code: def __init__(self, config, multi_label):
      super(SequencePipeline, self).__init__(config)
      self.multi_label = multi_label
      self.empty_counts = {"empty": 0, "labeled": 0}
  
imports: import copy
  import os
  from collections import Counter, defaultdict
  import math
  from typing import Dict, List, Tuple, Union
  import tensorflow
  import numpy
  from finetune.base import BaseModel
  from finetune.encoding.target_encoders import SequenceLabelingEncoder, SequenceMultiLabelingEncoder
  from finetune.nn.target_blocks import sequence_labeler
  from finetune.nn.crf import sequence_decode
  from finetune.encoding.sequence_encoder import finetune_to_indico_sequence
  from finetune.encoding.input_encoder import get_spacy
  from finetune.input_pipeline import BasePipeline
  from finetune.util.metrics import sequences_overlap
  from finetune.encoding.input_encoder import tokenize_context
label_desc: Use image node_id 1 to create a new SequencePipeline object from inherited base classes: BasePipeline with example: obj = SequencePipeline(config, multi_label)