code: def test_transpose_cudnn(self, X, use_axes, gc, dc):
      ndim = len(X.shape)
      axes = np.arange(ndim)
      np.random.shuffle(axes)
  
      if use_axes:
          op = core.CreateOperator(
              "Transpose",
              ["X"],
              ["Y"],
              axes=axes,
              engine="CUDNN",
              device_option=hu.cuda_do,
          )
      else:
          op = core.CreateOperator(
              "Transpose",
              ["X"],
              ["Y"],
              engine="CUDNN",
              device_option=hu.cuda_do,
          )
  
      def transpose_ref(X):
          if use_axes:
              return [np.transpose(X, axes=axes)]
          else:
              return [np.transpose(X)]
  
      self.assertReferenceChecks(hu.gpu_do, op, [X], transpose_ref)
      self.assertGradientChecks(hu.gpu_do, op, [X], 0, [0])
  
file_path: pytorch/caffe2/python/operator_test/transpose_op_test.py
imports: from caffe2.python import core, workspace
  from hypothesis import given, settings
  import caffe2.python.hypothesis_test_util
  import caffe2.python.serialized_test.serialized_test_util
  import hypothesis.strategies
  import numpy
  import unittest
label_desc: Use image node_id 3 for calling the TestTransposeOp obj's underlying member method code with example usage: obj.test_transpose_cudnn(X, use_axes, gc, dc) and returns: list, list