensors(size, bigdl_type)