class_docstr: Class to apply pattern matching in the forward direction.
class_docstr_tok: ["Class","to","apply","pattern","matching","in","the","forward","direction","."]
docstr: Initialize the list of corresponding matches in the circuit for the pattern.
code: def _init_matched_with_pattern(self):
      """
      Initialize the list of corresponding matches in the circuit for the pattern.
      """
      for i in range(0, self.pattern_dag.size):
          if i == self.node_id_p:
              self.pattern_matched_with[i] = [self.node_id_c]
          else:
              self.pattern_matched_with[i] = []
  
imports: import copy
  import itertools
  from collections import OrderedDict
  from typing import Sequence, Callable
  import numpy
  import pennylane
  from pennylane.transforms import transform
  from pennylane import adjoint
  from pennylane.ops.qubit.attributes import symmetric_over_all_wires
  from pennylane.tape import QuantumTape, QuantumScript
  from pennylane.transforms.commutation_dag import commutation_dag
  from pennylane.wires import Wires
label_desc: Use image node_id 4 for calling the ForwardMatch obj's underlying member method code with example usage: obj._init_matched_with_pattern() without return types