hunk.code_window:                     episode.batch_builder.total(),
                       episode.batch_builder.count) + "are buffered in "
                   "the sampler. If this is more than you expected, check that "
                   "that you set a horizon on your environment correctly. Note "
                   "that in multi-agent environments, `sample_batch_size` sets "
                   "the batch size based on environment steps, not the steps of "
                   "individual agents, which can result in unexpectedly large "
  
hunk.labels: keep keep keep replace replace keep keep
hunk.after_edit:                 "that you set a horizon on your environment correctly and that"
                   " it terminates at some point. "
                   "Note: In multi-agent environments, `sample_batch_size` sets "
  
hunk.file_path: rllib/evaluation/sampler.py
hunk.type: replace
file: package org.ray.streaming.runtime.master.graphmanager;
  
  import org.ray.streaming.jobgraph.JobGraph;
  import org.ray.streaming.runtime.core.graph.executiongraph.ExecutionGraph;
  
  /**
   * Graph manager is one of the important roles of JobMaster. It mainly focuses on graph management.
   *
   * <p>
   * Such as:
   * <ol>
   * <li>Build execution graph from job graph.</li>
   * <li>Do modifications or operations on graph.</li>
   * <li>Query vertex info from graph.</li>
   * </ol>
   * </p>
   */
  public interface GraphManager {
  
    /**
     * Build execution graph from job graph.
     *
     * @param jobGraph logical plan of streaming job.
     * @return physical plan of streaming job.
     */
    ExecutionGraph buildExecutionGraph(JobGraph jobGraph);
  
    /**
     * Get job graph.
     *
     * @return the job graph.
     */
    JobGraph getJobGraph();
  
    /**
     * Get execution graph.
     *
     * @return the execution graph.
     */
    ExecutionGraph getExecutionGraph();
  
  }
  