with SummaryRecord to enforce closing

tutorials/source_en/advanced_use/visualization_tutorials.md

@@ -148,7 +148,7 @@ def test_summary():
 
     # Init SummaryRecord and specify a folder for storing summary log files
     # and specify the graph that needs to be recorded
-    summary_writer = SummaryRecord(log_dir='./summary', network=net)
+    with SummaryRecord(log_dir='./summary', network=net) as summary_writer:
         summary_callback = SummaryStep(summary_writer, flush_step=10)
 
         # Init TrainLineage to record the training information
@@ -164,9 +164,6 @@ def test_summary():
         # Prepare mindrecord_dataset for testing
         eval_ds = create_mindrecord_dataset_for_testing()
         model.eval(eval_ds, callbacks=[eval_callback])
-
-    # Note: Make sure to close summary
-    summary_writer.close()
 ```
 
 Use the `save_graphs` option of `context` to record the computational graph after operator fusion.
@@ -174,6 +171,7 @@ Use the `save_graphs` option of `context` to record the computational graph afte
 
 > - Currently MindSpore supports recording computational graph after operator fusion for Ascend 910 AI processor only.
 > - It's recommended that you reduce calls to `HistogramSummary` under 10 times per batch. The more you call `HistogramSummary`, the more performance overhead.
+> - Please use the *with statement* to ensure that `SummaryRecord` is properly closed at the end, otherwise the process may fail to exit.
 
 ## MindInsight Commands
 

tutorials/source_zh_cn/advanced_use/visualization_tutorials.md

@@ -154,7 +154,7 @@ def test_summary():
 
     # Init SummaryRecord and specify a folder for storing summary log files
     # and specify the graph that needs to be recorded
-    summary_writer = SummaryRecord(log_dir='./summary', network=net)
+    with SummaryRecord(log_dir='./summary', network=net) as summary_writer:
         summary_callback = SummaryStep(summary_writer, flush_step=10)
 
         # Init TrainLineage to record the training information
@@ -170,9 +170,6 @@ def test_summary():
         # Prepare mindrecord_dataset for testing
         eval_ds = create_mindrecord_dataset_for_testing()
         model.eval(eval_ds, callbacks=[eval_callback])
-
-    # Note: Make sure to close summary
-    summary_writer.close()
 ```
 
 可以通过脚本中`context`的`save_graphs`选项配置记录算子融合后的计算图。
@@ -180,6 +177,7 @@ def test_summary():
 
 > - 目前MindSpore仅支持在Ascend 910 AI处理器上导出算子融合后的计算图。
 > - 一个batch中，`HistogramSummary`算子的调用次数请尽量控制在10次以下，调用次数越多，性能开销越大。
+> - 请使用*with语句*确保`SummaryRecord`最后正确关闭，否则可能会导致进程无法退出。
 
 ## MindInsight相关命令