code: def __init__(
      self,
      table_model_config: t.Dict[str, t.Any] = None,
      text_model_config: t.Dict[str, t.Any] = None,
      drop_table_from_text_labels: bool = False,
      drop_table_from_text_preds: bool = True,
      split_preds_to_cells: bool = True,
      chunk_tables: bool = True,
  ):
      self.etl = TableETL(
          drop_table_from_text_labels=drop_table_from_text_labels,
          drop_table_from_text_preds=drop_table_from_text_preds,
          split_preds_to_cells=split_preds_to_cells,
          chunk_tables=chunk_tables,
      )
      self.table_model = SequenceLabeler(
          base_model=TableRoBERTa, **(table_model_config or {})
      )
      self.text_model = SequenceLabeler(**(text_model_config or {}))
      self.table_chunker = TableChunker.from_table_model(
          self.table_model
      )
  
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 1 to create a new TableLabeler object  with example: obj = TableLabeler(table_model_config, text_model_config, drop_table_from_text_labels, drop_table_from_text_preds, split_preds_to_cells, chunk_tables)