docstr: Converts the offet list from the table into a Chunk object.
  Storing the mapping from original document to the table-text
  as output by get_table_text.
docstr_tok: ["Converts","the","offet","list","from","the","table","into","a","Chunk","object",".","Storing","the","mapping","from","original","document","to","the","table-text","as","output","by","get_table_text","."]
code: def create_chunks_from_doc_offset(
      self, doc_offsets: t.List[t.Dict[str, int]]
  ) -> TableChunks:
      """
      Converts the offet list from the table into a Chunk object.
      Storing the mapping from original document to the table-text
      as output by get_table_text.
      """
      output = []
      for offset in doc_offsets:
          c_start = (
              0 if not output else output[-1]["table"]["end"] + 1
          )  # +1 to account for us joining on newlines.
          output.append(
              {
                  "document": {
                      "start": offset["start"],
                      "end": offset["end"],
                  },
                  "table": {
                      "start": c_start,
                      "end": c_start + offset["end"] - offset["start"],
                  },
              }
          )
      return output
  
imports: import copy
  import functools
  import os
  import tempfile
  import typing
  import sys
  from finetune.base_models import TableRoBERTa
  from finetune.util.metrics import sequences_overlap
  from finetune.scheduler import Scheduler
  from finetune.encoding.input_encoder import BaseEncoder
  from finetune import SequenceLabeler
label_desc: Use image node_id 5 for calling the TableETL obj's underlying member method code with example usage: obj.create_chunks_from_doc_offset(doc_offsets) and returns: output