Fix result reporting and enable INFO logging in Fleetbench parallel benchmarks.

PiperOrigin-RevId: 802247987
Change-Id: I8de0e80cf541aca3b39b412a506d1760cdcb4a82

Author: liyuying0000

fleetbench/parallel/parallel_bench.py

@@ -210,6 +210,9 @@ def main(argv: Sequence[str]) -> None:
   if len(argv) > 1:
     raise app.UsageError("Too many command-line arguments.")
 
+  # Sets the logging threshold to INFO.
+  logging.set_stderrthreshold(logging.INFO)
+
   shutil.rmtree(_TEMP_ROOT.value, ignore_errors=True)
   os.makedirs(_TEMP_ROOT.value, exist_ok=True)
 

fleetbench/parallel/reporter.py

@@ -314,18 +314,25 @@ def GenerateFinalReport(
     # we simply copy the single run report to the final report.
     input_file = os.path.join(output_dir, "run_0", "results.json")
     if os.path.exists(input_file):
-      with open(input_file, "r") as infile, open(output_file, "w") as outfile:
-        outfile.write(infile.read())
+      with open(input_file, "r") as infile:
+        content = infile.read()
+      with open(output_file, "w") as outfile:
+        outfile.write(content)
+
+      # load the data from the content so we can print the summary.
+      json_data = json.loads(content)
+      data = json_data.get("benchmarks", [])  # Safely get the benchmark data
+
     else:
       logging.warning(
           "Warning: results.json not found in %s",
           os.path.join(output_dir, "run_0"),
       )
-    return
-
-  context = AggregateFinalContext(context_list)
-  data = AggregateFinalData(data_list)
-  _SaveFile(output_file, data, context)
+      return
+  else:
+    context = AggregateFinalContext(context_list)
+    data = AggregateFinalData(data_list)
+    _SaveFile(output_file, data, context)
 
   df = pd.DataFrame(data)
   selected_columns = [

fleetbench/parallel/reporter_test.py

@@ -392,7 +392,8 @@ def test_generate_final_report_single_repetition_perf_counters(self):
     os.makedirs(run_0_dir)
     input_content = (
         '{"context": {"key": "value"}, "benchmarks": [{"name": "benchmark_1",'
-        ' "metric_1": 10, "cycles": 100}]}'
+        ' "Count": 1, "real_time": 10, "cpu_time": 10  , "metric_1": 10,'
+        ' "cycles": 100}]}'
     )
     with open(os.path.join(run_0_dir, "results.json"), "w") as f:
       f.write(input_content)