def test_parametrizedgates_class():
from qibo.abstractions.circuit import _ParametrizedGates
paramgates = _ParametrizedGates()
paramgates.append(gates.RX(0, 0.1234))
paramgates.append(gates.fSim(0, 1, 0.1234, 0.4321))
assert len(paramgates.set) == 2
assert paramgates.nparams == 3
def test_fsim_init():
import numpy as np
gate = gates.fSim(0, 1, 0.1234, 0.4321)
assert gate.target_qubits == (0, 1)
matrix = np.random.random((2, 2))
gate = gates.GeneralizedfSim(0, 1, matrix, 0.4321)
assert gate.target_qubits == (0, 1)
assert gate.parameters == (matrix, 0.4321)
matrix = np.random.random((3, 3))
with pytest.raises(ValueError):
gate = gates.GeneralizedfSim(0, 1, matrix, 0.4321)
def test_circuit_draw_line_wrap():
"""Test circuit text draw with line wrap."""
ref_line_wrap_50 = \
'q0: ─H─U1─U1─U1─U1───────────────────────────x───I───f ...\n' \
'q1: ───o──|──|──|──H─U1─U1─U1────────────────|─x─I───| ...\n' \
'q2: ──────o──|──|────o──|──|──H─U1─U1────────|─|─────| ...\n' \
'q3: ─────────o──|───────o──|────o──|──H─U1───|─x───M─| ...\n' \
'q4: ────────────o──────────o───────o────o──H─x───────f ...\n' \
'\n' \
'q0: ... ─o────gf───M─\n' \
'q1: ... ─U3───|──o─M─\n' \
'q2: ... ────X─gf─o─M─\n' \
'q3: ... ────o────o───\n' \
'q4: ... ────o────X───'
ref_line_wrap_30 = \
'q0: ─H─U1─U1─U1─U1──────────────── ...\n' \
'q1: ───o──|──|──|──H─U1─U1─U1───── ...\n' \
'q2: ──────o──|──|────o──|──|──H─U1 ...\n' \
'q3: ─────────o──|───────o──|────o─ ...\n' \
'q4: ────────────o──────────o────── ...\n' \
'\n' \
'q0: ... ───────────x───I───f─o────gf── ...\n' \
'q1: ... ───────────|─x─I───|─U3───|──o ...\n' \
'q2: ... ─U1────────|─|─────|────X─gf─o ...\n' \
'q3: ... ─|──H─U1───|─x───M─|────o────o ...\n' \
'q4: ... ─o────o──H─x───────f────o────X ...\n' \
'\n' \
'q0: ... ─M─\n' \
'q1: ... ─M─\n' \
'q2: ... ─M─\n' \
'q3: ... ───\n' \
'q4: ... ───'
import numpy as np
circuit = Circuit(5)
for i1 in range(5):
circuit.add(gates.H(i1))
for i2 in range(i1 + 1, 5):
circuit.add(gates.CU1(i2, i1, theta=0))
circuit.add(gates.SWAP(0, 4))
circuit.add(gates.SWAP(1, 3))
circuit.add(gates.I(*range(2)))
circuit.add(gates.M(3, collapse=True))
circuit.add(gates.fSim(0, 4, 0, 0))
circuit.add(gates.CU3(0, 1, 0, 0, 0))
circuit.add(gates.TOFFOLI(4, 3, 2))
circuit.add(gates.GeneralizedfSim(0, 2, np.eye(2), 0))
circuit.add(gates.X(4).controlled_by(1, 2, 3))
circuit.add(gates.M(*range(3)))
assert circuit.draw(line_wrap=50) == ref_line_wrap_50
assert circuit.draw(line_wrap=30) == ref_line_wrap_30
def test_circuit_set_parameters_errors():
"""Check updating parameters errors."""
c = Circuit(2)
c.add(gates.RX(0, theta=0.789))
c.add(gates.RX(1, theta=0.789))
c.add(gates.fSim(0, 1, theta=0.123, phi=0.456))
with pytest.raises(KeyError):
c.set_parameters({gates.RX(0, theta=1.0): 0.568})
with pytest.raises(ValueError):
c.set_parameters([0.12586])
with pytest.raises(TypeError):
c.set_parameters({0.3568})
with pytest.raises(ValueError):
c.queue[2].parameters = [0.1234, 0.4321, 0.156]
def test_circuit_set_parameters_with_list(trainable):
"""Check updating parameters of circuit with list."""
params = [0.123, 0.456, (0.789, 0.321)]
c = Circuit(3)
if trainable:
c.add(gates.RX(0, theta=0, trainable=trainable))
else:
c.add(gates.RX(0, theta=params[0], trainable=trainable))
c.add(gates.RY(1, theta=0))
c.add(gates.CZ(1, 2))
c.add(gates.fSim(0, 2, theta=0, phi=0))
c.add(gates.H(2))
if trainable:
c.set_parameters(params)
assert c.queue[0].parameters == params[0]
else:
c.set_parameters(params[1:])
assert c.queue[1].parameters == params[1]
assert c.queue[3].parameters == params[2]
def test_get_parameters(trainable, include_not_trainable, format):
import numpy as np
matrix = np.random.random((2, 2))
c = Circuit(3)
c.add(gates.RX(0, theta=0.123))
c.add(gates.RY(1, theta=0.456, trainable=trainable))
c.add(gates.CZ(1, 2))
c.add(gates.Unitary(matrix, 2))
c.add(gates.fSim(0, 2, theta=0.789, phi=0.987, trainable=trainable))
c.add(gates.H(2))
c.param_tensor_types = (np.ndarray, )
params = c.get_parameters(format, include_not_trainable)
if trainable or include_not_trainable:
target_params = {
"list": [0.123, 0.456, (0.789, 0.987)],
"dict": {
c.queue[0]: 0.123,
c.queue[1]: 0.456,
c.queue[4]: (0.789, 0.987)
},
"flatlist": [0.123, 0.456]
}
target_params["flatlist"].extend(list(matrix.ravel()))
target_params["flatlist"].extend([0.789, 0.987])
else:
target_params = {
"list": [0.123],
"dict": {
c.queue[0]: 0.123
},
"flatlist": [0.123]
}
target_params["flatlist"].extend(list(matrix.ravel()))
if format == "list":
i = len(target_params["list"]) // 2 + 1
np.testing.assert_allclose(params.pop(i), matrix)
elif format == "dict":
np.testing.assert_allclose(params.pop(c.queue[3]), matrix)
assert params == target_params[format]
with pytest.raises(ValueError):
c.get_parameters("test")