code: def test_conv1d_record_states_incremental_mode(self):
      batch = 2
      d_model = 6
      filter_size = 3
  
      state = np.random.randn(batch, filter_size, d_model)
      context = get_dummy_decoder_context(
          self.converter, batch=batch, d_model=d_model, state=state
      )
  
      x = np.random.randn(batch, d_model)
      x_mtf = self.converter.convert_np_array_to_mtf_tensor(
          x, dtype=tf.float32, dim_names=["batch", "d_model"]
      )
      conv_layer = transformer_layers.Conv1D()
      _ = conv_layer.record_states_incremental_mode(
          context, x_mtf, filter_size
      )
      actual = self.converter.convert_mtf_tensor_to_np_array(
          context.new_states[0]
      )
  
      # [batch, 2, d_model], [batch, 1, d_model] -> [batch, 3, d_model]
      expected = np.concatenate(
          [state[:, 1:, :], x[:, np.newaxis, :]], axis=1
      )
      self.assertAllClose(actual, expected)
  
imports: import collections
  import mesh_tensorflow
  from mesh_tensorflow import test_utils
  from mesh_tensorflow.transformer import transformer
  from mesh_tensorflow.transformer import transformer_layers
  import mock
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 5 for calling the TransformerLayersTest obj's underlying member method code with example usage: obj.test_conv1d_record_states_incremental_mode() without return types