code: def score(self, originals, generateds, **kwargs):
      with torch.no_grad():
          logits, histograms, images = self.forward(
              originals, generateds
          )
          probs = torch.nn.functional.softmax(logits, dim=-1)
          batch_scores = probs[:, 1].tolist()
      return {"scores": batch_scores}
  
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 6 for calling the SummaCConv obj's underlying member method code with example usage: obj.score(originals, generateds) and returns: dict