class_docstr: Helper functions for working with RNNs.
class_docstr_tok: ["Helper","functions","for","working","with","RNNs","."]
docstr: Returns the list of cells in an RNN layer.
docstr_tok: ["Returns","the","list","of","cells","in","an","RNN","layer","."]
code: def _get_rnn_cells(self, rnn_layer):
      """Returns the list of cells in an RNN layer."""
      if isinstance(rnn_layer.cell, layers.StackedRNNCells):
          return rnn_layer.cell.cells
      else:
          return [rnn_layer.cell]
  
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 1 for calling the _RNNHelper obj's underlying member method code with example usage: obj._get_rnn_cells(rnn_layer) and returns: rnn_layer, list