ai-content-maker/.venv/Lib/site-packages/numba/tests/compile_with_pycc.py

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2024-05-03 04:18:51 +03:00
import cmath
import numpy as np
from numba import float32
from numba.types import unicode_type, i8
from numba.pycc import CC, exportmany, export
from numba.tests.support import has_blas
from numba import typed
#
# New API
#
cc = CC('pycc_test_simple')
cc.use_nrt = False
# Note the first signature omits the return type
@cc.export('multf', (float32, float32))
@cc.export('multi', 'i4(i4, i4)')
def mult(a, b):
return a * b
# Test imported C globals such as Py_None, PyExc_ZeroDivisionError
@cc.export('get_none', 'none()')
def get_none():
return None
@cc.export('div', 'f8(f8, f8)')
def div(x, y):
return x / y
_two = 2
# This one can't be compiled by the legacy API as it doesn't execute
# the script in a proper module.
@cc.export('square', 'i8(i8)')
def square(u):
return u ** _two
# These ones need helperlib
cc_helperlib = CC('pycc_test_helperlib')
cc_helperlib.use_nrt = False
@cc_helperlib.export('power', 'i8(i8, i8)')
def power(u, v):
return u ** v
@cc_helperlib.export('sqrt', 'c16(c16)')
def sqrt(u):
return cmath.sqrt(u)
@cc_helperlib.export('size', 'i8(f8[:])')
def size(arr):
return arr.size
# Exercise linking to Numpy math functions
@cc_helperlib.export('np_sqrt', 'f8(f8)')
def np_sqrt(u):
return np.sqrt(u)
@cc_helperlib.export('spacing', 'f8(f8)')
def np_spacing(u):
return np.spacing(u)
# This one clashes with libc random() unless pycc is careful with naming.
@cc_helperlib.export('random', 'f8(i4)')
def random_impl(seed):
if seed != -1:
np.random.seed(seed)
return np.random.random()
# These ones need NRT
cc_nrt = CC('pycc_test_nrt')
@cc_nrt.export('zero_scalar', 'f8(i4)')
def zero_scalar(n):
arr = np.zeros(n)
return arr[-1]
if has_blas:
# This one also needs BLAS
@cc_nrt.export('vector_dot', 'f8(i4)')
def vector_dot(n):
a = np.linspace(1, n, n)
return np.dot(a, a)
# This one needs an environment
@cc_nrt.export('zeros', 'f8[:](i4)')
def zeros(n):
return np.zeros(n)
# requires list dtor, #issue3535
@cc_nrt.export('np_argsort', 'intp[:](float64[:])')
def np_argsort(arr):
return np.argsort(arr)
#
# Legacy API
#
exportmany(['multf f4(f4,f4)', 'multi i4(i4,i4)'])(mult)
# Needs to link to helperlib to due with complex arguments
# export('multc c16(c16,c16)')(mult)
export('mult f8(f8, f8)')(mult)
@cc_nrt.export('dict_usecase', 'intp[:](intp[:])')
def dict_usecase(arr):
d = typed.Dict()
for i in range(arr.size):
d[i] = arr[i]
out = np.zeros_like(arr)
for k, v in d.items():
out[k] = k * v
return out
# checks for issue #6386
@cc_nrt.export('internal_str_dict', i8(unicode_type))
def internal_str_dict(x):
d = typed.Dict.empty(unicode_type,i8)
if(x not in d):
d[x] = len(d)
return len(d)
@cc_nrt.export('hash_str', i8(unicode_type))
def internal_str_dict(x):
return hash(x)
@cc_nrt.export('hash_literal_str_A', i8())
def internal_str_dict():
return hash("A")