code: def test_single_input_conv_transpose(self):
      rng = dict(params=random.key(0))
      x = jnp.ones((8, 3))
      conv_transpose_module = nn.ConvTranspose(
          features=4,
          kernel_size=(3,),
          padding="VALID",
          kernel_init=initializers.ones,
          bias_init=initializers.ones,
      )
      y, initial_params = conv_transpose_module.init_with_output(rng, x)
      self.assertEqual(
          initial_params["params"]["kernel"].shape, (3, 3, 4)
      )
      correct_ans = np.array(
          [
              [4.0, 4.0, 4.0, 4.0],
              [7.0, 7.0, 7.0, 7.0],
              [10.0, 10.0, 10.0, 10.0],
              [10.0, 10.0, 10.0, 10.0],
              [10.0, 10.0, 10.0, 10.0],
              [10.0, 10.0, 10.0, 10.0],
              [10.0, 10.0, 10.0, 10.0],
              [10.0, 10.0, 10.0, 10.0],
              [7.0, 7.0, 7.0, 7.0],
              [4.0, 4.0, 4.0, 4.0],
          ]
      )
      np.testing.assert_allclose(y, correct_ans)
  
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 31 for calling the LinearTest obj's underlying member method code with example usage: obj.test_single_input_conv_transpose() without return types