[英]Performance drop using cython
I wanted to make some code faster using cython's capability to use efficient indexing: http://docs.cython.org/src/tutorial/numpy.html 我希望使用cython使用高效索引的能力来更快地编写代码: http ://docs.cython.org/src/tutorial/numpy.html
Basically the code represents the dependency of buttons on a game board of the game http://www.hacker.org/cross/index.php 基本上,代码表示游戏的游戏板上按钮的依赖性http://www.hacker.org/cross/index.php
# file test_so_cy.pyx
import time
import numpy as np
cimport numpy as np
DTYPE = np.uint8
ctypedef np.uint8_t DTYPE_t
def time_fmt(td):
return "{:.2f} s".format(td)
def derive_equations(np.ndarray[DTYPE_t, ndim=2] field not None):
cdef unsigned int n, m, i, j, x, y
t1 = time.time()
n, m = len(field), len(field[0])
# generate equations for dimensions n and m
eqs = []
block = 2 # as soon as a 2 is hit there isnt any influence
for i in xrange(n):
for j in xrange(m):
eq = 0L
if field[i][j] == block:
eqs.append([i*m+j ,field[i][j], eq])
continue
# rows upwards
for x in xrange(i-1, -1, -1):
if field[x][j] == block: break
eq ^= 1L << (x*m+j)
# rows downwards
for x in xrange(i, n):
if field[x][j] == block: break
eq ^= 1L << (x*m+j)
# cols left
for y in xrange(j-1, -1, -1):
if field[i][y] == block: break
eq ^= 1L << (i*m+y)
# cols right
# j+1 to avoid resetting the influence of itself
for y in xrange(j+1, m):
if field[i][y] == block: break
eq ^= 1L << (i*m+y)
eqs.append([i*m+j, field[i][j], eq])
t2 = time.time()
print 'preprocess time:', time_fmt(t2 - t1)
return n, m, eqs
def main():
field = np.array(
[[0,1,0,0,0,0,0,0,0,0,0,1,1,1,0,2,1,0,0,2,1,0,1,1,0,0,0,0,0],
[0,1,0,0,1,1,0,1,0,0,0,1,1,0,0,1,0,1,0,0,1,0,1,1,1,0,1,1,1],
[1,1,0,1,0,0,0,0,0,0,0,1,1,0,1,0,1,0,0,1,0,1,1,0,0,1,0,0,2],
[0,0,0,0,1,0,1,1,0,1,1,1,0,1,0,1,1,0,0,0,1,1,0,0,2,1,1,0,1],
[0,1,0,1,1,1,1,1,2,1,1,0,1,0,0,0,0,0,0,1,0,0,1,0,2,0,1,0,1],
[0,1,1,0,0,1,1,0,1,0,0,1,1,1,0,1,1,1,0,0,1,1,1,0,1,0,1,1,1],
[0,0,0,1,0,1,1,0,1,0,0,1,1,1,0,1,0,0,0,0,0,0,0,1,0,1,0,1,1],
[1,0,1,0,1,1,0,0,0,0,0,1,0,0,2,0,1,1,0,0,0,0,1,0,0,2,1,0,0],
[1,0,1,0,1,0,1,0,1,1,1,0,1,0,1,1,0,1,1,0,1,0,1,0,1,0,1,1,1],
[0,0,1,0,0,1,1,0,1,0,0,1,0,0,1,0,0,0,1,0,0,0,0,1,0,1,1,1,2],
[1,0,1,1,0,0,1,0,1,1,1,0,1,2,1,1,1,2,1,0,1,1,1,0,0,0,0,0,0],
[0,0,1,0,1,0,0,1,0,1,1,1,1,1,1,0,0,1,1,0,0,1,0,0,0,1,0,0,1],
[1,1,0,0,0,1,0,0,1,0,0,1,0,1,1,0,0,0,0,1,1,0,0,1,0,0,0,0,0],
[1,1,1,0,1,1,1,1,0,0,1,0,1,1,0,0,0,0,1,1,1,1,1,0,1,0,1,0,1],
[1,0,0,0,1,1,0,0,2,0,1,1,2,0,0,1,0,1,0,1,0,2,1,1,1,1,0,0,2],
[1,0,1,1,1,1,1,0,0,1,1,0,1,1,0,0,1,0,0,0,2,1,0,1,0,1,0,1,1],
