code: def test_invalid_input_mask(self):
      n = 2
      with self.assertRaisesRegex(
          ValueError,
          "Mask needs to have the same "
          "shape as weights. Shapes are:",
      ):
          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([1, 2, 3]),
          )
          net(data)
  
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 8 for calling the ConvTransposeTest obj's underlying member method code with example usage: obj.test_invalid_input_mask() without return types