code: def can_transpose_pass(self):
      const_input = None
      if (
          self.op.inputs["x"].op
          and self.op.inputs["x"].op.op_type == "const"
      ):
          const_input = self.op.inputs["x"]
          other_input = self.op.inputs["y"]
      if (
          self.op.inputs["y"].op
          and self.op.inputs["y"].op.op_type == "const"
      ):
          if const_input is not None:
              return False  # both inputs are constant
          const_input = self.op.inputs["y"]
          other_input = self.op.inputs["x"]
      if const_input is None:
          return True
      if not isinstance(const_input.val, (np.ndarray, np.generic)):
          return False
      rank_const_input = len(const_input.val.shape)
      rank_other_input = (
          len(other_input.shape) if other_input.shape else 0
      )
      if rank_const_input <= 1 and rank_other_input > 0:
          return True
      return False
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  from coremltools.converters.mil.mil.passes.pass_registry import register_pass
  from coremltools.converters.mil.mil import Builder
  from coremltools.converters.mil.mil.var import Var
  import logging
  import numpy
  import copy
  from collections import defaultdict
label_desc: Use image node_id 2 for calling the transform_add obj's underlying member method code with example usage: obj.can_transpose_pass() and returns: False, True, False, True, False