[Python-checkins] Print summary stats for overall success of specialization. (GH-31211)

[markshannon]

https://github.com/python/cpython/commit/328fe3fd2034a91a15b77a24a307e218d02d7bf1
commit: 328fe3fd2034a91a15b77a24a307e218d02d7bf1
branch: main
author: Mark Shannon <mark at hotpy.org>
committer: markshannon <mark at hotpy.org>
date: 2022-02-08T11:50:02Z
summary:

Print summary stats for overall success of specialization. (GH-31211)

files:
M Tools/scripts/summarize_stats.py

diff --git a/Tools/scripts/summarize_stats.py b/Tools/scripts/summarize_stats.py
index 6d0020739a31f..1271c194e96a1 100644
--- a/Tools/scripts/summarize_stats.py
+++ b/Tools/scripts/summarize_stats.py
@@ -77,6 +77,33 @@ def extract_opcode_stats(stats):
     return opcode_stats
 
 
+def categorized_counts(opcode_stats):
+    basic = 0
+    specialized = 0
+    not_specialized = 0
+    specialized_instructions = {
+        op for op in opcode._specialized_instructions
+        if "__" not in op and "ADAPTIVE" not in op}
+    adaptive_instructions = {
+        op for op in opcode._specialized_instructions
+        if "ADAPTIVE" in op}
+    for i, opcode_stat in enumerate(opcode_stats):
+        if "execution_count" not in opcode_stat:
+            continue
+        count = opcode_stat['execution_count']
+        name = opname[i]
+        if "specializable" in opcode_stat:
+            not_specialized += count
+        elif name in adaptive_instructions:
+            not_specialized += count
+        elif name in specialized_instructions:
+            miss = opcode_stat.get("specialization.miss", 0)
+            not_specialized += miss
+            specialized += count - miss
+        else:
+            basic += count
+    return basic, not_specialized, specialized
+
 def main():
     stats = gather_stats()
     opcode_stats = extract_opcode_stats(stats)
@@ -102,6 +129,11 @@ def main():
     for i, opcode_stat in enumerate(opcode_stats):
         name = opname[i]
         print_specialization_stats(name, opcode_stat)
+    basic, not_specialized, specialized = categorized_counts(opcode_stats)
+    print("Specialization effectiveness:")
+    print(f"    Base instructions {basic} {basic*100/total:0.1f}%")
+    print(f"    Not specialized {not_specialized} {not_specialized*100/total:0.1f}%")
+    print(f"    Specialized {specialized} {specialized*100/total:0.1f}%")
     print("Call stats:")
     total = 0
     for key, value in stats.items():