class_docstr: A basic Adam optimizer that includes "correct" L2 weight decay.
docstr: Whether to use L2 weight decay for `param_name`.
docstr_tok: ["Whether","to","use","L2","weight","decay","for","`","param_name","`","."]
code: def _do_use_weight_decay(self, param_name):
      """Whether to use L2 weight decay for `param_name`."""
      if not self.weight_decay_rate:
          return False
      if self.exclude_from_weight_decay:
          for r in self.exclude_from_weight_decay:
              if re.search(r, param_name) is not None:
                  return False
      return True
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import functools
  import re
  import gin
  from mesh_tensorflow import layers
  from mesh_tensorflow import ops_with_redefined_builtins
  import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling the AdamWeightDecayOptimizer obj's underlying member method code with example usage: obj._do_use_weight_decay(param_name) and returns: True, False, False