code: def test_convolution_transpose_attributes():
      x = C.input_variable((1, 5, 5))
      filter = np.reshape(
          np.array([2, -1, -1, 2], dtype=np.float32), (1, 2, 2)
      )
      kernel = C.constant(value=filter)
      f = C.convolution_transpose(kernel, x, auto_padding=[False])
      d = f.root_function.attributes
      expected = {
          "autoPadding": [False, False, False],
          "sharing": [True, True, True],
          "groups": 1,
          "strides": (1, 1, 1),
          "dilation": (1, 1, 1),
          "maxTempMemSizeInSamples": 0,
          "upperPad": (0, 0, 0),
          "lowerPad": (0, 0, 0),
          "transpose": True,
          "outputShape": (0,),
          "kernelShape": (1, 2, 2),
          "sequential": False,
      }
      _check(expected, d)
  
imports: import cntk
  import numpy
label_desc: Use image node_id 3 for calling a global function with example usage: test_convolution_transpose_attributes() without return types