code: def _test_gradient(self, x_shape, f_shape, dilation_rate, padding):
      x_val = np.random.random_sample(x_shape).astype(np.float32)
      f_val = np.random.random_sample(f_shape).astype(np.float32)
      x = constant_op.constant(x_val, name="x", dtype=dtypes.float32)
      f = constant_op.constant(f_val, name="f", dtype=dtypes.float32)
      output = nn_ops.convolution(
          input=x,
          filter=f,
          dilation_rate=dilation_rate,
          padding=padding,
      )
      y_shape = output.get_shape().as_list()
      err = gradient_checker.compute_gradient_error(
          [x, f], [x_shape, f_shape], output, y_shape
      )
      err_tolerance = 1e-2
      self.assertLess(err, err_tolerance)
  
imports: import contextlib
  import numpy
  from tensorflow.python.eager import context
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gradient_checker
  from tensorflow.python.ops import nn_ops
  import tensorflow.python.ops.nn_grad
  from tensorflow.python.platform import test
label_desc: Use image node_id 10 for calling the AtrousConvolutionTest obj's underlying member method code with example usage: obj._test_gradient(x_shape, f_shape, dilation_rate, padding) without return types