code: def test_with_nones(
      self, Conv3DImpl, DummyInputLayer, input, kernel, output, kwargs
  ):
      if kwargs.get("untie_biases", False):
          pytest.skip()
      b, c, d, h, w = input.shape.eval()
      input_layer = DummyInputLayer((None, c, None, None, None))
      try:
          layer = Conv3DImpl(
              input_layer,
              num_filters=kernel.shape[0],
              filter_size=kernel.shape[2:],
              W=kernel,
              **kwargs,
          )
          actual = layer.get_output_for(input).eval()
  
          assert layer.output_shape == (
              None,
              kernel.shape[0],
              None,
              None,
              None,
          )
          assert actual.shape == output.shape
          assert np.allclose(actual, output)
  
      except (NotImplementedError, RuntimeError):
          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 3 for calling the TestConv3DLayerImplementations obj's underlying member method code with example usage: obj.test_with_nones(Conv3DImpl, DummyInputLayer, input, kernel, output, kwargs) without return types