code: def test_causal_conv1d(self):
      rng = dict(params=random.key(0))
      x = jnp.ones((1, 8, 4))
      conv_module = nn.Conv(
          features=4,
          kernel_size=(3,),
          padding="CAUSAL",
          kernel_init=initializers.ones,
          bias_init=initializers.ones,
      )
      y, _ = conv_module.init_with_output(rng, x)
      correct_ans = np.array(
          [
              [
                  [5.0, 5.0, 5.0, 5.0],
                  [9.0, 9.0, 9.0, 9.0],
                  [13.0, 13.0, 13.0, 13.0],
                  [13.0, 13.0, 13.0, 13.0],
                  [13.0, 13.0, 13.0, 13.0],
                  [13.0, 13.0, 13.0, 13.0],
                  [13.0, 13.0, 13.0, 13.0],
                  [13.0, 13.0, 13.0, 13.0],
              ]
          ]
      )
      np.testing.assert_allclose(y, correct_ans)
      np.testing.assert_array_equal(correct_ans.shape, y.shape)
  
imports: import functools
  import jax
  import jax.numpy
  import numpy
  from absl.testing import absltest, parameterized
  from jax import random
  from jax.nn import initializers
  from flax import linen
label_desc: Use image node_id 28 for calling the LinearTest obj's underlying member method code with example usage: obj.test_causal_conv1d() without return types