code: def __new__(cls, *args, **kwargs):
      kwargs.setdefault("transform", None)
      if kwargs.get("transform") is not None:
          raise ValueError("Cannot transform discrete variable.")
      return super().__new__(cls, *args, **kwargs)
  
imports: import warnings
  import numpy
  import pytensor.tensor
  from pytensor.tensor import as_tensor_variable
  from pytensor.tensor.random.op import RandomVariable
  from pytensor.tensor.variable import TensorVariable
  from pymc.distributions.continuous import BoundedContinuous, bounded_cont_transform
  from pymc.distributions.dist_math import check_parameters
  from pymc.distributions.distribution import Continuous, Discrete
  from pymc.distributions.shape_utils import to_tuple
  from pymc.distributions.transforms import _default_transform
  from pymc.logprob.basic import logp
  from pymc.model import modelcontext
  from pymc.pytensorf import floatX, intX
  from pymc.util import check_dist_not_registered
label_desc: Use image node_id 1 for calling the _DiscreteBounded obj's underlying member method code with example usage: obj.__new__(cls) and returns: super