class_docstr: PrunePreserveInfo.
class_docstr_tok: ["PrunePreserveInfo","."]
docstr: Initializes PrunePreserveInfo.
  
  Args:
    weight_attrs: list of sparsity preservable weight attributes of layer.
    quantize_config_attrs: list of quantization configuration class name.
docstr_tok: ["Initializes","PrunePreserveInfo",".","Args",":","weight_attrs",":","list","of","sparsity","preservable","weight","attributes","of","layer",".","quantize_config_attrs",":","list","of","quantization","configuration","class","name","."]
code: def __init__(self, weight_attrs, quantize_config_attrs):
      """Initializes PrunePreserveInfo.
  
      Args:
        weight_attrs: list of sparsity preservable weight attributes of layer.
        quantize_config_attrs: list of quantization configuration class name.
      """
      self.weight_attrs = weight_attrs
      self.quantize_config_attrs = quantize_config_attrs
  
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 1 to create a new _PrunePreserveInfo object from inherited base classes: object with example: obj = _PrunePreserveInfo(weight_attrs, quantize_config_attrs)