|
1
|
|
"""
|
|
2
|
|
@file
|
|
3
|
|
@brief Measures speed.
|
|
4
|
|
"""
|
|
5
|
1
|
import sys
|
|
6
|
1
|
from timeit import Timer
|
|
7
|
|
|
|
8
|
|
|
|
9
|
1
|
def measure_time(stmt, context, repeat=10, number=50, div_by_number=False):
|
|
10
|
|
"""
|
|
11
|
|
Measures a statement and returns the results as a dictionary.
|
|
12
|
|
|
|
13
|
|
@param stmt string
|
|
14
|
|
@param context variable to know in a dictionary
|
|
15
|
|
@param repeat average over *repeat* experiment
|
|
16
|
|
@param number number of executions in one row
|
|
17
|
|
@param div_by_number divide by the number of executions
|
|
18
|
|
@return dictionary
|
|
19
|
|
|
|
20
|
|
.. runpython::
|
|
21
|
|
:showcode:
|
|
22
|
|
|
|
23
|
|
from cpyquickhelper.numbers import measure_time
|
|
24
|
|
from math import cos
|
|
25
|
|
|
|
26
|
|
res = measure_time("cos(x)", context=dict(cos=cos, x=5.))
|
|
27
|
|
print(res)
|
|
28
|
|
|
|
29
|
|
See `Timer.repeat <https://docs.python.org/3/library/timeit.html?timeit.Timer.repeat>`_
|
|
30
|
|
for a better understanding of parameter *repeat* and *number*.
|
|
31
|
|
The function returns a duration corresponding to
|
|
32
|
|
*number* times the execution of the main statement.
|
|
33
|
|
"""
|
|
34
|
1
|
import numpy # pylint: disable=C0415
|
|
35
|
1
|
tim = Timer(stmt, globals=context)
|
|
36
|
1
|
res = numpy.array(tim.repeat(repeat=repeat, number=number))
|
|
37
|
1
|
if div_by_number:
|
|
38
|
1
|
res /= number
|
|
39
|
1
|
mean = numpy.mean(res)
|
|
40
|
1
|
dev = numpy.mean(res ** 2)
|
|
41
|
1
|
dev = (dev - mean**2) ** 0.5
|
|
42
|
1
|
mes = dict(average=mean, deviation=dev, min_exec=numpy.min(res),
|
|
43
|
|
max_exec=numpy.max(res), repeat=repeat, number=number)
|
|
44
|
1
|
if 'values' in context:
|
|
45
|
1
|
if hasattr(context['values'], 'shape'):
|
|
46
|
1
|
mes['size'] = context['values'].shape[0]
|
|
47
|
|
else:
|
|
48
|
|
mes['size'] = len(context['values']) # pragma: no cover
|
|
49
|
|
else:
|
|
50
|
1
|
mes['context_size'] = sys.getsizeof(context)
|
|
51
|
1
|
return mes
|
|
52
|
|
|
|
53
|
|
|
|
54
|
1
|
def _fcts():
|
|
55
|
|
"""
|
|
56
|
|
Returns functions to measure.
|
|
57
|
|
"""
|
|
58
|
1
|
import numpy # pylint: disable=C0415
|
|
59
|
1
|
from .cbenchmark_dot import vector_dot_product # pylint: disable=E0611,C0415
|
|
60
|
1
|
from .cbenchmark_dot import vector_dot_product16 # pylint: disable=E0611,C0415
|
|
61
|
1
|
from .cbenchmark_dot import vector_dot_product16_nofcall # pylint: disable=E0611,C0415
|
|
62
|
1
|
from .cbenchmark_dot import vector_dot_product16_sse # pylint: disable=E0611,C0415
|
|
63
|
|
|
|
64
|
1
|
def simple_dot(values):
|
|
65
|
1
|
return numpy.dot(values, values)
|
|
66
|
|
|
|
67
|
1
|
def c11_dot(vect):
|
|
68
|
1
|
return vector_dot_product(vect, vect)
|
|
69
|
|
|
|
70
|
1
|
def c11_dot16(vect):
|
|
71
|
1
|
return vector_dot_product16(vect, vect)
|
|
72
|
|
|
|
73
|
1
|
def c11_dot16_nofcall(vect):
|
|
74
|
1
|
return vector_dot_product16_nofcall(vect, vect)
|
|
75
|
|
|
|
76
|
1
|
def c11_dot16_sse(vect):
|
|
77
|
1
|
return vector_dot_product16_sse(vect, vect)
|
|
78
|
|
|
|
79
|
1
|
return [simple_dot, c11_dot, c11_dot16, c11_dot16_nofcall, c11_dot16_sse]
|
|
80
|
|
|
|
81
|
|
|
|
82
|
1
|
def check_speed(dims=[100000], repeat=10, number=50, fLOG=print): # pylint: disable=W0102
|
|
83
|
|
"""
|
|
84
|
|
Prints out some information about speed computation
|
|
85
|
|
of this laptop. See :ref:`cbenchmarkbranchingrst` to compare.
|
|
86
|
|
|
|
87
|
|
@param dims sets of dimensions to try
|
|
88
|
|
@param repeat average over *repeat* experiment
|
|
89
|
|
@param number number of execution in one row
|
|
90
|
|
@param fLOG logging function
|
|
91
|
|
@return iterator on results
|
|
92
|
|
|
|
93
|
|
:epkg:`numpy` is multithreaded. For an accurate comparison,
|
|
94
|
|
this needs to be disabled. This can be done by setting environment variable
|
|
95
|
|
``MKL_NUM_THREADS=1`` or by running:
|
|
96
|
|
|
|
97
|
|
::
|
|
98
|
|
|
|
99
|
|
import mkl
|
|
100
|
|
mkl.set_num_threads(1)
|
|
101
|
|
|
|
102
|
|
.. index:: MKL_NUM_THREADS
|
|
103
|
|
|
|
104
|
|
One example of use:
|
|
105
|
|
|
|
106
|
|
.. runpython::
|
|
107
|
|
:showcode:
|
|
108
|
|
|
|
109
|
|
from cpyquickhelper.numbers import check_speed
|
|
110
|
|
res = list(check_speed(dims=[100, 1000]))
|
|
111
|
|
import pprint
|
|
112
|
|
pprint.pprint(res)
|
|
113
|
|
"""
|
|
114
|
1
|
import numpy # pylint: disable=C0415
|
|
115
|
1
|
fcts = _fcts()
|
|
116
|
1
|
mx = max(dims)
|
|
117
|
1
|
vect = numpy.ones((mx,))
|
|
118
|
1
|
for i in range(0, vect.shape[0]):
|
|
119
|
1
|
vect[i] = i
|
|
120
|
1
|
for i in dims:
|
|
121
|
1
|
values = vect[:i].copy()
|
|
122
|
1
|
for fct in fcts:
|
|
123
|
1
|
ct = {fct.__name__: fct}
|
|
124
|
1
|
ct['values'] = values
|
|
125
|
1
|
t = measure_time("{0}(values)".format(fct.__name__),
|
|
126
|
|
repeat=repeat, number=number, context=ct)
|
|
127
|
1
|
t['name'] = fct.__name__
|
|
128
|
1
|
if fLOG:
|
|
129
|
1
|
fLOG(t)
|
|
130
|
1
|
yield t
|
sdpython