docs: def stop_gradient(cls, x: 'TensorFluent') -> 'TensorFluent':
          '''Returns a copy of the input fluent with stop_gradient at tensor level.
  
          Args:
              x: The input fluent.
  
          Returns:
              A TensorFluent that stops backpropagation of gradient computations.
          '''
          scope = x.scope.as_list()
          batch = x.batch
          return TensorFluent(tf.stop_gradient(x.tensor), scope, batch)