class_docstr: Tests the Autoregressive distribution.
class_docstr_tok: ["Tests","the","Autoregressive","distribution","."]
code: def _normal_fn(self, affine_bijector):
      def _fn(samples):
          scale = tf.exp(affine_bijector.forward(samples))
          return independent.Independent(
              normal.Normal(loc=0.0, scale=scale, validate_args=True),
              reinterpreted_batch_ndims=1,
              validate_args=True,
          )
  
      return _fn
  
imports: import warnings
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import masked_autoregressive
  from tensorflow_probability.python.bijectors import scale_matvec_tril
  from tensorflow_probability.python.distributions import autoregressive
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import sample
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.internal import reparameterization
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import linalg
label_desc: Use image node_id 3 for calling the AutoregressiveTest obj's underlying member method code with example usage: obj._normal_fn(affine_bijector) and returns: _fn, independent