class_docstr: Bidirectional RNN
  Input Shape: [batch_size, steps, features]
  Output Shape: [batch_size, units]
class_docstr_tok: ["Bidirectional","RNN","Input","Shape",":","[","batch_size",",","steps",",","features","]","Output","Shape",":","[","batch_size",",","units","]"]
code: def call(self, inputs, training=None, mask=None):
      out = self.bi_rnn(inputs)
      return out
  
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 5 for calling the BiRnn obj's underlying member method code with example usage: obj.call(inputs, training, mask) and returns: out