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376 lines
14 KiB
Python
376 lines
14 KiB
Python
"""Print a summary of specialization stats for all files in the
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default stats folders.
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"""
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import collections
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import os.path
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import opcode
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from datetime import date
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import itertools
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import argparse
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import sys
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if os.name == "nt":
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DEFAULT_DIR = "c:\\temp\\py_stats\\"
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else:
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DEFAULT_DIR = "/tmp/py_stats/"
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#Create list of all instruction names
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specialized = iter(opcode._specialized_instructions)
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opname = ["<0>"]
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for name in opcode.opname[1:]:
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if name.startswith("<"):
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try:
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name = next(specialized)
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except StopIteration:
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pass
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opname.append(name)
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# opcode_name --> opcode
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# Sort alphabetically.
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opmap = {name: i for i, name in enumerate(opname)}
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opmap = dict(sorted(opmap.items()))
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TOTAL = "specialization.deferred", "specialization.hit", "specialization.miss", "execution_count"
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def print_specialization_stats(name, family_stats, defines):
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if "specializable" not in family_stats:
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return
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total = sum(family_stats.get(kind, 0) for kind in TOTAL)
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if total == 0:
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return
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with Section(name, 3, f"specialization stats for {name} family"):
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rows = []
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for key in sorted(family_stats):
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if key.startswith("specialization.failure_kinds"):
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continue
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if key in ("specialization.hit", "specialization.miss"):
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label = key[len("specialization."):]
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elif key == "execution_count":
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label = "unquickened"
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elif key in ("specialization.success", "specialization.failure", "specializable"):
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continue
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elif key.startswith("pair"):
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continue
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else:
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label = key
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rows.append((f"{label:>12}", f"{family_stats[key]:>12}", f"{100*family_stats[key]/total:0.1f}%"))
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emit_table(("Kind", "Count", "Ratio"), rows)
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print_title("Specialization attempts", 4)
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total_attempts = 0
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for key in ("specialization.success", "specialization.failure"):
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total_attempts += family_stats.get(key, 0)
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rows = []
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for key in ("specialization.success", "specialization.failure"):
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label = key[len("specialization."):]
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label = label[0].upper() + label[1:]
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val = family_stats.get(key, 0)
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rows.append((label, val, f"{100*val/total_attempts:0.1f}%"))
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emit_table(("", "Count:", "Ratio:"), rows)
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total_failures = family_stats.get("specialization.failure", 0)
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failure_kinds = [ 0 ] * 30
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for key in family_stats:
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if not key.startswith("specialization.failure_kind"):
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continue
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_, index = key[:-1].split("[")
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index = int(index)
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failure_kinds[index] = family_stats[key]
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failures = [(value, index) for (index, value) in enumerate(failure_kinds)]
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failures.sort(reverse=True)
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rows = []
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for value, index in failures:
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if not value:
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continue
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rows.append((kind_to_text(index, defines, name), value, f"{100*value/total_failures:0.1f}%"))
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emit_table(("Failure kind", "Count:", "Ratio:"), rows)
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def gather_stats():
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stats = collections.Counter()
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for filename in os.listdir(DEFAULT_DIR):
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with open(os.path.join(DEFAULT_DIR, filename)) as fd:
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for line in fd:
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try:
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key, value = line.split(":")
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except ValueError:
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print (f"Unparsable line: '{line.strip()}' in {filename}", file=sys.stderr)
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continue
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key = key.strip()
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value = int(value)
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stats[key] += value
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return stats
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def extract_opcode_stats(stats):
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opcode_stats = [ {} for _ in range(256) ]
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for key, value in stats.items():
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if not key.startswith("opcode"):
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continue
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n, _, rest = key[7:].partition("]")
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opcode_stats[int(n)][rest.strip(".")] = value
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return opcode_stats
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def parse_kinds(spec_src, prefix="SPEC_FAIL"):
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defines = collections.defaultdict(list)
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start = "#define " + prefix + "_"
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for line in spec_src:
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line = line.strip()
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if not line.startswith(start):
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continue
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line = line[len(start):]
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name, val = line.split()
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defines[int(val.strip())].append(name.strip())
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return defines
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def pretty(defname):
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return defname.replace("_", " ").lower()
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def kind_to_text(kind, defines, opname):
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if kind < 7:
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return pretty(defines[kind][0])
