class_docstr: QuantizationRegistry for built-in Keras classes for default 8-bit scheme.
class_docstr_tok: ["QuantizationRegistry","for","built-in","Keras","classes","for","default","8-bit","scheme","."]
code: def __init__(self, disable_per_axis=False):
      self._layer_quantize_map = {}
      for quantize_info in self._LAYER_QUANTIZE_INFO:
          self._layer_quantize_map[
              quantize_info.layer_type
          ] = quantize_info
  
      # Hack for `Activation` layer. That is the only layer with a separate
      # QuantizeConfig.
      self._layer_quantize_map[
          layers.Activation
      ] = Default8BitActivationQuantizeConfig()
  
      self._layer_quantize_map[
          layers.Conv2DTranspose
      ] = Default8BitConvTransposeQuantizeConfig(
          ["kernel"], ["activation"], False
      )
  
      self._disable_per_axis = disable_per_axis
      if not self._disable_per_axis:
          self._layer_quantize_map[
              layers.Conv2D
          ] = Default8BitConvQuantizeConfig(
              ["kernel"], ["activation"], False
          )
          self._layer_quantize_map[
              layers.DepthwiseConv2D
          ] = Default8BitConvQuantizeConfig(
              ["depthwise_kernel"], ["activation"], False
          )
      else:
          self._layer_quantize_map[
              layers.Conv2D
          ] = Default8BitQuantizeConfig(
              ["kernel"], ["activation"], False
          )
          self._layer_quantize_map[
              layers.DepthwiseConv2D
          ] = Default8BitQuantizeConfig(
              ["depthwise_kernel"], ["activation"], False
          )
  
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 Default8BitQuantizeRegistry object from inherited base classes: quantize_registry, _RNNHelper with example: obj = Default8BitQuantizeRegistry(disable_per_axis)