code: def _equal_parametrized_evolution(
      op1: ParametrizedEvolution, op2: ParametrizedEvolution, **kwargs
  ):
      # check times match
      if op1.t is None or op2.t is None:
          if not (op1.t is None and op2.t is None):
              return False
      elif not qml.math.allclose(op1.t, op2.t):
          return False
  
      # check parameters passed to operator match
      if not _equal_operators(op1, op2, **kwargs):
          return False
  
      # check H.coeffs match
      if not all(
          c1 == c2 for c1, c2 in zip(op1.H.coeffs, op2.H.coeffs)
      ):
          return False
  
      # check that all the base operators on op1.H and op2.H match
      return all(
          equal(o1, o2, **kwargs)
          for o1, o2 in zip(op1.H.ops, op2.H.ops)
      )
  
imports: from collections.abc import Iterable
  from functools import singledispatch
  from typing import Union
  import pennylane
  from pennylane.measurements import MeasurementProcess
  from pennylane.measurements.classical_shadow import ShadowExpvalMP
  from pennylane.measurements.mid_measure import MidMeasureMP, MeasurementValue
  from pennylane.measurements.mutual_info import MutualInfoMP
  from pennylane.measurements.vn_entropy import VnEntropyMP
  from pennylane.measurements.counts import CountsMP
  from pennylane.pulse.parametrized_evolution import ParametrizedEvolution
  from pennylane.operation import Observable, Operator, Tensor
  from pennylane.ops import Hamiltonian, Controlled, Pow, Adjoint, Exp, SProd, CompositeOp
  from pennylane.templates.subroutines import ControlledSequence
  from pennylane.tape import QuantumTape
label_desc: Use image node_id 14 for calling a global function with example usage: _equal_parametrized_evolution(op1, op2) and returns: all, False, False, False, False