code: def _testUniformSampleMultiDimensional(self):
      # DISABLED: Please enable this test once b/issues/30149644 is resolved.
      batch_size = 2
      a_v = [3.0, 22.0]
      b_v = [13.0, 35.0]
      a = tf.constant([a_v] * batch_size)
      b = tf.constant([b_v] * batch_size)
  
      dist = uniform.Uniform(low=a, high=b, validate_args=True)
  
      n_v = 100000
      n = tf.constant(n_v)
      samples = dist.sample(n, seed=test_util.test_seed())
      self.assertEqual(samples.shape, (n_v, batch_size, 2))
  
      sample_values = self.evaluate(samples)
  
      self.assertFalse(
          np.any(sample_values[:, 0, 0] < a_v[0])
          or np.any(sample_values[:, 0, 0] >= b_v[0])
      )
      self.assertFalse(
          np.any(sample_values[:, 0, 1] < a_v[1])
          or np.any(sample_values[:, 0, 1] >= b_v[1])
      )
  
      self.assertAllClose(
          sample_values[:, 0, 0].mean(),
          (a_v[0] + b_v[0]) / 2,
          atol=1e-2,
      )
      self.assertAllClose(
          sample_values[:, 0, 1].mean(),
          (a_v[1] + b_v[1]) / 2,
          atol=1e-2,
      )
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import uniform
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 10 for calling the UniformTest obj's underlying member method code with example usage: obj._testUniformSampleMultiDimensional() without return types