class_docstr: RNN + Attention
  Input Shape: [batch_size, steps, features]
  Output Shape: [batch_size, units]
class_docstr_tok: ["RNN","+","Attention","Input","Shape",":","[","batch_size",",","steps",",","features","]","Output","Shape",":","[","batch_size",",","units","]"]
code: def compute_output_shape(self, input_shape):
      return tf.TensorShape([input_shape[0], self.cell_dim * 2])
  
imports: from absl import logging
  import delta.compat
  import delta
  from delta.layers.base_layer import Layer
  from tensorflow_addons import seq2seq
label_desc: Use image node_id 3 for calling the RnnEncoder obj's underlying member method code with example usage: obj.compute_output_shape(input_shape) and returns: tf