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.Calculatrice de Postfix en Cython
Salut. J'essaye de développer une calculatrice de postfix dans Cython, traduite d'une version de Numpy fonctionnante. C'est ma première tentative. La fonction calculatrice obtient l'expression postfix dans une liste et la matrice des échantillons. Ensuite, il doit retourner le tableau calculé.
exemple d'entrée:
postfix = ['X0', 'X1', 'add']
samples = [[0, 1],
[2, 3],
[4, 5]]
result = [1, 5, 9]
example_cython.pyx
#cython: boundscheck=False, wraparound=False, nonecheck=False
import numpy
from libc.math cimport sin as c_sin
cdef inline calculate(list lst, double [:,:] samples):
cdef int N = samples.shape[0]
cdef int i, j
cdef list stack = []
cdef double[:] Y = numpy.zeros(N)
for p in lst:
if p == 'add':
b = stack.pop()
a = stack.pop()
for i in range(N):
Y[i] = a[i] + b[i]
stack.append(Y)
elif p == 'sub':
b = stack.pop()
a = stack.pop()
for i in range(N):
Y[i] = a[i] - b[i]
stack.append(Y)
elif p == 'mul':
b = stack.pop()
a = stack.pop()
for i in range(N):
Y[i] = a[i] * b[i]
stack.append(Y)
elif p == 'div':
b = stack.pop()
a = stack.pop()
for i in range(N):
if abs(b[i]) < 1e-4: b[i]=1e-4
Y[i] = a[i]/b[i]
stack.append(Y)
elif p == 'sin':
a = stack.pop()
for i in range(N):
Y[i] = c_sin(a[i])
stack.append(Y)
else:
if p[0] == 'X':
j = int(p[1:])
stack.append (samples[:, j])
else:
stack.append(float(p))
return stack.pop()
# Generate and evaluate expressions
cpdef test3(double [:,:] samples, object _opchars, object _inputs, int nExpr):
for i in range(nExpr):
size = 2
postfix = list(numpy.concatenate((numpy.random.choice(_inputs, 5*size),
numpy.random.choice(_inputs + _opchars, size),
numpy.random.choice(_opchars, size)), 0))
#print postfix
res = calculate(postfix, samples)
main.py
import random
import time
import numpy
from example_cython import test3
# Random dataset
n = 1030
nDim=10
samples = numpy.random.uniform(size=(n, nDim))
_inputs = ['X'+str(i) for i in range(nDim)]
_ops_1 = ['sin']
_ops_2 = ['add', 'sub', 'mul', 'div']
_opchars = _ops_1 + _ops_2
nExpr = 1000
nTrials = 3
tic = time.time()
for i in range(nTrials): test3(samples, _opchars, _inputs, nExpr)
print ("TEST 1: It took an average of {} seconds to evaluate {} expressions on a dataset of {} rows and {} columns.".format(str((time.time() - tic)/nTrials), str(nExpr), str(n), str(nDim)))
setup.py
from distutils.core import setup
from distutils.extension import Extension
from Cython.Distutils import build_ext
ext_modules=[ Extension("example_cython",
["example_cython.pyx"],
libraries=["m"],
extra_compile_args = ["-Ofast", "-ffast-math"])]
setup(
name = "example_cython",
cmdclass = {"build_ext": build_ext},
ext_modules = ext_modules)
Configuration:
Python 3.6.2 |Anaconda, Inc.| (default, Sep 21 2017, 18:29:43)
[GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)] on darwin
>>> numpy.__version__
'1.13.1'
>>> cython.__version__
'0.26.1'
Compilation et exécutez:
running build_ext
skipping 'example_cython.c' Cython extension (up-to-date)
building 'example_cython' extension
/usr/bin/clang -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -fwrapv -O2 -Wall -Wstrict-prototypes -march=core2 -mtune=haswell -mssse3 -ftree-vectorize -fPIC -fPIE -fstack-protector-strong -O2 -pipe -march=core2 -mtune=haswell -mssse3 -ftree-vectorize -fPIC -fPIE -fstack-protector-strong -O2 -pipe -I/Users/vmelo/anaconda3/include/python3.6m -c example_cython.c -o build/temp.macosx-10.9-x86_64-3.6/example_cython.o -Ofast -ffast-math
example_cython.c:2506:15: warning: code will never be executed [-Wunreachable-code]
if (0 && (__pyx_tmp_idx < 0 || __pyx_tmp_idx >= __pyx_tmp_shape)) {
^~~~~~~~~~~~~
example_cython.c:2506:9: note: silence by adding parentheses to mark code as explicitly dead
if (0 && (__pyx_tmp_idx < 0 || __pyx_tmp_idx >= __pyx_tmp_shape)) {
^
/* DISABLES CODE */ ()
example_cython.c:2505:9: warning: code will never be executed [-Wunreachable-code]
__pyx_tmp_idx += __pyx_tmp_shape;
^~~~~~~~~~~~~
example_cython.c:2504:9: note: silence by adding parentheses to mark code as explicitly dead
if (0 && (__pyx_tmp_idx < 0))
^
/* DISABLES CODE */ ()
2 warnings generated.
/usr/bin/clang -bundle -undefined dynamic_lookup -Wl,-pie -Wl,-headerpad_max_install_names -Wl,-rpath,/Users/vmelo/anaconda3/lib -L/Users/vmelo/anaconda3/lib -Wl,-pie -Wl,-headerpad_max_install_names -Wl,-rpath,/Users/vmelo/anaconda3/lib -L/Users/vmelo/anaconda3/lib -arch x86_64 build/temp.macosx-10.9-x86_64-3.6/example_cython.o -L/Users/vmelo/anaconda3/lib -lm -o /Users/vmelo/Dropbox/SRC/python/random_equation/cython_v2/example_cython.cpython-36m-darwin.so
ld: warning: -pie being ignored. It is only used when linking a main executable
TEST 1: It took an average of 1.2609198093414307 seconds to evaluate 1000 expressions on a dataset of 1030 rows and 10 columns.
Il faut environ secondes pour exécuter 1,25 sur mon i5 1.4Ghz. Cependant, un code C similaire prend 0,13 secondes.
Le code ci-dessus évalue 1000 expressions, mais je vis à 1 000 000. Ainsi, je dois accélérer ce code Cython par une grande marge.
Comme je l'ai écrit au début, la version Numpy fonctionne correctement. Peut-être, dans cette version de Cython, je ne devrais pas utiliser une liste comme une pile? Je ne vérifie toujours pas si les résultats générés par ce code Cython sont corrects, car je suis concentré sur l'amélioration de sa vitesse.
Des suggestions?
Merci.