code: def test_valid_input_mask(self):
      n = 2
      input_shape = [2, 4] + [16] * n
      data = jnp.zeros(input_shape)
      net = conv.ConvNDTranspose(
          n,
          output_channels=3,
          kernel_shape=3,
          data_format="channels_first",
          mask=jnp.zeros([3, 3, 3, 4]),
      )
      out = net(data)
      expected_output_shape = (2, 3, 16, 16)
      self.assertEqual(out.shape, expected_output_shape)
  
imports: from absl.testing import absltest
  from absl.testing import parameterized
  from haiku._src import conv
  from haiku._src import initializers
  from haiku._src import test_utils
  from haiku._src import transform
  import jax
  from jax import random
  import jax.numpy
  import numpy
label_desc: Use image node_id 9 for calling the ConvTransposeTest obj's underlying member method code with example usage: obj.test_valid_input_mask() without return types