class_docstr: Optimizer that implements the LAMBOptimizer as tf.train.Optimizer.
docstr: Whether to do layer-wise learning rate adaptation for `param_name`.
docstr_tok: ["Whether","to","do","layer-wise","learning","rate","adaptation","for","`","param_name","`","."]
code: def _do_layer_adaptation(self, param_name):
      """Whether to do layer-wise learning rate adaptation for `param_name`."""
      if self.exclude_from_layer_adaptation:
          for r in self.exclude_from_layer_adaptation:
              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 re
  import tensorflow.compat.v1
  from tensorflow.python.eager import context
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import linalg_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import state_ops
  from tensorflow.python.training import optimizer
label_desc: Use image node_id 14 for calling the LAMBOptimizer obj's underlying member method code with example usage: obj._do_layer_adaptation(param_name) and returns: True, False