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if opname.endswith("ATTR"):
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opname = "ATTR"
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if opname.endswith("SUBSCR"):
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opname = "SUBSCR"
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for name in defines[kind]:
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if name.startswith(opname):
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return pretty(name[len(opname)+1:])
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return "kind " + str(kind)
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def categorized_counts(opcode_stats):
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basic = 0
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specialized = 0
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not_specialized = 0
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specialized_instructions = {
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op for op in opcode._specialized_instructions
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if "__" not in op and "ADAPTIVE" not in op}
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adaptive_instructions = {
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op for op in opcode._specialized_instructions
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if "ADAPTIVE" in op}
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for i, opcode_stat in enumerate(opcode_stats):
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if "execution_count" not in opcode_stat:
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continue
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count = opcode_stat['execution_count']
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name = opname[i]
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if "specializable" in opcode_stat:
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not_specialized += count
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elif name in adaptive_instructions:
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not_specialized += count
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elif name in specialized_instructions:
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miss = opcode_stat.get("specialization.miss", 0)
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not_specialized += miss
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specialized += count - miss
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else:
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basic += count
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return basic, not_specialized, specialized
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def print_title(name, level=2):
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print("#"*level, name)
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print()
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class Section:
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def __init__(self, title, level=2, summary=None):
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self.title = title
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self.level = level
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if summary is None:
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self.summary = title.lower()
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else:
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self.summary = summary
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def __enter__(self):
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print_title(self.title, self.level)
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print("<details>")
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print("<summary>", self.summary, "</summary>")
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print()
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return self
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def __exit__(*args):
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print()
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print("</details>")
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print()
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def emit_table(header, rows):
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width = len(header)
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header_line = "|"
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under_line = "|"
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for item in header:
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under = "---"
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if item.endswith(":"):
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item = item[:-1]
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under += ":"
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header_line += item + " | "
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under_line += under + "|"
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print(header_line)
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print(under_line)
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for row in rows:
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if width is not None and len(row) != width:
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raise ValueError("Wrong number of elements in row '" + str(rows) + "'")
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print("|", " | ".join(str(i) for i in row), "|")
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print()
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def emit_execution_counts(opcode_stats, total):
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with Section("Execution counts", summary="execution counts for all instructions"):
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counts = []
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for i, opcode_stat in enumerate(opcode_stats):
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if "execution_count" in opcode_stat:
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count = opcode_stat['execution_count']
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miss = 0
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if "specializable" not in opcode_stat:
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miss = opcode_stat.get("specialization.miss")
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counts.append((count, opname[i], miss))
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counts.sort(reverse=True)
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cumulative = 0
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rows = []
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for (count, name, miss) in counts:
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cumulative += count
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if miss:
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miss = f"{100*miss/count:0.1f}%"
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else:
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miss = ""
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rows.append((name, count, f"{100*count/total:0.1f}%",
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f"{100*cumulative/total:0.1f}%", miss))
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emit_table(
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("Name", "Count:", "Self:", "Cumulative:", "Miss ratio:"),
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rows
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)
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def emit_specialization_stats(opcode_stats):
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spec_path = os.path.join(os.path.dirname(__file__), "../../Python/specialize.c")
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with open(spec_path) as spec_src:
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defines = parse_kinds(spec_src)
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with Section("Specialization stats", summary="specialization stats by family"):
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for i, opcode_stat in enumerate(opcode_stats):
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name = opname[i]
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print_specialization_stats(name, opcode_stat, defines)
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def emit_specialization_overview(opcode_stats, total):
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basic, not_specialized, specialized = categorized_counts(opcode_stats)
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with Section("Specialization effectiveness"):
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emit_table(("Instructions", "Count:", "Ratio:"), (
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("Basic", basic, f"{basic*100/total:0.1f}%"),
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("Not specialized", not_specialized, f"{not_specialized*100/total:0.1f}%"),
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("Specialized", specialized, f"{specialized*100/total:0.1f}%"),
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))
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def emit_call_stats(stats):
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stats_path = os.path.join(os.path.dirname(__file__), "../../Include/pystats.h")
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with open(stats_path) as stats_src:
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defines = parse_kinds(stats_src, prefix="EVAL_CALL")
