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","."]
docstr: Returns whether the registry supports this layer type.
  
  # TODO(pulkitb): Consider pushing this function up to the registry.
  
  Args:
    layer: The layer to check for support.
  
  Returns:
    True/False whether the layer type is supported.
docstr_tok: ["Returns","whether","the","registry","supports","this","layer","type",".","#","TODO","(","pulkitb",")",":","Consider","pushing","this","function","up","to","the","registry",".","Args",":","layer",":","The","layer","to","check","for","support",".","Returns",":","True\/False","whether","the","layer","type","is","supported","."]
code: def supports(self, layer):
      """Returns whether the registry supports this layer type.
  
      # TODO(pulkitb): Consider pushing this function up to the registry.
  
      Args:
        layer: The layer to check for support.
  
      Returns:
        True/False whether the layer type is supported.
  
      """
      if self._is_supported_layer(layer.__class__):
          return True
  
      if self._is_rnn_layer(layer):
          for rnn_cell in self._get_rnn_cells(layer):
              # All cells in the RNN layer should be supported.
              if not self._is_supported_layer(rnn_cell.__class__):
                  return False
          return True
  
      return 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 5 for calling the Default8BitQuantizeRegistry obj's underlying member method code with example usage: obj.supports(layer) and returns: False, True, True, False