@boost
def func2(a: A, b: float):
return a - func_tmp(b)
A1 = Array[int, "1d", "C", "memview"]
@boost
def func3(c: const(A1)):
return c[0] + 1
ts = Transonic()
def func1(a, b):
n = 10
if ts.is_transpiled:
result = ts.use_block("block0")
else:
# transonic block (
# float a, b;
# int n
# )
result = 0.0
for _ in range(n):
import numpy as np
import foo
from transonic import Transonic, Type, NDim, Array
T = Type(float, complex)
N = NDim(1, 2)
A = Array[T, N]
A1 = Array[T, N + 1]
ts = Transonic()
class MyClass:
def __init__(self, a, b):
self.a = a
self.b = b
def compute(self, n):
a = self.a
b = self.b
if ts.is_transpiled:
result = ts.use_block("block0")
else:
# transonic block (
# A a; A1 b;
# float n
# )
def test_use_pythran_false():
Transonic(use_transonified=False)