class_docstr: QuantizeConfig for non recurrent Keras layers.
class_docstr_tok: ["QuantizeConfig","for","non","recurrent","Keras","layers","."]
docstr: Instantiates a `DefaultNBitQuantizeConfig` from its config.
  
  Args:
      config: Output of `get_config()`.
  
  Returns:
      A `DefaultNBitQuantizeConfig` instance.
docstr_tok: ["Instantiates","a","`","DefaultNBitQuantizeConfig","`","from","its","config",".","Args",":","config",":","Output","of","`","get_config","(",")","`",".","Returns",":","A","`","DefaultNBitQuantizeConfig","`","instance","."]
code: def from_config(cls, config):
      """Instantiates a `DefaultNBitQuantizeConfig` from its config.
  
      Args:
          config: Output of `get_config()`.
  
      Returns:
          A `DefaultNBitQuantizeConfig` instance.
      """
      return cls(**config)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import Any, Dict
  import tensorflow
  from tensorflow_model_optimization.python.core.quantization.keras import quantize_config
  from tensorflow_model_optimization.python.core.quantization.keras import quantize_registry
  from tensorflow_model_optimization.python.core.quantization.keras import quantizers
  from tensorflow_model_optimization.python.core.quantization.keras.experimental.default_n_bit import default_n_bit_quantize_configs
  from tensorflow_model_optimization.python.core.quantization.keras.experimental.default_n_bit import default_n_bit_quantizers
label_desc: Use image node_id 7 for calling the DefaultNBitQuantizeConfig obj's underlying member method code with example usage: obj.from_config(cls, config) and returns: cls