class_docstr: Abstract specification of a term prior.
  
  Parameters
  ----------
  name : str
      Name of prior distribution. Must be the name of a PyMC distribution
      (e.g., ``"Normal"``, ``"Bernoulli"``, etc.)
  auto_scale: bool
      Whether to adjust the parameters of the prior or use them as passed. Default to ``True``.
  kwargs : dict
      Optional keywords specifying the parameters of the named distribution.
  dist : pymc.distributions.distribution.DistributionMeta or callable
      A callable that returns a valid PyMC distribution. The signature must contain ``name``,
      ``dims``, and ``shape``, as well as its own keyworded arguments.
code: def __eq__(self, other):
      if not isinstance(other, type(self)):
          return False
      else:
          return self.__dict__ == other.__dict__
  
file_path: bambi/bambi/priors/prior.py
imports: import numpy
  import pytensor
label_desc: Use image node_id 3 for calling the Prior obj's underlying member method code with example usage: obj.__eq__(other) and returns: False, unknown