code: def testStudentSampleMultiDimensional(self):
      batch_size = 7
      df = constant_op.constant([[5.0, 7.0]] * batch_size)
      mu = constant_op.constant([[3.0, -3.0]] * batch_size)
      sigma = constant_op.constant(
          [[math.sqrt(10.0), math.sqrt(15.0)]] * batch_size
      )
      df_v = [5.0, 7.0]
      mu_v = [3.0, -3.0]
      sigma_v = [np.sqrt(10.0), np.sqrt(15.0)]
      n = constant_op.constant(200000)
      student = student_t.StudentT(df=df, loc=mu, scale=sigma)
      samples = student.sample(n, seed=123456)
      sample_values = self.evaluate(samples)
      self.assertEqual(samples.get_shape(), (200000, batch_size, 2))
      self.assertAllClose(
          sample_values[:, 0, 0].mean(), mu_v[0], rtol=0.1, atol=0
      )
      self.assertAllClose(
          sample_values[:, 0, 0].var(),
          sigma_v[0] ** 2 * df_v[0] / (df_v[0] - 2),
          rtol=0.2,
          atol=0,
      )
      self._checkKLApprox(
          df_v[0], mu_v[0], sigma_v[0], sample_values[:, 0, 0]
      )
      self.assertAllClose(
          sample_values[:, 0, 1].mean(), mu_v[1], rtol=0.1, atol=0
      )
      self.assertAllClose(
          sample_values[:, 0, 1].var(),
          sigma_v[1] ** 2 * df_v[1] / (df_v[1] - 2),
          rtol=0.2,
          atol=0,
      )
      self._checkKLApprox(
          df_v[1], mu_v[1], sigma_v[1], sample_values[:, 0, 1]
      )
  
imports: import importlib
  import math
  import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import random_seed
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops.distributions import student_t
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 8 for calling the StudentTTest obj's underlying member method code with example usage: obj.testStudentSampleMultiDimensional() without return types