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.
docstr: Update the arguments of the prior with additional arguments.
  
  Parameters
  ----------
  kwargs : dict
      Optional keyword arguments to add to prior args.
docstr_tok: ["Update","the","arguments","of","the","prior","with","additional","arguments",".","Parameters","--","--","--","--","--","kwargs",":","dict","Optional","keyword","arguments","to","add","to","prior","args","."]
code: def update(self, **kwargs):
      """Update the arguments of the prior with additional arguments.
  
      Parameters
      ----------
      kwargs : dict
          Optional keyword arguments to add to prior args.
      """
      # The backend expect numpy arrays, so make sure all numeric values are represented as such.
      kwargs_ = {}
      for key, val in kwargs.items():
          if isinstance(val, (int, float)):
              val = np.array(
                  val, dtype=pytensor.config.floatX
              )  # pylint: disable = no-member
          elif isinstance(val, np.ndarray):
              val = val.squeeze().astype(
                  pytensor.config.floatX
              )  # pylint: disable = no-member
          kwargs_[key] = val
      self.args.update(kwargs_)
  
file_path: bambi/bambi/priors/prior.py
imports: import numpy
  import pytensor
label_desc: Use image node_id 2 for calling the Prior obj's underlying member method code with example usage: obj.update() without return types