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
      )
      tp = student_t_process.StudentTProcess(
          df=3.0,
          kernel=kernel,
          index_points=index_points,
          mean_fn=mean_fn,
          validate_args=True,
      )
      expected_mean = mean_fn(index_points)
      self.assertAllClose(expected_mean, self.evaluate(tp.mean()))
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import multivariate_student_t
  from tensorflow_probability.python.distributions import student_t_process
  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 _StudentTProcessTest obj's underlying member method code with example usage: obj.testMean() without return types