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with Section("Call stats", summary="Inlined calls and frame stats"):
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total = 0
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for key, value in stats.items():
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if "Calls to" in key:
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total += value
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rows = []
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for key, value in stats.items():
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if "Calls to" in key:
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rows.append((key, value, f"{100*value/total:0.1f}%"))
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elif key.startswith("Calls "):
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name, index = key[:-1].split("[")
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index = int(index)
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label = name + " (" + pretty(defines[index][0]) + ")"
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rows.append((label, value, f"{100*value/total:0.1f}%"))
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for key, value in stats.items():
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if key.startswith("Frame"):
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rows.append((key, value, f"{100*value/total:0.1f}%"))
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emit_table(("", "Count:", "Ratio:"), rows)
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def emit_object_stats(stats):
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with Section("Object stats", summary="allocations, frees and dict materializatons"):
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total_materializations = stats.get("Object new values")
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total_allocations = stats.get("Object allocations") + stats.get("Object allocations from freelist")
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total_increfs = stats.get("Object interpreter increfs") + stats.get("Object increfs")
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total_decrefs = stats.get("Object interpreter decrefs") + stats.get("Object decrefs")
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rows = []
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for key, value in stats.items():
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if key.startswith("Object"):
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if "materialize" in key:
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ratio = f"{100*value/total_materializations:0.1f}%"
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elif "allocations" in key:
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ratio = f"{100*value/total_allocations:0.1f}%"
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elif "increfs" in key:
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ratio = f"{100*value/total_increfs:0.1f}%"
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elif "decrefs" in key:
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ratio = f"{100*value/total_decrefs:0.1f}%"
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else:
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ratio = ""
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label = key[6:].strip()
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label = label[0].upper() + label[1:]
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rows.append((label, value, ratio))
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emit_table(("", "Count:", "Ratio:"), rows)
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def get_total(opcode_stats):
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total = 0
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for opcode_stat in opcode_stats:
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if "execution_count" in opcode_stat:
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total += opcode_stat['execution_count']
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return total
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def emit_pair_counts(opcode_stats, total):
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pair_counts = []
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for i, opcode_stat in enumerate(opcode_stats):
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if i == 0:
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continue
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for key, value in opcode_stat.items():
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if key.startswith("pair_count"):
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x, _, _ = key[11:].partition("]")
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if value:
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pair_counts.append((value, (i, int(x))))
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with Section("Pair counts", summary="Pair counts for top 100 pairs"):
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pair_counts.sort(reverse=True)
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cumulative = 0
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rows = []
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for (count, pair) in itertools.islice(pair_counts, 100):
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i, j = pair
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cumulative += count
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rows.append((opname[i] + " " + opname[j], count, f"{100*count/total:0.1f}%",
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f"{100*cumulative/total:0.1f}%"))
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emit_table(("Pair", "Count:", "Self:", "Cumulative:"),
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rows
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)
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with Section("Predecessor/Successor Pairs", summary="Top 5 predecessors and successors of each opcode"):
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predecessors = collections.defaultdict(collections.Counter)
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successors = collections.defaultdict(collections.Counter)
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total_predecessors = collections.Counter()
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total_successors = collections.Counter()
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for count, (first, second) in pair_counts:
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if count:
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predecessors[second][first] = count
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successors[first][second] = count
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total_predecessors[second] += count
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total_successors[first] += count
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for name, i in opmap.items():
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total1 = total_predecessors[i]
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total2 = total_successors[i]
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if total1 == 0 and total2 == 0:
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continue
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pred_rows = succ_rows = ()
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if total1:
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pred_rows = [(opname[pred], count, f"{count/total1:.1%}")
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for (pred, count) in predecessors[i].most_common(5)]
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if total2:
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succ_rows = [(opname[succ], count, f"{count/total2:.1%}")
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for (succ, count) in successors[i].most_common(5)]
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with Section(name, 3, f"Successors and predecessors for {name}"):
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emit_table(("Predecessors", "Count:", "Percentage:"),
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pred_rows
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)
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emit_table(("Successors", "Count:", "Percentage:"),
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succ_rows
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)
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def main():
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stats = gather_stats()
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opcode_stats = extract_opcode_stats(stats)
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total = get_total(opcode_stats)
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emit_execution_counts(opcode_stats, total)
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emit_pair_counts(opcode_stats, total)
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emit_specialization_stats(opcode_stats)
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emit_specialization_overview(opcode_stats, total)
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emit_call_stats(stats)
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emit_object_stats(stats)
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print("---")
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print("Stats gathered on:", date.today())
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if __name__ == "__main__":
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main()
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