code: def test_conv1d_call_same_input_output_dims(self):
      batch = 2
      d_model = 6
      length = 3
      inputs = np.random.randint(0, 10, size=[batch, length])
      inputs_mtf = self.converter.convert_np_array_to_mtf_tensor(
          inputs, dim_names=["batch", "length"]
      )
      # Dummy context with necessary information for Conv1DLayer.call
      Context = collections.namedtuple(
          "Context", ["inputs", "activation_dtype", "mode"]
      )
      context = Context(
          inputs=inputs_mtf, activation_dtype=tf.float32, mode="train"
      )
      x = np.random.randn(batch, length, d_model)
      x_mtf = self.converter.convert_np_array_to_mtf_tensor(
          x, dtype=tf.float32, dim_names=["batch", "length", "d_model"]
      )
      conv_layer = transformer_layers.Conv1DLayer(
          filter_size=3, output_size=d_model
      )
      output_mtf = conv_layer.call(context, x_mtf)
      self.assertAllEqual(
          [batch, length, d_model], output_mtf.shape.to_integer_list
      )
  
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 2 for calling the TransformerLayersTest obj's underlying member method code with example usage: obj.test_conv1d_call_same_input_output_dims() without return types