docstr: Update the model parameters given the extracted statistics.
  
  This method uses calculated statistics from calls to the `summarize`
  method to update the distribution parameters. Hyperparameters for the
  update are passed in at initialization time.
  
  Note: Internally, a call to `fit` is just a successive call to the
  `summarize` method followed by the `from_summaries` method.
docstr_tok: ["Update","the","model","parameters","given","the","extracted","statistics",".","This","method","uses","calculated","statistics","from","calls","to","the","`","summarize","`","method","to","update","the","distribution","parameters",".","Hyperparameters","for","the","update","are","passed","in","at","initialization","time",".","Note",":","Internally",",","a","call","to","`","fit","`","is","just","a","successive","call","to","the","`","summarize","`","method","followed","by","the","`","from_summaries","`","method","."]
code: def from_summaries(self):
      """Update the model parameters given the extracted statistics.
  
      This method uses calculated statistics from calls to the `summarize`
      method to update the distribution parameters. Hyperparameters for the
      update are passed in at initialization time.
  
      Note: Internally, a call to `fit` is just a successive call to the
      `summarize` method followed by the `from_summaries` method.
      """
  
      for d in self.distributions:
          d.from_summaries()
  
      if self.frozen == True:
          return
  
      priors = self._w_sum / torch.sum(self._w_sum)
  
      _update_parameter(self.priors, priors, self.inertia)
      self._reset_cache()
  
file_path: pomegranate/pomegranate/_bayes.py
imports: import torch
  from ._utils import _cast_as_tensor
  from ._utils import _update_parameter
  from ._utils import _check_parameter
  from ._utils import _reshape_weights
  from .distributions._distribution import Distribution
label_desc: Use image node_id 8 for calling the BayesMixin obj's underlying member method code with example usage: obj.from_summaries() without return types