code: def test_conv1d_call_incremental_mode(self):
      batch = 2
      d_model = 6
      length = 4
      filter_size = 3
      output_size = 2
  
      state = np.random.randn(batch, filter_size, d_model)
      context = get_dummy_decoder_context(
          self.converter,
          batch=batch,
          d_model=d_model,
          length=length,
          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_filter = np.random.randn(
          1, filter_size, d_model, output_size
      )
  
      def mock_initializer():
          # pylint: disable=unused-argument
          def conv_init(shape, dtype, **unused_kwargs):
              return conv_filter
  
          return conv_init
  
      with mock.patch.object(
          tf, "glorot_uniform_initializer", mock_initializer
      ):
          conv_layer = transformer_layers.Conv1DLayer(
              filter_size=filter_size, output_size=output_size
          )
          output_mtf = conv_layer.call(context, x_mtf)
      actual = self.converter.convert_mtf_tensor_to_np_array(output_mtf)
  
      # [batch, 2, d_model], [batch, 1, d_model] -> [batch, 3, d_model]
      padded_x = np.concatenate(
          [state[:, 1:, :], x[:, np.newaxis, :]], axis=1
      )
      # b: batch h: fake height, l: length (or filter), d: d_model, o: output_size
      expected = np.einsum("bld,hldo->bo", padded_x, conv_filter)
      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 8 for calling the TransformerLayersTest obj's underlying member method code with example usage: obj.test_conv1d_call_incremental_mode() and returns: conv_init, conv_filter