!1258 Return empty step trace data to UI in heterogeneous training scene

From: @gzhcv
Reviewed-by: @ouwenchang,@lilongfei15
Signed-off-by: @lilongfei15

mindinsight/backend/profiler/profile_api.py

@@ -156,6 +156,12 @@ def get_training_trace_graph():
         }})
     graph_info['summary'] = analyser.summary
     graph_info['point_info'] = analyser.point_info
+
+    # In heterogeneous training scene, do not display step trace data.
+    cpu_op_type_file_name = f"cpu_op_type_info_{device_id}.csv"
+    if cpu_op_type_file_name in os.listdir(profiler_dir_abs):
+        graph_info = {}
+
     return jsonify(graph_info)
 
 

mindinsight/ui/src/locales/en-us.json

@@ -388,7 +388,7 @@
     "opNum": "Number of operators:",
     "opTimes": "Total operator execution times:",
     "features": "Functions:",
-    "iterationInfo": "The step trace displays the duration of each step from the start of the previous iteration to the end of the step. The main time is divided into three parts: step interval, forward and backward propagation, and step tail.",
+    "iterationInfo": "The step trace displays the duration of each step from the start of the previous iteration to the end of the step. The main time is divided into three parts: step interval, forward and backward propagation, and step tail.(Note that this feature do not support heterogeneous training scene)",
     "iterationGapInfo": "Reads data from data queues. If this part takes a long time, you are advised to check the data processing for further analysis.",
     "fpbpTitle": "Forward and Backward Propagation",
     "fpbpInfo": "Executes the forward and backward operators on the network, which carry the main calculation work of a step. If this part takes a long time, you are advised to check the operator statistics or timeline for further analysis.",

mindinsight/ui/src/locales/zh-cn.json

@@ -387,7 +387,7 @@
     "opNum": "算子数目：",
     "opTimes": "算子执行总次数：",
     "features": "功能介绍：",
-    "iterationInfo": "迭代轨迹展示的是每个step从上个迭代开始至该step结束的耗时信息，主体时间分为3部分：迭代间隙、前向反向、迭代拖尾。",
+    "iterationInfo": "迭代轨迹展示的是每个step从上个迭代开始至该step结束的耗时信息，主体时间分为3部分：迭代间隙、前向反向、迭代拖尾。(该特性暂不支持异构训练场景)",
     "iterationGapInfo": "主要负责从数据队列中读取数据，如果该部分耗时较长，建议前往数据处理部分进一步分析；",
     "fpbpTitle": "前向反向",
     "fpbpInfo": "执行网络中的前向算子以及反向算子，承载了一个step主要的计算工作，如果该部分耗时较长，建议前往算子统计或时间线中进一步分析；",