Setup main in compute score module

Author: pgmpablo157321

mlperf_logging/result_summarizer/compute_score/__main__.py

@@ -1,4 +1,5 @@
 from .. import result_summarizer
+from ...rcp_checker import rcp_checker
 from ...compliance_checker.mlp_compliance import usage_choices, rule_choices
 import argparse
 
@@ -8,40 +9,62 @@ def get_compute_args():
         prog="mlperf_logging.result_summarizer.compute_score",
         description="Compute the score of a single benchmark",
     )
-    parser.add_argument("benchmark", type=str, help="TODO:", required=True)
-    parser.add_argument("system", type=str, help="System name", default=None)
+    parser.add_argument("--benchmark", type=str, help="TODO:", required=True)
+    parser.add_argument("--system", type=str, help="System name", default=None)
     parser.add_argument(
-        "has_power", action="store_true", help="Compute power score as well"
+        "--has_power", action="store_true", help="Compute power score as well"
     )
     parser.add_argument(
-        "benchmark_folder", type=str, help="Folder containing all the result files", required=True
+        "--benchmark_folder", type=str, help="Folder containing all the result files", required=True
     )
     parser.add_argument(
-        "usage",
+        "--usage",
         type=str,
         default="training",
         choices=usage_choices(),
         help="the usage such as training, hpc, inference_edge, inference_server",
         required=True,
     )
     parser.add_argument(
-        "ruleset",
+        "--ruleset",
         type=str,
         choices=rule_choices(),
         help="the ruleset such as 0.6.0, 0.7.0, or 1.0.0",
         required=True,
     )
-
     parser.add_argument(
-        "weak_scaling", action="store_true", help="Compute weak scaling score"
+        "--is_weak_scaling", action="store_true", help="Compute weak scaling score"
+    )
+    parser.add_argument(
+        "--scale", action="store_true", help="Compute the scaling factor"
     )
 
     return parser.parse_args()
 
 
+def print_benchmark_info(args):
+    print(f"MLPerf {args.usage}")
+    print(f"Folder: {args.benchmark_folder}")
+    print(f"Version: {args.ruleset}")
+    print(f"System: {args.system}")
+    print(f"Benchmark: {args.benchmark}")
+
 args = get_compute_args()
 
-if args.weak_scaling:
+if args.scale:
+    rcp_checker.check_directory(
+        args.benchmark_folder, 
+        args.usage,
+        args.ruleset,
+        False,
+        False,
+        rcp_file=None,
+        rcp_pass='pruned_rcps',
+        rcp_bypass=False,
+        set_scaling=True,
+    )
+
+if args.is_weak_scaling:
     scores, power_scores = result_summarizer._compute_weak_score_standalone(
         args.benchmark,
         args.system,
@@ -50,9 +73,10 @@ def get_compute_args():
         args.usage,
         args.ruleset,
     )
+    print_benchmark_info(args)
     print(f"Scores: {scores}")
     if power_scores:
-        print(f"Power Scores: {power_scores}")
+        print(f"Power Scores - Energy (kJ): {power_scores}")
 else:
     score, power_score = result_summarizer._compute_strong_score_standalone(
         args.benchmark,
@@ -62,6 +86,7 @@ def get_compute_args():
         args.usage,
         args.ruleset,
     )
-    print(f"Score: {score}")
+    print_benchmark_info(args)
+    print(f"Score - Time to Train (minutes): {score}")
     if power_score:
-        print(f"Power Score: {power_score}")
+        print(f"Power Score - Energy (kJ): {power_score}")