class_docstr: Exact Match Metric.
class_docstr_tok: ["Exact","Match","Metric","."]
docstr: Initializes exact match metric.
  
  Args:
    name: The name of the metric to use.
    convert_to: The conversion to perform before checking equality.
docstr_tok: ["Initializes","exact","match","metric",".","Args",":","name",":","The","name","of","the","metric","to","use",".","convert_to",":","The","conversion","to","perform","before","checking","equality","."]
code: def __init__(
      self,
      name: str = EXACT_MATCH_NAME,
      convert_to: Optional[str] = None,
  ):
      """Initializes exact match metric.
  
      Args:
        name: The name of the metric to use.
        convert_to: The conversion to perform before checking equality.
      """
  
      super().__init__(
          metric_util.merge_per_key_computations(_exact_match),
          name=name,
          convert_to=convert_to,
      )
      if convert_to and convert_to not in _CONVERT_TO_VALUES:
          raise ValueError(
              "convert_to can only be one of the following: %s"
              % str(convert_to)
          )
  
file_path: model-analysis/tensorflow_model_analysis/metrics/exact_match.py
imports: import json
  from typing import Dict, Iterable, Optional
  import apache_beam
  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 ExactMatch object from inherited base classes: metric_types with example: obj = ExactMatch(name, convert_to)