code: def is_adjoint_pair(x, y):
      """True iff x and y are adjoints of each other (by id, not entries)."""
      if (
          x is y
      ):  # Note that if x is y then all of their hints are the same!
          if (
              x.is_self_adjoint is False
          ):  # pylint:disable=g-bool-id-comparison
              return False
          if x.is_self_adjoint:
              return True
      # Use the fact that if x = LinearOperatorAdjoint(y), then x.H is y.
      return x.H is y or y.H is x
  
imports: import numpy
  from tensorflow_probability.python.internal.backend.numpy import dtype
  from tensorflow_probability.python.internal.backend.numpy import ops
  from tensorflow_probability.python.internal.backend.numpy import ops
  from tensorflow_probability.python.internal.backend.numpy import numpy_array
  from tensorflow_probability.python.internal.backend.numpy import debugging
  from tensorflow_probability.python.internal.backend.numpy import control_flow
  from tensorflow_probability.python.internal.backend.numpy import linalg_impl
  from tensorflow_probability.python.internal.backend.numpy import numpy_math
  from tensorflow_probability.python.internal.backend.numpy import ops
  from tensorflow_probability.python.internal.backend.numpy import nest
  import numpy
  from tensorflow_probability.python.internal.backend.numpy import linalg_impl
  from tensorflow_probability.python.internal.backend.numpy import ops
  from tensorflow_probability.python.internal.backend.numpy.gen import tensor_shape
  from tensorflow_probability.python.internal.backend.numpy import private
label_desc: Use image node_id 15 for calling a global function with example usage: is_adjoint_pair(x, y) and returns: unknown, False, True