class_docstr: Provides BLEU score for a model prediction.
code: def __call__(
      self, prediction: [Dict[str, Union[str, np.array]]]
  ) -> float:
      tokens_predicted = prediction["predicted_text"].split()
      tokens_output = prediction["preprocessed_text"][1].split()
      tokens_predicted_filtered = [
          t for t in tokens_predicted if t not in self.tokens_to_exclude
      ]
      tokens_output_filtered = [
          t for t in tokens_output if t not in self.tokens_to_exclude
      ]
      return sentence_bleu(
          [tokens_output_filtered],
          tokens_predicted_filtered,
          weights=self.weights,
      )
  
imports: from typing import Dict, Union
  import numpy
  from nltk.translate.bleu_score import sentence_bleu
  from headliner.evaluation.scorer import Scorer
label_desc: Use image node_id 2 for calling the BleuScorer obj's underlying member method code with example usage: obj.__call__(prediction) and returns: sentence_bleu