class_docstr: Implements a check in truncated graphs.
  Raises `TruncationError` if the check is not True.
class_docstr_tok: ["Implements","a","check","in","truncated","graphs",".","Raises","`","TruncationError","`","if","the","check","is","not","True","."]
code: def __str__(self):
      return f"TruncationCheck{{{self.msg}}}"
  
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 2 for calling the TruncationCheck obj's underlying member method code with example usage: obj.__str__() and returns: str, self, str