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Project description
perfbench
About
Feature
Compatibility
perfbench works with Python 3.3 or higher.
Dependencies
ipython(6.0.0 or higher.)
tqdm(4.6.1 or higher.)
plotly(2.7.0 or lower)
Installation
Usage
case1:
import numpy as np
from perfbench.process import *
setups = [
{'func': lambda n: np.random.uniform(low=-1., high=1., size=n).astype(np.float64), 'title': 'float64'}
]
kernels = [
{'func': lambda x: np.around(x), 'label': 'around'},
{'func': lambda x: np.rint(x), 'label': 'rint'}
]
ntimes = [2 ** n for n in range(15)]
bm = Benchmark(
setups=setups,
kernels=kernels,
ntimes=ntimes,
xlabel='samples',
title='test',
logx=True
)
bm.run()
bm.show()
case2:
import numpy as np
from perfbench.process import *
setups = [
{'func': lambda n: np.random.uniform(low=-1., high=1., size=n).astype(np.float16), 'title': 'float16'},
{'func': lambda n: np.random.uniform(low=-1., high=1., size=n).astype(np.float32), 'title': 'float32'},
{'func': lambda n: np.random.uniform(low=-1., high=1., size=n).astype(np.float64), 'title': 'float64'}
]
kernels = [
{'func': lambda x: np.around(x), 'label': 'around'},
{'func': lambda x: np.rint(x), 'label': 'rint'}
]
ntimes = [2 ** n for n in range(5)]
bm = Benchmark(
setups=setups,
kernels=kernels,
ntimes=ntimes,
xlabel='samples',
title='test',
logx=True
)
bm.run()
bm.show()
License
This software is released under the MIT License, see LICENSE.
Project details
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