class_docstr: Common tests for noisy mixture distributions.
code: def test_uniform_is_special_case(self):
      # With the scale parameters going to zero, the adapted distribution should
      # approach a mixture of unit-width uniform distributions.
      dist = self.dist_cls(
          loc=[2.5, -1.0], scale=[1e-7, 1e-7], weight=[0.3, 0.7]
      )
      mean = dist.components_distribution.mean()
      x = tf.linspace(mean[0] - 1, mean[0] + 1, 10)
      self.assertAllClose(
          dist.prob(x), [0, 0, 0, 0.3, 0.3, 0.3, 0.3, 0, 0, 0]
      )
      x = tf.linspace(mean[1] - 1, mean[1] + 1, 10)
      self.assertAllClose(
          dist.prob(x), [0, 0, 0, 0.7, 0.7, 0.7, 0.7, 0, 0, 0]
      )
  
imports: import tensorflow
  from tensorflow_compression.python.distributions import helpers
  from tensorflow_compression.python.distributions import uniform_noise
label_desc: Use image node_id 4 for calling the MixtureTest obj's underlying member method code with example usage: obj.test_uniform_is_special_case() without return types