class_docstr: Checks if a particular subgraph matches a given pattern.
docstr: Returns whether an TF expression rooted at `op` matches `pattern`.
  
  If there is a match, adds to `self._match_result` the matching op and tensor
  with key `pattern`.
  
  Args:
    pattern: An `Pattern`.
    op: A `tf.Operation` to match against the pattern.
    tensor: the output `tf.Tensor` of `op` that is used by the matching op of
      `pattern`'s parent. Can be None if `pattern` is already the root of the
      pattern tree.
  
  Returns:
    True if an TF expression rooted at `op` matches `pattern`.
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code: def _match_pattern(self, pattern, op):
      """Returns whether an TF expression rooted at `op` matches `pattern`.
  
      If there is a match, adds to `self._match_result` the matching op and tensor
      with key `pattern`.
  
      Args:
        pattern: An `Pattern`.
        op: A `tf.Operation` to match against the pattern.
        tensor: the output `tf.Tensor` of `op` that is used by the matching op of
          `pattern`'s parent. Can be None if `pattern` is already the root of the
          pattern tree.
  
      Returns:
        True if an TF expression rooted at `op` matches `pattern`.
      """
      match_result = pattern.match(op)
      if match_result is None:
          return False
      self._match_result.merge_from(match_result)
      return True
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import abc
  import itertools
  from mmdnn.conversion.common.DataStructure.graph import Graph
label_desc: Use image node_id 2 for calling the GraphMatcher obj's underlying member method code with example usage: obj._match_pattern(pattern, op) and returns: True, False