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GH-100143: Improve collecting pystats for parts of runs (GH-100144)

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* pystats off by default

* Add -Xpystats flag

* Always dump pystats, even if turned off
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Michael Droettboom 2022-12-12 09:50:43 -05:00 • committed by GitHub
parent e4ea33b178
commit 1583c6e326
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4 changed files with 48 additions and 25 deletions
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48
Tools/scripts/summarize_stats.py
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@ -34,6 +34,16 @@ opmap = dict(sorted(opmap.items()))
TOTAL = "specialization.deferred", "specialization.hit", "specialization.miss", "execution_count"
def format_ratio(num, den):
"""
Format a ratio as a percentage. When the denominator is 0, returns the empty
string.
"""
if den == 0:
return ""
else:
return f"{num/den:.01%}"
def join_rows(a_rows, b_rows):
"""
Joins two tables together, side-by-side, where the first column in each is a
@ -87,7 +97,7 @@ def calculate_specialization_stats(family_stats, total):
continue
else:
label = key
rows.append((f"{label:>12}", f"{family_stats[key]:>12}", f"{100*family_stats[key]/total:0.1f}%"))
rows.append((f"{label:>12}", f"{family_stats[key]:>12}", format_ratio(family_stats[key], total)))
return rows
def calculate_specialization_success_failure(family_stats):
@ -100,7 +110,7 @@ def calculate_specialization_success_failure(family_stats):
label = key[len("specialization."):]
label = label[0].upper() + label[1:]
val = family_stats.get(key, 0)
rows.append((label, val, f"{100*val/total_attempts:0.1f}%"))
rows.append((label, val, format_ratio(val, total_attempts)))
return rows
def calculate_specialization_failure_kinds(name, family_stats, defines):
@ -118,7 +128,7 @@ def calculate_specialization_failure_kinds(name, family_stats, defines):
for value, index in failures:
if not value:
continue
rows.append((kind_to_text(index, defines, name), value, f"{100*value/total_failures:0.1f}%"))
rows.append((kind_to_text(index, defines, name), value, format_ratio(value, total_failures)))
return rows
def print_specialization_stats(name, family_stats, defines):
@ -318,11 +328,11 @@ def calculate_execution_counts(opcode_stats, total):
for (count, name, miss) in counts:
cumulative += count
if miss:
miss = f"{100*miss/count:0.1f}%"
miss = format_ratio(miss, count)
else:
miss = ""
rows.append((name, count, f"{100*count/total:0.1f}%",
f"{100*cumulative/total:0.1f}%", miss))
rows.append((name, count, format_ratio(count, total),
format_ratio(cumulative, total), miss))
return rows
def emit_execution_counts(opcode_stats, total):
@ -386,9 +396,9 @@ def emit_comparative_specialization_stats(base_opcode_stats, head_opcode_stats):
def calculate_specialization_effectiveness(opcode_stats, total):
basic, not_specialized, specialized = categorized_counts(opcode_stats)
return [
("Basic", basic, f"{basic*100/total:0.1f}%"),
("Not specialized", not_specialized, f"{not_specialized*100/total:0.1f}%"),
("Specialized", specialized, f"{specialized*100/total:0.1f}%"),
("Basic", basic, format_ratio(basic, total)),
("Not specialized", not_specialized, format_ratio(not_specialized, total)),
("Specialized", specialized, format_ratio(specialized, total)),
]
def emit_specialization_overview(opcode_stats, total):
@ -405,7 +415,7 @@ def emit_specialization_overview(opcode_stats, total):
counts.sort(reverse=True)
if total:
with Section(f"{title} by instruction", 3):
rows = [ (name, count, f"{100*count/total:0.1f}%") for (count, name) in counts[:10] ]
rows = [ (name, count, format_ratio(count, total)) for (count, name) in counts[:10] ]
emit_table(("Name", "Count:", "Ratio:"), rows)
def emit_comparative_specialization_overview(base_opcode_stats, base_total, head_opcode_stats, head_total):
@ -432,15 +442,15 @@ def calculate_call_stats(stats):
rows = []
for key, value in stats.items():
if "Calls to" in key:
rows.append((key, value, f"{100*value/total:0.1f}%"))
rows.append((key, value, format_ratio(value, total)))
elif key.startswith("Calls "):
name, index = key[:-1].split("[")
index = int(index)
label = name + " (" + pretty(defines[index][0]) + ")"
rows.append((label, value, f"{100*value/total:0.1f}%"))
rows.append((label, value, format_ratio(value, total)))
for key, value in stats.items():
if key.startswith("Frame"):
rows.append((key, value, f"{100*value/total:0.1f}%"))
rows.append((key, value, format_ratio(value, total)))
return rows
def emit_call_stats(stats):
@ -468,13 +478,13 @@ def calculate_object_stats(stats):
for key, value in stats.items():
if key.startswith("Object"):
if "materialize" in key:
ratio = f"{100*value/total_materializations:0.1f}%"
ratio = format_ratio(value, total_materializations)
elif "allocations" in key:
ratio = f"{100*value/total_allocations:0.1f}%"
ratio = format_ratio(value, total_allocations)
elif "increfs" in key:
ratio = f"{100*value/total_increfs:0.1f}%"
ratio = format_ratio(value, total_increfs)
elif "decrefs" in key:
ratio = f"{100*value/total_decrefs:0.1f}%"
ratio = format_ratio(value, total_decrefs)
else:
ratio = ""
label = key[6:].strip()
@ -517,8 +527,8 @@ def emit_pair_counts(opcode_stats, total):
for (count, pair) in itertools.islice(pair_counts, 100):
i, j = pair
cumulative += count
rows.append((opname[i] + " " + opname[j], count, f"{100*count/total:0.1f}%",
f"{100*cumulative/total:0.1f}%"))
rows.append((opname[i] + " " + opname[j], count, format_ratio(count, total),
format_ratio(cumulative, total)))
emit_table(("Pair", "Count:", "Self:", "Cumulative:"),
rows
)