class_docstr: Splits a repeated message field on a proto.
class_docstr_tok: ["Splits","a","repeated","message","field","on","a","proto","."]
docstr: Initializer.
docstr_tok: ["Initializer","."]
code: def __init__(
      self,
      proto,
      repeated_field: util.FieldTypes,
      message_splitters: Sequence[Type[SplitBasedOnSize]],
      **kwargs,
  ):
      """Initializer."""
      super().__init__(proto, **kwargs)
      if not isinstance(repeated_field, list):
          repeated_field = [repeated_field]
      self.repeated_field = repeated_field
      self.message_splitters = message_splitters
  
imports: from collections.abc import Sequence
  import itertools
  from typing import Optional, Type
  from google.protobuf import message
  from tensorflow.core.framework import graph_pb2
  from tensorflow.core.framework import node_def_pb2
  from tensorflow.python.framework import tensor_util
  from tensorflow.tools.proto_splitter import constants
  from tensorflow.tools.proto_splitter import split
  from tensorflow.tools.proto_splitter import util
label_desc: Use image node_id 1 to create a new RepeatedMessageSplitter object from inherited base classes: split with example: obj = RepeatedMessageSplitter(proto, repeated_field, message_splitters)