class_docstr: Tests HierarchicalRNNEncoder
      
docstr: Tests encoder_minor as a BidirectionalRNNEncoder
          
code: def test_encoder_minor_as_birnn(self):
      """Tests encoder_minor as a BidirectionalRNNEncoder"""
      hparams = {
          "encoder_minor_type": "BidirectionalRNNEncoder",
          "encoder_minor_hparams": {
              "rnn_cell_fw": {
                  "type": "LSTMCell",
                  "kwargs": {"num_units": 100},
              }
          },
          "encoder_major_hparams": {
              "rnn_cell": {
                  "type": "LSTMCell",
                  "kwargs": {"num_units": 200},
              }
          },
      }
      encoder = HierarchicalRNNEncoder(hparams=hparams)
  
      batch_size = 16
      max_major_time = 8
      max_minor_time = 6
      dim = 10
      inputs = tf.random_uniform(
          [batch_size, max_major_time, max_minor_time, dim],
          maxval=1,
          minval=-1,
          dtype=tf.float32,
      )
  
      outputs, _ = encoder(inputs)
      self.assertEqual(list(outputs.shape), [16, 8, 200])
  
file_path: texar/tests/modules/encoders/hierarchical_encoders_test.py
imports: import tensorflow
  from texar.tf.modules.encoders.hierarchical_encoders import HierarchicalRNNEncoder
label_desc: Use image node_id 5 for calling the HierarchicalRNNEncoderTest obj's underlying member method code with example usage: obj.test_encoder_minor_as_birnn() without return types