class_docstr: Generic processors for the sequence samples.
class_docstr_tok: ["Generic","processors","for","the","sequence","samples","."]
code: def to_dict(self) -> Dict[str, Any]:
      data = super(SequenceProcessor, self).to_dict()
      data["config"].update(
          {
              "build_in_vocab": self.build_in_vocab,
              "min_count": self.min_count,
          }
      )
      return data
  
file_path: Kashgari/kashgari/processors/sequence_processor.py
imports: import collections
  import operator
  from typing import Dict, List, Any, Optional, Union
  import numpy
  import tqdm
  from tensorflow.keras.preprocessing.sequence import pad_sequences
  from kashgari.generators import CorpusGenerator
  from kashgari.logger import logger
  from kashgari.processors.abc_processor import ABCProcessor
  from kashgari.types import TextSamplesVar
label_desc: Use image node_id 1 for calling the SequenceProcessor obj's underlying member method code with example usage: obj.to_dict() and returns: data