class_docstr: BLEU Metric.
class_docstr_tok: ["BLEU","Metric","."]
docstr: Initializes BLEU Metric.
docstr_tok: ["Initializes","BLEU","Metric","."]
code: def __init__(
      self,
      name: Optional[str] = _BLEU_NAME_DEFAULT,
      lowercase: Optional[bool] = False,
      force: Optional[bool] = False,
      tokenize: Optional[str] = "13a",
      smooth_method: Optional[str] = "exp",
      smooth_value: Optional[float] = None,
      use_effective_order: Optional[bool] = False,
  ):
      """Initializes BLEU Metric."""
  
      # This is 'use_effective_order' and not 'effective_order' for backward
      # compatibility for old style BLEU API access (< 1.4.11)
      super().__init__(
          metric_util.merge_per_key_computations(_bleu),
          name=name,
          lowercase=lowercase,
          force=force,
          tokenize=tokenize,
          smooth_method=smooth_method,
          smooth_value=smooth_value,
          effective_order=use_effective_order,
      )
  
file_path: model-analysis/tensorflow_model_analysis/metrics/bleu.py
imports: from typing import Dict, Iterable, Optional
  import apache_beam
  import numpy
  import sacrebleu
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.metrics import metric_util
  from tensorflow_model_analysis.proto import config_pb2
label_desc: Use image node_id 1 to create a new Bleu object from inherited base classes: metric_types with example: obj = Bleu(name, lowercase, force, tokenize, smooth_method, smooth_value, use_effective_order)