docs: def Uniform(cls,
              low: 'TensorFluent', high: 'TensorFluent',
              batch_size: Optional[int] = None) -> Tuple[Distribution, 'TensorFluent']:
          '''Returns a TensorFluent for the Uniform sampling op with given low and high parameters.
  
          Args:
              low: The low parameter of the Uniform distribution.
              high: The high parameter of the Uniform distribution.
              batch_size: The size of the batch (optional).
  
          Returns:
              The Uniform distribution and a TensorFluent sample drawn from the distribution.
  
          Raises:
              ValueError: If parameters do not have the same scope.
          '''
          if low.scope != high.scope:
              raise ValueError('Uniform distribution: parameters must have same scope!')
          dist = tf.distributions.Uniform(low.tensor, high.tensor)
          batch = low.batch or high.batch
          if not batch and batch_size is not None:
              t = dist.sample(batch_size)
              batch = True
          else:
              t = dist.sample()
          scope = low.scope.as_list()
          return (dist, TensorFluent(t, scope, batch=batch))