class_docstr: Class to store results from the matcher.
  
  This class is used to store the results from the matcher. It provides
  convenient methods to query the matching results.
docstr: Constructs a Match object.
  
  Args:
    match_results: Integer tensor of shape [N] with (1) match_results[i]>=0,
      meaning that column i is matched with row match_results[i].
      (2) match_results[i]=-1, meaning that column i is not matched.
      (3) match_results[i]=-2, meaning that column i is ignored.
  
  Raises:
    ValueError: if match_results does not have rank 1 or is not an
      integer int32 scalar tensor
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code: def __init__(self, match_results):
      """Constructs a Match object.
  
      Args:
        match_results: Integer tensor of shape [N] with (1) match_results[i]>=0,
          meaning that column i is matched with row match_results[i].
          (2) match_results[i]=-1, meaning that column i is not matched.
          (3) match_results[i]=-2, meaning that column i is ignored.
  
      Raises:
        ValueError: if match_results does not have rank 1 or is not an
          integer int32 scalar tensor
      """
      if match_results.shape.ndims != 1:
          raise ValueError("match_results should have rank 1")
      if match_results.dtype != tf.int32:
          raise ValueError(
              "match_results should be an int32 or int64 scalar "
              "tensor"
          )
      self._match_results = match_results
  
imports: import abc
  import tensorflow.compat.v1
label_desc: Use image node_id 1 to create a new Match object from inherited base classes: object with example: obj = Match(match_results)