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 _is_rnn_layer(self, layer):
      return layer.__class__ in {
          layers.GRU,
          layers.LSTM,
          layers.RNN,
          layers.SimpleRNN,
      }
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import Any, Dict
  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.experimental.default_n_bit import default_n_bit_quantize_configs
  from tensorflow_model_optimization.python.core.quantization.keras.experimental.default_n_bit import default_n_bit_quantizers
label_desc: Use image node_id 3 for calling the DefaultNBitQuantizeRegistry obj's underlying member method code with example usage: obj._is_rnn_layer(layer) and returns: unknown