class_docstr: This class is an implementation of the original AEDA algorithm (2021) [1].
  
  [1] Karimi et al., 2021, November. AEDA: An Easier Data Augmentation Technique for Text Classification.
  In Findings of the Association for Computational Linguistics: EMNLP 2021 (pp. 2748-2754).
  https://aclanthology.org/2021.findings-emnlp.234.pdf
  
  Example usage: ::
      >>> from textaugment import AEDA
      >>> t = AEDA()
      >>> t.punct_insertion("John is going to town")
      ! John is going to town
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docstr: Validate input data
docstr_tok: ["Validate","input","data"]
code: def validate(**kwargs):
      """Validate input data"""
      if "sentence" in kwargs:
          if (
              not isinstance(kwargs["sentence"].strip(), str)
              or len(kwargs["sentence"].strip()) == 0
          ):
              raise TypeError("sentence must be a valid sentence")
  
imports: import random
label_desc: Use image node_id 1 for calling the AEDA obj's underlying member method code with example usage: obj.validate() without return types