code: def test_conv_transpose():
      axes = [(0, 2, 1, 3), (0, 2, 3, 1), (1, 2, 3, 0), (3, 2, 1, 0)]
      a = np.random.rand(10, 16, 50, 50)
      b = np.random.rand(32, 16, 3, 3)
      x = mx.nd.array(a)
      w = mx.nd.array(b)
      y = mx.nd.Convolution(
          data=x,
          weight=w,
          kernel=(3, 3),
          num_group=1,
          num_filter=32,
          no_bias=True,
      )
      for axis in axes:
          t = mx.nd.transpose(y, axis)
          t.wait_to_read()
          s = y.asnumpy()
          n = np.transpose(s, axis)
          np.allclose(t.asnumpy(), n)
  
imports: import sys
  import os
  import numpy
  import mxnet
  import pytest
  from mxnet.test_utils import rand_ndarray, assert_almost_equal
  from mxnet import gluon, context, use_np
  from mxnet.gluon import nn
  from mxnet.test_utils import *
  import itertools
label_desc: Use image node_id 21 for calling a global function with example usage: test_conv_transpose() without return types