class_docstr: QuantizeConfig for Conv2D/DepthwiseConv2D layers.
class_docstr_tok: ["QuantizeConfig","for","Conv2D\/DepthwiseConv2D","layers","."]
code: def __init__(self, weight_attrs, activation_attrs, quantize_output):
      super(Default8BitConvQuantizeConfig, self).__init__(
          weight_attrs, activation_attrs, quantize_output
      )
  
      self.weight_quantizer = (
          default_8bit_quantizers.Default8BitConvWeightsQuantizer()
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  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.default_8bit import default_8bit_quantize_configs
  from tensorflow_model_optimization.python.core.quantization.keras.default_8bit import default_8bit_quantizers
label_desc: Use image node_id 1 to create a new Default8BitConvQuantizeConfig object from inherited base classes: Default8BitQuantizeConfig with example: obj = Default8BitConvQuantizeConfig(weight_attrs, activation_attrs, quantize_output)