class_docstr: Optimizer that implements the Layer-wise Adaptive Moments (LAMB).
  
  See paper [Large Batch Optimization for Deep Learning: Training BERT
  in 76 minutes](https://arxiv.org/abs/1904.00962).
class_docstr_tok: ["Optimizer","that","implements","the","Layer-wise","Adaptive","Moments","(","LAMB",")",".","See","paper","[","Large","Batch","Optimization","for","Deep","Learning",":","Training","BERT","in","76","minutes","]","(","https",":","\/\/arxiv.org\/abs\/1904.00962",")","."]
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, variable):
      """Whether to do layer-wise learning rate adaptation for
      `param_name`."""
      return not is_variable_matched_by_regexes(
          variable, self.exclude_from_layer_adaptation
      )
  
file_path: addons/tensorflow_addons/optimizers/lamb.py
imports: import warnings
  from typing import Optional, Union, Callable, List
  from typeguard import typechecked
  import tensorflow
  from tensorflow_addons.optimizers import KerasLegacyOptimizer
  from tensorflow_addons.utils.types import FloatTensorLike
  from tensorflow_addons.optimizers.utils import is_variable_matched_by_regexes
label_desc: Use image node_id 8 for calling the LAMB obj's underlying member method code with example usage: obj._do_layer_adaptation(variable) and returns: unknown