code: def test_terraformer_predict_equals_eval(self):
      with fastmath.use_backend(fastmath.Backend.JAX):
          vocab_size = 16
          d_model = 8
          batch_size = 1
          length = 5
  
          model_fn = functools.partial(
              terraformer.ConfigurableTerraformer,
              vocab_size,
              d_model=d_model,
              d_ff=16,
              n_encoder_layers=1,
              n_decoder_layers=1,
              n_heads=2,
              ff_use_sru=(1, 8),  # ? is SRU working?
              dropout=0.0,
              max_len=(length + 7) * 2,
              pos_type=None,
              reversible_encoder=True,
              n_decoder_attention_layers=1,
              encoder_attention_type=tl.Attention,
              encoder_decoder_attention_type=tl.CausalAttention,
          )
  
          # Token id of 0 indicates padding; and predict mode doesn't support it.
          inp = np.random.randint(
              1, vocab_size, size=(batch_size, length)
          )
          inp[:, -2:] = 0
          out = np.zeros((batch_size, length), dtype=np.int32)
  
          test_utils.test_eval_equals_predict(
              (inp, out),
              model_fn,
              seq_axis=1,
              seq_tensor=-1,
              init_tokens=1,
          )
  
imports: import functools
  from absl.testing import absltest
  from absl.testing import parameterized
  import gin
  import numpy
  from trax import fastmath
  from trax import layers
  from trax import shapes
  from trax.layers import test_utils
  from trax.models.research import terraformer
label_desc: Use image node_id 6 for calling the TerraformerTest obj's underlying member method code with example usage: obj.test_terraformer_predict_equals_eval() without return types