[0,0,1,1,1,0,0,0,0,0,2,1,0,1,0,1,0,1,1,1,1,0,0,1,1,1,1,0,1],
[0,1,0,1,2,0,0,0,0,0,1,1,0,1,0,1,0,1,0,1,0,0,1,0,1,0,1,1,0],
[0,1,0,0,2,0,0,0,1,0,1,0,0,1,0,1,1,0,0,1,0,1,1,1,0,1,1,1,1],
[1,0,0,1,0,0,1,0,1,0,0,2,0,1,1,1,1,1,0,0,1,0,1,0,1,1,0,1,1],
[0,0,1,0,1,1,0,0,1,0,0,0,1,1,1,0,0,1,0,0,1,0,1,2,0,1,1,0,2],
[0,1,1,0,1,0,1,1,0,0,1,0,0,0,1,1,0,1,0,1,1,1,1,1,2,0,1,2,0],
[0,0,0,0,1,0,1,0,0,0,0,1,0,0,1,0,0,1,1,1,2,0,0,1,0,0,1,1,0],
[0,0,1,1,0,1,1,0,0,1,1,1,1,0,0,1,0,0,1,1,1,0,0,0,1,1,1,0,1],
[0,2,0,1,1,1,1,0,1,0,0,0,0,0,1,1,1,0,1,1,1,1,0,1,0,0,0,1,1],
[0,2,1,1,1,1,1,1,1,1,0,1,1,0,0,0,0,0,1,0,1,1,1,1,1,1,0,1,1],
[0,1,1,1,0,1,0,0,0,1,0,2,0,1,1,1,1,1,0,1,0,1,0,0,1,1,0,1,0],
[0,1,1,1,1,1,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0,0,1,1,0,0,0,0,0],
[1,0,0,0,0,1,0,1,0,1,0,1,0,0,1,0,0,1,0,0,1,0,1,0,0,1,2,1,1]], dtype=DTYPE)
derive_equations(field)
if __name__ == '__main__':
main()
# file setup_so.py
from distutils.core import setup
from Cython.Build import cythonize
import numpy
setup(
name = "test_so",
ext_modules = cythonize('test_so_cy.pyx'),
include_dirs=[numpy.get_include()]
)
# usage: python setup_so.py build_ext --inplace
# import test_so_cy
# test_so_cy.main()
The problem is that the cython code runs ~3 times slower than the pure python version. 问题是cython代码运行速度比纯python版慢~3倍。 (I am using the time module to measure execution time because for bigger matrices its ok).
(我使用时间模块来测量执行时间,因为对于更大的矩阵,它可以)。
cython -a tells me that the cython -a告诉我那个
if field[x][j] == block: break
lines are still using much python. 线仍然使用很多python。 So it seems that fast indexing still cannot be used.
所以似乎仍然无法使用快速索引。 Any ideas what i am doing wrong?
我有什么想法吗?
Original speed: 0.14s 原始速度:0.14秒
14X speedup (0.01s): The field[i][j]
will evaluate the field[i]
first and then try to evaluate the resulting python object. 14X加速(0.01s):
field[i][j]
将首先评估field[i]
,然后尝试评估生成的python对象。 use the field[i,j]
notation for a HUGE boost in speed 使用
field[i,j]
表示法来提高速度
5X speedup (0.0018s): type the eq variable cdef long eq
5X加速(0.0018s):输入eq变量
cdef long eq
12X s5eedup (0.00012s) : replace the list with a stack made of an np array: 12X s5eedup(0.00012s):用由np数组组成的堆栈替换列表:
cdef np.ndarray[long, ndim=2] eqs=np.zeros((n*m,3),np.long)
cdef int curr_eqn=0
#append to list code
if field[i,j] == block:
eqs[curr_eqn,0]=i*m+j
eqs[curr_eqn,1]=field[i,j]
eqs[curr_eqn,2]=eq
curr_eqn+=1
continue
total speedup: 1100x 总加速:1100x
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