def test_free_par_str(self):
"""Test a FreeParameter with some transformations converts properly"""
prog = Program(2)
r, alpha = prog.params('r', 'alpha')
with prog.context as q:
ops.Sgate(r) | q[0]
ops.Zgate(3 * pf.log(-alpha)) | q[1]
bb = io.to_blackbird(prog)
assert bb.operations[0] == {"op": "Sgate", "modes": [0], "args": ['{r}', 0.0], "kwargs": {}}
assert bb.operations[1] == {"op": "Zgate", "modes": [1], "args": ['3*log(-{alpha})'], "kwargs": {}}
def test_free_par_str(self):
"""Test a FreeParameter with some transformations converts properly"""
sf_prog = Program(2)
r, alpha = sf_prog.params("r", "alpha")
with sf_prog.context as q:
ops.Sgate(r) | q[0]
ops.Zgate(3 * pf.log(-alpha)) | q[1]
xir_prog = io.to_xir(sf_prog)
expected = [("Sgate", ["r", 0.0], (0,)), ("Zgate", ["3*log(-alpha)"], (1,))]
assert [(stmt.name, stmt.params, stmt.wires) for stmt in xir_prog.statements] == expected
def test_tf_batch_in_gates_previously_supporting_complex(gate):
"""Test if gates that previously accepted complex arguments support the input of TF tensors in
batch form"""
tf = pytest.importorskip("tensorflow")
batch_size = 2
prog = Program(1)
eng = Engine(backend="tf",
backend_options={
"cutoff_dim": 3,
"batch_size": batch_size
})
theta = prog.params("theta")
_theta = tf.Variable([0.1] * batch_size)
with prog.context as q:
gate(theta) | q[0]
eng.run(prog, args={"theta": _theta})
def test_tf_batch_complex_raise(gate):
"""Test if an error is raised if complex TF tensors with a batch dimension are input for gates
that previously accepted complex arguments"""
tf = pytest.importorskip("tensorflow")
batch_size = 2
prog = Program(1)
eng = Engine(backend="tf",
backend_options={
"cutoff_dim": 3,
"batch_size": batch_size
})
theta = prog.params("theta")
_theta = tf.Variable([0.1j] * batch_size)
with prog.context as q:
gate(theta) | q[0]
with pytest.raises(ValueError, match="cannot be complex"):
eng.run(prog, args={"theta": _theta})
