enable to show the fp and bp point

mindinsight/backend/profiler/profile_api.py

@@ -146,6 +146,7 @@ def get_training_trace_graph():
             'step_id': graph_type
         }})
     graph_info['summary'] = analyser.summary
+    graph_info['point_info'] = analyser.point_info
     return jsonify(graph_info)
 
 

mindinsight/profiler/analyser/step_trace_analyser.py

@@ -14,11 +14,13 @@
 # ============================================================================
 """The StepTraceAnalyser analyser class."""
 import csv
+import json
+import os
 
 from mindinsight.datavisual.utils.tools import to_int
 from mindinsight.profiler.analyser.base_analyser import BaseAnalyser
 from mindinsight.profiler.common.exceptions.exceptions import ProfilerParamValueErrorException, \
-    ProfilerFileNotFoundException, StepNumNotSupportedException
+    ProfilerFileNotFoundException, StepNumNotSupportedException, ProfilerRawFileException
 from mindinsight.profiler.common.log import logger as log
 from mindinsight.profiler.common.util import query_latest_trace_time_file, get_field_value, \
     get_summary_for_step_trace, to_millisecond
@@ -31,6 +33,7 @@ class StepTraceAnalyser(BaseAnalyser):
     _attr_ui_name = 'name'
     _attr_ui_start = 'start'
     _attr_ui_duration = 'duration'
+    _point_info = {}
 
     @property
     def summary(self):
@@ -40,6 +43,11 @@ class StepTraceAnalyser(BaseAnalyser):
         summary['total_steps'] = self._size
         return summary
 
+    @property
+    def point_info(self):
+        """The property of point info."""
+        return self._point_info
+
     def query(self, condition=None):
         """
         Query data according to the condition.
@@ -90,6 +98,18 @@ class StepTraceAnalyser(BaseAnalyser):
             self._data = list(csv_reader)
         self._size = len(self._data) - 1
         self._display_col_names = self._col_names[:]
+        self._load_point_info()
+
+    def _load_point_info(self):
+        """Load point info."""
+        file_path = os.path.join(self._profiling_dir, 'step_trace_point_info.json')
+        if os.path.isfile(file_path):
+            with open(file_path, 'r', encoding='utf-8') as file:
+                try:
+                    self._point_info = json.load(file)
+                except (json.JSONDecodeError, TypeError) as err:
+                    log.exception(err)
+                    raise ProfilerRawFileException('Fail to parse point info file.')
 
     def _filter(self, filter_condition):
         """

mindinsight/profiler/parser/step_trace_parser.py

@@ -14,6 +14,7 @@
 # ============================================================================
 """The parser for step trace data."""
 import csv
+import json
 import os
 import stat
 import struct
@@ -41,6 +42,8 @@ class StepTraceParser:
         skip_first_step (bool): Whether skip the first step or not.
     """
     _event_size = 20
+    _fp_tag = 1
+    _bp_tag = 2
 
     def __init__(self, input_dir, output_file_path, job_id=0, skip_first_step=False):
         self._input_dir = input_dir
@@ -80,6 +83,30 @@ class StepTraceParser:
         else:
             log.info("Finish to save intermediate result for step trace file.")
 
+    def record_point_info(self, point_info, output_path):
+        """
+        Record point info into json.
+
+        Args:
+            point_info (dict): The point info about tag id and relative op name.
+            output_path (str): The output path for saving point info.
+
+        Returns:
+            dict, parsed point info.
+        """
+        points = {
+            'fp_start': point_info.get(self._fp_tag, ''),
+            'bp_end': point_info.get(self._bp_tag, '')
+        }
+        try:
+            with open(output_path, 'w') as json_file:
+                json.dump(points, json_file)
+            os.chmod(output_path, stat.S_IREAD)
+        except (IOError, OSError) as err:
+            log.warning('Failed to save point info. %s', err)
+            raise ProfilerIOException
+        return points
+
     def _get_step_trace_files(self):
         """Get step trace files."""
         # step trace files may under $profiler_dir or $profiler_dir/data
@@ -169,8 +196,8 @@ class StepTraceParser:
         min_job_id = 255
         step_flag: bool = lambda tag: tag > min_job_id or tag == 0
         end_flag: bool = lambda tag: tag == min_job_id
-        fp_flag: bool = lambda tag: tag == 1
-        bp_flag: bool = lambda tag: tag == 2
+        fp_flag: bool = lambda tag: tag == self._fp_tag
+        bp_flag: bool = lambda tag: tag == self._bp_tag
 
         def _on_step_event():
             """Handle step event."""

mindinsight/profiler/profiling.py

@@ -245,16 +245,24 @@ class Profiler:
             self._output_path,
             f'step_trace_raw_{self._dev_id}_detail_time.csv'
         )
+        point_info_file_path = os.path.join(
+            self._output_path,
+            'step_trace_point_info.json'
+        )
         # whether keep the first step
         skip_first_step_flag = framework_parser.check_op_name(INIT_OP_NAME)
+        point_info = framework_parser.point_info
         # parser the step trace files and save the result to disk
         parser = StepTraceParser(input_dir=source_path,
                                  output_file_path=step_trace_intermediate_file_path,
                                  job_id=self._job_id_env,
                                  skip_first_step=skip_first_step_flag)
         parser.parse_and_save()
+        point_info = parser.record_point_info(point_info, point_info_file_path)
         # print parser result
         parser.show()
+        logger.info("Finish saving the intermediate result: %s", step_trace_intermediate_file_path)
+        logger.info("The point info is: %s", point_info)
 
     def _analyse_timeline(self):
         """

tests/st/func/profiler/test_analyse.py

@@ -74,6 +74,20 @@ class TestProfilerAnalyse(TestCase):
         output_files = os.listdir(self.profiler)
         assert self.step_trace_file in output_files
 
+    @pytest.mark.level0
+    @pytest.mark.env_single
+    @pytest.mark.platform_x86_cpu
+    @pytest.mark.platform_arm_ascend_training
+    @pytest.mark.platform_x86_gpu_training
+    @pytest.mark.platform_x86_ascend_training
+    def test_step_trace_point_info(self):
+        """Test the step trace file has been generated"""
+        point_info = self.step_trace_analyser.point_info
+        assert point_info == {
+            'fp_start': 'Default/Cast-op6',
+            'bp_end': 'Default/TransData-op7'
+        }
+
     @pytest.mark.level0
     @pytest.mark.env_single
     @pytest.mark.platform_x86_cpu

tests/utils/resource/JOB3/Framework.host.vm.point.1.slice_0

+1 Default/Cast-op6
+2 Default/TransData-op7
+3 Default/network-WithLossCell/_backbone-ResNet/conv1-Conv2d/Cast-op5
+4 Default/network-WithLossCell/_backbone-ResNet/layer1-SequentialCell/0-ResidualBlock/conv1-Conv2d/Cast-op28