def aot_compile(file_name):
"""
:param file_name:
:return:
"""
cc = CC(config['module_name'])
func = []
signatures = []
if os.path.exists(config['example']):
f = os.open(config['example'], os.O_RDONLY)
stdin_bk = os.dup(0)
os.dup2(f, 0)
try:
module = runpy.run_module(file_name, run_name="__main__")
for k in module:
e = module[k]
if type(e) == numba.targets.registry.CPUDispatcher \
and e.nopython_signatures:
cc.export(k, e.nopython_signatures[0])(e)
func.append(k)
signatures.append(str(e.nopython_signatures[0]))
auto_jit = True
finally:
os.dup2(stdin_bk, 0)
os.close(f)
else:
module = importlib.import_module(file_name)
for dir_ in dir(module):
e = eval('module.' + dir_)
if type(e) == numba.targets.registry.CPUDispatcher \
and e.nopython_signatures:
cc.export(dir_, e.nopython_signatures[0])(e)
func.append(dir_)
signatures.append(str(e.nopython_signatures[0]))
auto_jit = False
cc.output_dir = os.curdir
if func:
cc.compile()
return cc, func, signatures, auto_jit
import os
import numpy as np
from numba.pycc import CC
cc = CC('kernels')
output_dir = '{}/dist'.format(os.path.abspath('..'))
cc.output_dir = output_dir
@cc.export('square', 'f8(f8)')
def square(x):
return x**2
@cc.export('squarearr', 'f8[:](f8[:])')
def square_array(arr):
return np.square(arr)
cc.compile()
This is the pure python version where the cython code is outlined
CSparse3.py: a Concise Sparse matrix Python package
@author: Timothy A. Davis
@author: Richard Lincoln
@author: Santiago Peñate Vera
"""
import numpy as np
import numba as nb
from numba.pycc import CC
from numba.typed import List
import math
cc = CC(extension_name='csc_native', source_module='CSparse3')
cc.output_dir = 'CSParse3'
def compile_code():
cc.compile()
@cc.export('ialloc', 'i4[:](i8)')
def ialloc(n):
return np.zeros(n, dtype=nb.int32)
@cc.export('xalloc', 'f8[:](i8)')
def xalloc(n):
return np.zeros(n, dtype=nb.float64)
