class_docstr:     The BLEU evaluation metric class.
  Parameters
  ----------
  n_grams: list[int]
      The BLEU's n_gram parameter. The results will be returned according             to the ``n_grams`` one-by-one.
  verbose: int, default = 0
      The log indicator. If set to 0, it will output no logs.
code: def __init__(self, n_grams, verbose=0):
      super(BLEU, self).__init__()
      max_gram = self._check_available(n_grams)
      self.scorer = Bleu(max_gram, verbose=verbose)
      self.metrics = n_grams
  
imports: from graph4nlp.pytorch.modules.evaluation.base import EvaluationMetricBase
  from graph4nlp.pytorch.modules.evaluation.bleu_tool.bleu import Bleu
label_desc: Use image node_id 1 to create a new BLEU object from inherited base classes: EvaluationMetricBase with example: obj = BLEU(n_grams, verbose)