hunk.code_window:         else:
               self.devices = ["/gpu:{}".format(i) for i in range(num_gpus)]
           logger.info("TFMultiGPULearner devices {}".format(self.devices))
           assert self.train_batch_size % len(self.devices) == 0
           assert self.train_batch_size >= len(self.devices), "batch too small"
  
hunk.labels: keep replace keep keep keep
hunk.after_edit:             self.devices = [
                   "/gpu:{}".format(i) for i in range(int(math.ceil(num_gpus)))
               ]
  
hunk.file_path: python/ray/rllib/optimizers/aso_multi_gpu_learner.py
hunk.type: replace
file: // generated automatically, do not modify.
  
  package org.ray.api.function;
  
  /**
   * Functional interface for a remote function that has 5 parameters.
   */
  @FunctionalInterface
  public interface RayFunc5<T0, T1, T2, T3, T4, R> extends RayFunc {
    R apply(T0 t0, T1 t1, T2 t2, T3 t3, T4 t4);
  }
  