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#!/usr/bin/env python3
# ===--- perf_test_driver.py ---------------------------------------------===//
#
# This source file is part of the Swift.org open source project
#
# Copyright (c) 2014 - 2017 Apple Inc. and the Swift project authors
# Licensed under Apache License v2.0 with Runtime Library Exception
#
# See https://swift.org/LICENSE.txt for license information
# See https://swift.org/CONTRIBUTORS.txt for the list of Swift project authors
#
# ===---------------------------------------------------------------------===//
import functools
import glob
import multiprocessing
import os
import platform
import re
import subprocess
BENCHMARK_OUTPUT_RE = re.compile(r"\d+,([^,]+)")
class Result(object):
def __init__(self, name, status, output, xfail_list):
self.name = name
self.status = status
self.output = output
self.is_xfailed = any((re.match(x, self.name) is not None for x in xfail_list))
def is_failure(self):
return self.get_result() in ["FAIL", "XPASS"]
def get_result(self):
if self.is_xfailed:
if self.status:
return "XFAIL"
return "XPASS"
if self.status:
return "FAIL"
return "PASS"
def get_name(self):
return self.name
def merge_in_extra_data(self, d):
"""Rather than modifying the extra data dict, return it as a no-op"""
return d
def print_data(self, max_test_len):
fmt = "{:<%d}{:}" % (max_test_len + 5)
print(fmt.format(self.get_name(), self.get_result()))
def run_with_timeout(func, args):
# We timeout after 10 minutes.
timeout_seconds = 10 * 60
# We just use this to create a timeout since we use an older python. Once
# we update to use python >= 3.3, use the timeout API on communicate
# instead.
import multiprocessing.dummy
fakeThreadPool = multiprocessing.dummy.Pool(1)
try:
result = fakeThreadPool.apply_async(func, args=args)
return result.get(timeout_seconds)
except multiprocessing.TimeoutError:
fakeThreadPool.terminate()
raise RuntimeError(
"Child process aborted due to timeout. "
"Timeout: %s seconds" % timeout_seconds
)
def _unwrap_self(args):
return type(args[0]).process_input(*args)
def get_benchmark_executable(binary_dir, opt_level):
suffix = opt_level + "-" + platform.machine() + "*"
pattern = os.path.join(binary_dir, "Benchmark_" + suffix)
executables = glob.glob(pattern)
if len(executables) == 0:
raise ValueError(
"No benchmark executable for file name pattern " +
pattern + " found")
if len(executables) > 1:
raise ValueError(
"Multiple benchmark executables for file name pattern " +
pattern + " found\n" +
str(executables))
return executables[0]
BenchmarkDriver_OptLevels = ["Onone", "O", "Osize"]
class BenchmarkDriver(object):
def __init__(
self,
binary_dir,
xfail_list,
enable_parallel=False,
opt_levels=BenchmarkDriver_OptLevels,
):
self.targets = [
(get_benchmark_executable(binary_dir, o), o) for o in opt_levels
]
self.xfail_list = xfail_list
self.enable_parallel = enable_parallel
self.data = None
def print_data_header(self, max_test_len):
fmt = "{:<%d}{:}" % (max_test_len + 5)
print(fmt.format("Name", "Result"))
def prepare_input(self, name, opt_level):
raise RuntimeError("Abstract method")
def process_input(self, data):
raise RuntimeError("Abstract method")
def run_for_opt_level(self, binary, opt_level, test_filter):
print("testing driver at path: %s" % binary)
names = []
output = subprocess.check_output([binary, "--list"], universal_newlines=True)
for line in output.split("\n")[1:]:
m = BENCHMARK_OUTPUT_RE.match(line)
if m is None:
continue
names.append(m.group(1))
if test_filter:
regex = re.compile(test_filter)
names = [n for n in names if regex.match(n)]
def prepare_input_wrapper(name):
x = {"opt": opt_level, "path": binary, "test_name": name}
x.update(self.prepare_input(name))
return x
prepared_input = [prepare_input_wrapper(n) for n in names]
results = None
if self.enable_parallel:
p = multiprocessing.Pool()
z = zip([self] * len(prepared_input), prepared_input)
results = p.map_async(_unwrap_self, z).get(999999)
else:
results = map(self.process_input, prepared_input)
def reduce_results(acc, r):
acc["result"].append(r)
acc["has_failure"] = acc["has_failure"] or r.is_failure()
acc["max_test_len"] = max(acc["max_test_len"], len(r.get_name()))
acc["extra_data"] = r.merge_in_extra_data(acc["extra_data"])
return acc
return functools.reduce(
reduce_results,
results,
{"result": [], "has_failure": False, "max_test_len": 0, "extra_data": {}},
)
def print_data(self, data, max_test_len):
print("Results:")
self.print_data_header(max_test_len)
for d in data:
for r in d["result"]:
r.print_data(max_test_len)
def run(self, test_filter=None):
self.data = [
self.run_for_opt_level(binary, opt_level, test_filter)
for binary, opt_level in self.targets
]
max_test_len = functools.reduce(max, [d["max_test_len"] for d in self.data])
has_failure = functools.reduce(max, [d["has_failure"] for d in self.data])
self.print_data(self.data, max_test_len)
return not has_failure
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