是的。你知道吗
你好。你知道吗
我正在尝试用Cython开发一个后缀计算器,它是从一个正常工作的Numpy版本翻译过来的。这是我第一次尝试。计算器函数获取列表中的后缀表达式和示例矩阵。然后,它必须返回计算出的数组。你知道吗
输入示例:
postfix = ['X0', 'X1', 'add']
samples = [[0, 1],
[2, 3],
[4, 5]]
result = [1, 5, 9]
示例_cython.pyx公司你知道吗
#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)
你知道吗主.py你知道吗
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)))
你知道吗设置.py你知道吗
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)
配置:
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'
编译和运行:
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.
在我的i5 1.4Ghz上运行大约需要1,25秒。但是,类似的C代码需要0,13秒。你知道吗
上面的代码计算1000个表达式,但我的目标是1000000个。因此,我必须大大加快这个Cython代码的速度。你知道吗
正如我在开头所写的,Numpy版本工作正常。 也许,在这个Cython版本中,我不应该使用列表作为堆栈?我仍然没有检查这个Cython代码生成的结果是否正确,因为我专注于提高它的速度。你知道吗
有什么建议吗?你知道吗
谢谢。你知道吗
目前唯一优化的操作是索引
samples[:, j]
。(几乎)其他一切都是非类型化的,因此Cython无法对其进行太多优化。你知道吗我真的不想完全重写你的(相当大的)程序,但这里有一些关于如何改进它的简单想法。你知道吗
修复一个基本的逻辑错误-您需要在循环中使用
Y = numpy.zeros(N)
行。stack.append(Y)
不会生成Y
的副本,因此每次修改Y
时,也会修改堆栈上的所有其他版本。为
a
和b
设置类型:这将大大加快索引的速度
但是,它会导致像
a = stack.pop()
这样的行稍微慢一点,因为它需要检查结果是否可以用作memoryview。您还需要更改线路要确保在堆栈上放置具有memoryview的可用对象,请执行以下操作:
将堆栈更改为二维内存视图。我建议您过度分配它,只需保持
number_on_stack
的计数,然后根据需要重新分配堆栈。然后可以更改:收件人:
以及
至
其他变化也遵循类似的模式。这个选项是大多数工作,但可能得到最好的结果。
使用
cython -a
生成彩色HTML可以让您合理地了解哪些位得到了很好的优化(黄色代码通常更糟)相关问题 更多 >
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