pyodide/benchmark/benchmark.py

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import json
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from pathlib import Path
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import re
import subprocess
import sys
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sys.path.insert(
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0, str((Path(__file__).resolve().parents[1] / 'test')))
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import conftest
SKIP = set(['fft', 'hyantes'])
def run_native(hostpython, code):
output = subprocess.check_output(
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[hostpython.resolve(), '-c', code],
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cwd=Path(__file__).resolve().parent,
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env={
'PYTHONPATH':
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str(Path(__file__).resolve().parents[1] / 'src')
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}
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)
return float(output.strip().split()[-1])
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def run_wasm(code, cls):
s = cls()
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try:
s.load_package('numpy')
s.run(code)
try:
runtime = float(s.logs[-1])
except ValueError:
print('\n'.join(s.logs))
raise
finally:
s.driver.quit()
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return runtime
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def run_all(hostpython, code):
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a = run_native(hostpython, code)
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print("native:", a)
b = run_wasm(code, conftest.FirefoxWrapper)
print("firefox:", b)
c = run_wasm(code, conftest.ChromeWrapper)
print("chrome:", c)
result = {
'native': a,
'firefox': b,
'chrome': c
}
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return result
def get_pystone_benchmarks():
yield 'pystone', (
"import pystone\n"
"pystone.main(pystone.LOOPS)\n"
)
def parse_numpy_benchmark(filename):
lines = []
with open(filename) as fp:
for line in fp:
m = re.match('^#(setup|run): (.*)$', line)
if m:
line = '{} = {!r}\n'.format(m.group(1), m.group(2))
lines.append(line)
return ''.join(lines)
def get_numpy_benchmarks():
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root = Path('../numpy-benchmarks/benchmarks')
for filename in root.iterdir():
name = filename.name
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if name in SKIP:
continue
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content = parse_numpy_benchmark(filename)
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content += (
"import numpy as np\n"
"_ = np.empty(())\n"
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"setup = setup + '\\nfrom __main__ import {}'\n"
"from timeit import Timer\n"
"t = Timer(run, setup)\n"
"r = t.repeat(11, 40)\n"
"print(np.mean(r))\n".format(name))
yield name, content
def get_benchmarks():
yield from get_pystone_benchmarks()
yield from get_numpy_benchmarks()
def main(hostpython):
results = {}
for k, v in get_benchmarks():
print(k)
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results[k] = run_all(hostpython, v)
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return results
if __name__ == '__main__':
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results = main(Path(sys.argv[-2]).resolve())
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with open(sys.argv[-1], 'w') as fp:
json.dump(results, fp)