code: def test_channel_multiplier(self, with_bias):
      def f():
          data = np.ones([1, 10, 10, 3])
          data[0, :, :, 1] += 1
          data[0, :, :, 2] += 2
          data = jnp.array(data)
          net = depthwise_conv.DepthwiseConv2D(
              channel_multiplier=3,
              kernel_shape=3,
              stride=1,
              padding="VALID",
              with_bias=with_bias,
              data_format="channels_last",
              **create_constant_initializers(1.0, 0.0, with_bias),
          )
          return net(data)
  
      init_fn, apply_fn = transform.transform(f)
      out = apply_fn(init_fn(random.PRNGKey(428)), None)
      self.assertEqual(out.shape, (1, 8, 8, 9))
  
imports: from absl.testing import absltest
  from absl.testing import parameterized
  from haiku._src import depthwise_conv
  from haiku._src import initializers
  from haiku._src import transform
  from jax import random
  import jax.numpy
  import numpy
label_desc: Use image node_id 3 for calling the DepthwiseConv2DTest obj's underlying member method code with example usage: obj.test_channel_multiplier(with_bias) and returns: net