class_docstr: Tests xlnet model utils.
      
code: def test_PositionWiseFF(self):
      # Case 1
      model = PositionWiseFF()
      inputs = tf.random_uniform(shape=(32, model.hparams.hidden_dim))
      outputs = model(inputs)
      self.assertEqual(outputs.shape, [32, model._hparams.hidden_dim])
  
      # Case 2
      hparams = {
          "hidden_dim": 16,
          "ffn_inner_dim": 32,
          "dropout": 0.1,
          "activation": "relu",
      }
      model = PositionWiseFF(hparams=hparams)
      inputs = tf.random_uniform(shape=(32, 16))
      outputs = model(inputs)
      self.assertEqual(outputs.shape, [32, 16])
  
      # Case 3
      hparams = {
          "hidden_dim": 16,
          "ffn_inner_dim": 32,
          "dropout": 0.1,
          "activation": "gelu",
      }
      model = PositionWiseFF(hparams=hparams)
      inputs = tf.random_uniform(shape=(32, 16))
      outputs = model(inputs)
      self.assertEqual(outputs.shape, [32, 16])
  
imports: import tensorflow
  from texar.tf.modules.pretrained.xlnet_utils import PositionWiseFF, RelativePositionalEncoding, RelativeMutiheadAttention
label_desc: Use image node_id 1 for calling the XLNetModelUtilsTest obj's underlying member method code with example usage: obj.test_PositionWiseFF() without return types