tensorcircuit.interfaces.numpy#

Interface wraps quantum function as a numpy function

tensorcircuit.interfaces.numpy.np_interface(fun: Callable[[...], Any], jit: bool = True) → Callable[[...], Any]#

Convert fun on ML backend into a numpy function

Example

K = tc.set_backend("tensorflow")

def f(params, n):
    c = tc.Circuit(n)
    for i in range(n):
        c.rx(i, theta=params[i])
    for i in range(n-1):
        c.cnot(i, i+1)
    r = K.real(c.expectation_ps(z=[n-1]))
    return r

n = 3
f_np = tc.interfaces.numpy_interface(f, jit=True)
f_np(np.ones([n]), n)  # 0.1577285

Parameters

fun (Callable[..., Any]) – The quantum function
jit (bool, optional) – whether to jit fun, defaults to True

Returns

The numpy interface compatible version of fun

Return type

Callable[…, Any]

tensorcircuit.interfaces.numpy.numpy_interface(fun: Callable[[...], Any], jit: bool = True) → Callable[[...], Any][source]#