code: def _square_hamiltonian_terms(
      coeffs: Iterable[float], ops: Iterable[qml.operation.Observable]
  ) -> Tuple[List[float], List[qml.operation.Observable]]:
      """Calculates the coefficients and observables that compose the squared Hamiltonian.
  
      Args:
          coeffs (Iterable[float]): coeffients of the input Hamiltonian
          ops (Iterable[qml.operation.Observable]): observables of the input Hamiltonian
  
      Returns:
          Tuple[List[float], List[qml.operation.Observable]]: The list of coefficients and list of observables
          of the squared Hamiltonian.
      """
      squared_coeffs, squared_ops = [], []
      pairs = [(coeff, op) for coeff, op in zip(coeffs, ops)]
      products = itertools.product(pairs, repeat=2)
  
      for (coeff1, op1), (coeff2, op2) in products:
          squared_coeffs.append(coeff1 * coeff2)
  
          if isinstance(op1, qml.Identity):
              squared_ops.append(op2)
          elif isinstance(op2, qml.Identity):
              squared_ops.append(op1)
          # pylint: disable=unidiomatic-typecheck
          elif op1.wires == op2.wires and isinstance(op1, type(op2)):
              squared_ops.append(qml.Identity(0))
          elif op2.wires[0] < op1.wires[0]:
              squared_ops.append(op2 @ op1)
          else:
              squared_ops.append(op1 @ op2)
  
      return squared_coeffs, squared_ops
  
file_path: pennylane/pennylane/qaoa/cycle.py
imports: import itertools
  from typing import Dict, Tuple, Iterable, List, Union
  import networkx
  import rustworkx
  import numpy
  import pennylane
  from pennylane.ops import Hamiltonian
label_desc: Use image node_id 6 for calling a global function with example usage: _square_hamiltonian_terms(coeffs, ops) and returns: squared_coeffs,  squared_ops