class_docstr: This class implements the mixup algorithm [1] for natural language processing.
  
  [1] Zhang, Hongyi, Moustapha Cisse, Yann N. Dauphin, and David Lopez-Paz. "mixup: Beyond empirical risk
  minimization." in International Conference on Learning Representations (2018).
  https://openreview.net/forum?id=r1Ddp1-Rb
code: def __init__(self, random_state=1, runs=1):
      self.random_state = random_state
      self.runs = runs
      if isinstance(self.random_state, int):
          random.seed(self.random_state)
          np.random.seed(self.random_state)
      else:
          raise TypeError("random_state must have type int")
  
imports: import numpy
  import random
label_desc: Use image node_id 2 to create a new MIXUP object  with example: obj = MIXUP(random_state, runs)