tensorflow_probability/python/monte_carlo/expectation.py
def _get_samples(dist, z, n, seed):
  """Check args and return samples."""
  with tf.compat.v1.name_scope('get_samples', values=[z, n]):
    if (n is None) == (z is None):
      raise ValueError(
          'Must specify exactly one of arguments "n" and "z".  Found: '
          'n = %s, z = %s' % (n, z))
    if n is not None:
      return dist.sample(n, seed=seed)
    else:
      return tf.convert_to_tensor(value=z, name='z')
def _get_samples(dist, z, n, seed):
  """Check args and return samples."""
  with tf.compat.v1.name_scope('get_samples', values=[z, n]):
    if (n is None) == (z is None):
      raise ValueError(
          'Must specify exactly one of arguments "n" and "z".  Found: '
          'n = %s, z = %s' % (n, z))
    if n is not None:
      return dist.sample(n, seed=seed)
    else:
      return tf.convert_to_tensor(value=z, name='z')
def _get_samples ( dist , z , n , seed ) : with tf . compat . v1 . name_scope ( 'get_samples' , values = [ z , n ] ) : if ( n is None ) == ( z is None ) : raise ValueError ( 'Must specify exactly one of arguments "n" and "z".  Found: ' 'n = %s, z = %s' % ( n , z ) ) if n is not None : return dist . sample ( n , seed = seed ) else : return tf . convert_to_tensor ( value = z , name = 'z' )
Check args and return samples.
Check args and return samples .