class_docstr: QuantizeConfig for non recurrent Keras layers.
class_docstr_tok: ["QuantizeConfig","for","non","recurrent","Keras","layers","."]
code: def get_output_quantizers(self, layer):
      if self.quantize_output:
          return [self.activation_quantizer]
      return []
  
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 6 for calling the DefaultNBitQuantizeConfig obj's underlying member method code with example usage: obj.get_output_quantizers(layer) and returns: list, list