class_docstr: Stores hyperparameters for initialization, batch norm and training.
class_docstr_tok: ["Stores","hyperparameters","for","initialization",",","batch","norm","and","training","."]
code: def update(self, dikt, **kwargs):
      all_dikt = dict(
          it.chain(six.iteritems(dikt), six.iteritems(kwargs))
      )
      self._filter_and_check_legacy_hparams(all_dikt)
      for key, value in six.iteritems(all_dikt):
          setattr(self, key, value)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import itertools
  import os
  from magenta.models.coconet import lib_util
  import numpy
  import six
  import tensorflow.compat.v1
  import yaml
label_desc: Use image node_id 2 for calling the Hyperparameters obj's underlying member method code with example usage: obj.update(dikt) without return types