code: def testConv2DTransposeShapeInference(self):
      # Test case for 8972
      initializer = random_ops.truncated_normal(
          [3, 3, 5, 1], mean=0.0, stddev=0.01, dtype=dtypes.float32
      )
      x = variables.Variable(random_ops.random_normal([3, 10, 5, 1]))
      f = variable_scope.get_variable("f", initializer=initializer)
      f_shape = array_ops_stack.stack([array_ops.shape(x)[0], 10, 5, 5])
      output = nn_ops.conv2d_transpose(
          x, f, f_shape, strides=[1, 1, 1, 1], padding="SAME"
      )
      self.assertEqual(output.get_shape().as_list(), [3, 10, 5, 5])
  
imports: import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import gradient_checker
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.ops import variables
  import tensorflow.python.ops.nn_grad
  from tensorflow.python.platform import test
label_desc: Use image node_id 8 for calling the Conv2DTransposeTest obj's underlying member method code with example usage: obj.testConv2DTransposeShapeInference() without return types