class_docstr: PrunePreserveWeightsQuantizer for default 8bit Conv2D/DepthwiseConv2D weights.
class_docstr_tok: ["PrunePreserveWeightsQuantizer","for","default","8bit","Conv2D\/DepthwiseConv2D","weights","."]
code: def build(self, tensor_shape, name, layer):
      result = (
          PrunePreserveDefaultWeightsQuantizer._build_sparsity_mask(
              self, name, layer
          )
      )
      result.update(
          default_8bit_quantizers.Default8BitConvWeightsQuantizer.build(
              self, tensor_shape, name, layer
          )
      )
      return result
  
imports: import tensorflow
  from tensorflow_model_optimization.python.core.quantization.keras import quant_ops
  from tensorflow_model_optimization.python.core.quantization.keras import quantizers
  from tensorflow_model_optimization.python.core.quantization.keras.default_8bit import default_8bit_quantize_registry
  from tensorflow_model_optimization.python.core.quantization.keras.default_8bit import default_8bit_quantizers
label_desc: Use image node_id 2 for calling the PrunePreserveDefault8BitConvWeightsQuantizer obj's underlying member method code with example usage: obj.build(tensor_shape, name, layer) and returns: result