code: def __init__(
      self,
      model_name="mnli",
      granularity="paragraph",
      op1="max",
      op2="mean",
      use_ent=True,
      use_con=True,
      imager_load_cache=True,
      device="cuda",
      **kwargs,
  ):
      assert op2 in ["min", "mean", "max"], "Unrecognized `op2`"
      assert op1 in ["max", "mean", "min"], "Unrecognized `op1`"
  
      self.imager = SummaCImager(
          model_name=model_name,
          granularity=granularity,
          device=device,
          **kwargs,
      )
      if imager_load_cache:
          self.imager.load_cache()
      self.op2 = op2
      self.op1 = op1
      self.use_ent = use_ent
      self.use_con = use_con
  
imports: from transformers import AutoTokenizer, AutoModelForSequenceClassification
  import nltk
  import numpy
  import torch
  import os
  import json
  from .None import utils_misc
label_desc: Use image node_id 1 to create a new SummaCZS object  with example: obj = SummaCZS(model_name, granularity, op1, op2, use_ent, use_con, imager_load_cache, device)