code: def test_defaults(
      self,
      TransposedConv3DLayerImpl,
      DummyInputLayer,
      input,
      kernel,
      output,
      kwargs,
  ):
      b, c, d, h, w = input.shape
      input_layer = DummyInputLayer((b, c, d, h, w))
      try:
          layer = TransposedConv3DLayerImpl(
              input_layer,
              num_filters=kernel.shape[0],
              filter_size=kernel.shape[2:],
              W=kernel.transpose(1, 0, 2, 3, 4),
              **kwargs,
          )
          actual = layer.get_output_for(input).eval()
          assert actual.shape == output.shape
          # layer.output_shape == actual.shape or None
          assert all(
              [
                  s1 == s2
                  for (s1, s2) in zip(actual.shape, output.shape)
                  if s2
              ]
          )
          assert np.allclose(actual, output)
          # Check get_output_shape_for for symbolic output
          if "output_size" in kwargs and isinstance(
              kwargs["output_size"], T.Variable
          ):
              assert all(
                  el is None
                  for el in layer.get_output_shape_for(input.shape)[2:]
              )
      except NotImplementedError:
          pytest.skip()
  
imports: import numpy
  import pytest
  import importlib
  import theano
  from theano import tensor
  import lasagne
  from lasagne.utils import floatX, as_tuple
label_desc: Use image node_id 2 for calling the TestTransposedConv3DLayer obj's underlying member method code with example usage: obj.test_defaults(TransposedConv3DLayerImpl, DummyInputLayer, input, kernel, output, kwargs) without return types