code: def _check_clifford_op(op, use_decomposition=False):
      r"""Checks if an operator is Clifford or not.
  
      For a given unitary operator :math:`U` acting on :math:`N` qubits, this method checks that the
      transformation :math:`UPU^{\dagger}` maps the Pauli tensor products :math:`P = {I, X, Y, Z}^{\otimes N}`
      to Pauli tensor products using the decomposition of the matrix for :math:`U` in the Pauli basis.
  
      Args:
          op (~pennylane.operation.Operation): the operator that needs to be tested
          use_decomposition (bool): if ``True``, use operator's decomposition to compute the matrix, in case
              it doesn't define a ``compute_matrix`` method. Default is ``False``.
  
      Returns:
          Bool that represents whether the provided operator is Clifford or not.
      """
  
      # Check if matrix can be calculated for the operator
      if (not op.has_matrix and not use_decomposition) or (
          use_decomposition and not op.expand().wires
      ):
          return False
  
      # Compute the LCUs for the operator in Pauli basis
      pauli_terms = qml.pauli_decompose(
          qml.matrix(op), wire_order=op.wires, check_hermitian=False
      )
      pauli_terms_adj = qml.Hamiltonian(
          qml.math.conj(pauli_terms.coeffs), pauli_terms.ops
      )
  
      # Build Pauli tensor products P in the Hamiltonian form
      def pauli_group(x):
          return [
              qml.Identity(x),
              qml.PauliX(x),
              qml.PauliY(x),
              qml.PauliZ(x),
          ]
  
      # Build PauliSentence and Hamiltonians representations for set P
      pauli_sens = [
          qml.pauli.pauli_sentence(qml.prod(*pauli))
          for pauli in product(*(pauli_group(idx) for idx in op.wires))
      ]
      pauli_hams = (
          pauli_sen.hamiltonian(wire_order=op.wires)
          for pauli_sen in pauli_sens
      )
  
      # Perform U@P@U^\dagger and check if the result exists in set P
      for pauli_prod in product(
          [pauli_terms], pauli_hams, [pauli_terms_adj]
      ):
          # hopefully op_math.prod scales better than matrix multiplication, i.e., O((2^N)^3)
          upu = qml.pauli.pauli_sentence(qml.prod(*pauli_prod))
          upu.simplify()
          # Pauli sum always lie outside set P
          if len(upu) != 1:
              return False
  
      return True
  
file_path: pennylane/pennylane/transforms/decompositions/clifford_t_transform.py
imports: import math
  import warnings
  from itertools import product
  from typing import Sequence, Callable
  import pennylane
  from pennylane.queuing import QueuingManager
  from pennylane.transforms.core import transform
  from pennylane.tape import QuantumTape
  from pennylane.transforms.optimization import cancel_inverses, commute_controlled, merge_rotations, remove_barrier
  from pennylane.transforms.optimization.optimization_utils import find_next_gate, _fuse_global_phases
  from pennylane.ops.op_math.decompositions.solovay_kitaev import sk_decomposition
label_desc: Use image node_id 1 for calling a global function with example usage: _check_clifford_op(op, use_decomposition) and returns: True, False, list, False