@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)