code: def testMean(self):
      mean_fn = lambda x: x[:, 0] ** 2
      kernel = psd_kernels.ExponentiatedQuadratic()
      index_points = np.expand_dims(
          np.random.uniform(-1.0, 1.0, 10), -1
      )
      gp = gaussian_process.GaussianProcess(
          kernel, index_points, mean_fn=mean_fn, validate_args=True
      )
      expected_mean = mean_fn(index_points)
      self.assertAllClose(expected_mean, self.evaluate(gp.mean()))
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import gaussian_process
  from tensorflow_probability.python.distributions import gaussian_process_regression_model
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.math import psd_kernels
  from tensorflow_probability.python.math.psd_kernels.internal import test_util
label_desc: Use image node_id 3 for calling the _GaussianProcessTest obj's underlying member method code with example usage: obj.testMean() without return types