docstr: Sampling from the Standard Normal Distribution.
docstr_tok: ["Sampling","from","the","Standard","Normal","Distribution","."]
code: def testRWM1DUniform(self):
      """Sampling from the Standard Normal Distribution."""
      dtype = np.float32
  
      target = normal.Normal(loc=dtype(0), scale=dtype(1))
  
      samples = sample.sample_chain(
          num_results=2000,
          current_state=dtype(1),
          kernel=random_walk_metropolis.RandomWalkMetropolis(
              target.log_prob,
              new_state_fn=random_walk_metropolis.random_walk_uniform_fn(
                  scale=dtype(2.0)
              ),
          ),
          num_burnin_steps=500,
          trace_fn=None,
          seed=test_util.test_seed(),
      )
  
      sample_mean = tf.math.reduce_mean(samples, axis=0)
      sample_std = tf.math.reduce_std(samples, axis=0)
      [sample_mean_, sample_std_] = self.evaluate(
          [sample_mean, sample_std]
      )
  
      self.assertAllClose(0.0, sample_mean_, atol=0.17, rtol=0.0)
      self.assertAllClose(1.0, sample_std_, atol=0.2, rtol=0.0)
  
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import cauchy
  from tensorflow_probability.python.distributions import mvn_tril
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import distribute_lib
  from tensorflow_probability.python.internal import distribute_test_lib
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.mcmc import random_walk_metropolis
  from tensorflow_probability.python.mcmc import sample
label_desc: Use image node_id 1 for calling the RWMTest obj's underlying member method code with example usage: obj.testRWM1DUniform() without return types