class_docstr: QuantizeConfig which only quantizes the output from a layer.
class_docstr_tok: ["QuantizeConfig","which","only","quantizes","the","output","from","a","layer","."]
code: def __init__(
      self, num_bits_weight: int = 8, num_bits_activation: int = 8
  ):
      self._num_bits_weight = num_bits_weight
      self._num_bits_activation = num_bits_activation
  
file_path: model-optimization/tensorflow_model_optimization/python/core/quantization/keras/experimental/default_n_bit/default_n_bit_quantize_configs.py
imports: from typing import Any, Dict
  from tensorflow_model_optimization.python.core.quantization.keras import quantize_config
  from tensorflow_model_optimization.python.core.quantization.keras import quantizers
label_desc: Use image node_id 1 to create a new DefaultNBitOutputQuantizeConfig object from inherited base classes: quantize_config with example: obj = DefaultNBitOutputQuantizeConfig(num_bits_weight, num_bits_activation)