code: def test_dimshuffle_false_get_output_for(self, DummyInputLayer):
      try:
          from lasagne.layers.cuda_convnet import Conv2DCCLayer
      except ImportError:
          pytest.skip("cuda_convnet not available")
  
      # this implementation is tested against FilterActs instead of
      # theano.tensor.nnet.conv.conv2d because using the latter leads to
      # numerical precision errors.
      from pylearn2.sandbox.cuda_convnet.filter_acts import FilterActs
  
      filter_acts = FilterActs(stride=1, pad=0, partial_sum=1)
  
      input = theano.shared(floatX(np.random.random((4, 5, 5, 8))))
      kernel = theano.shared(floatX(np.random.random((4, 3, 3, 16))))
  
      input_layer = DummyInputLayer(
          (4, 5, 5, 8)
      )  # c01b instead of bc01
      layer = Conv2DCCLayer(
          input_layer,
          num_filters=16,
          filter_size=(3, 3),
          dimshuffle=False,
          W=kernel,
          b=None,
          nonlinearity=None,
      )
  
      output = np.array(filter_acts(input, kernel).eval())
  
      actual = layer.get_output_for(input).eval()
      actual = np.array(actual)
      assert actual.shape == output.shape
      assert actual.shape == layer.output_shape
      assert np.allclose(actual, output)
  
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 5 for calling the TestConv2DCCLayer obj's underlying member method code with example usage: obj.test_dimshuffle_false_get_output_for(DummyInputLayer) without return types