code: def _truncated_normal(
      op, lower, upper, size, rng, old_size, dtype, mu, sigma
  ):
      return TruncatedNormal.dist(
          mu=mu,
          sigma=sigma,
          lower=lower,
          upper=upper,
          rng=None,  # Do not reuse rng to avoid weird dependencies
          size=size,
          dtype=dtype,
      )
  
imports: from functools import singledispatch
  import numpy
  import pytensor
  import pytensor.tensor
  from pytensor import scan
  from pytensor.graph import Op
  from pytensor.graph.basic import Node
  from pytensor.raise_op import CheckAndRaise
  from pytensor.scan import until
  from pytensor.tensor import TensorConstant, TensorVariable
  from pytensor.tensor.random.basic import NormalRV
  from pytensor.tensor.random.op import RandomVariable
  from pymc.distributions.continuous import TruncatedNormal, bounded_cont_transform
  from pymc.distributions.dist_math import check_parameters
  from pymc.distributions.distribution import Distribution, SymbolicRandomVariable, _moment, moment
  from pymc.distributions.shape_utils import _change_dist_size, change_dist_size, to_tuple
  from pymc.distributions.transforms import _default_transform
  from pymc.exceptions import TruncationError
  from pymc.logprob.abstract import _logcdf, _logprob
  from pymc.logprob.basic import icdf, logcdf
  from pymc.math import logdiffexp
  from pymc.util import check_dist_not_registered
label_desc: Use image node_id 7 for calling a global function with example usage: _truncated_normal(op, lower, upper, size, rng, old_size, dtype, mu, sigma) and returns: TruncatedNormal