class_docstr: Wrapper that always initializes weights from a pre-trained checkpoint.
class_docstr_tok: ["Wrapper","that","always","initializes","weights","from","a","pre-trained","checkpoint","."]
docstr: We allow to set attributes required for loading the model from its checkpoints.
docstr_tok: ["We","allow","to","set","attributes","required","for","loading","the","model","from","its","checkpoints","."]
code: def _settable_attrs(self):
      """We allow to set attributes required for loading the model from its checkpoints."""
      return (*super()._settable_attrs(), "init_checkpoint")
  
imports: import os
  import pathlib
  import urllib
  import zipfile
  import gin
  import jax
  import tensorflow
  from trax import fastmath
  from trax import layers
  from trax.fastmath import numpy
label_desc: Use image node_id 4 for calling the PretrainedBERT obj's underlying member method code with example usage: obj._settable_attrs() and returns: unknown,  str