def test_run_correlations(dtype):
q0, q1 = cirq.LineQubit.range(2)
simulator = TFWaveFunctionSimulator(dtype=dtype)
circuit = cirq.Circuit.from_ops(cirq.H(q0), cirq.CNOT(q0, q1))
for _ in range(10):
circuit_op = simulator.simulate(circuit)
with tf.Session() as sess:
wf = sess.run(circuit_op)
measurements = cirq.sample_state_vector(wf.reshape(-1), [0, 1])
def test_resolve_named_placeholder():
"""Resolve named placeholders via feed_dict."""
wf = cirq.testing.random_superposition(2).astype(np.complex64)
# placeholders can be instantiated without references in circuit gates!
var_names = ["v_{}".format(i) for i in range(5)]
params = np.random.randn(5)
placeholder_circuit = cirq.Circuit()
for i in range(5):
placeholder_circuit += cirq.Rx(
tf.placeholder(tf.complex64, shape=(), name=f"theta_{i}"))(q(0))
circuit_op = TFWaveFunctionSimulator(dtype=tf.complex64).simulate(
placeholder_circuit, initial_state=wf)
placeholder_names = ["theta_{}:0".format(i) for i in range(5)]
feed_dict = dict(zip(placeholder_names, params))
with tf.Session() as sess:
tf_result = sess.run(circuit_op, feed_dict=feed_dict).reshape(-1)
circuit = cirq.Circuit()
for theta in params:
circuit += cirq.Rx(theta)(q(0))
cirq_result = cirq.Simulator().simulate(
circuit, initial_state=np.copy(wf)).final_state
np.testing.assert_array_almost_equal(tf_result, cirq_result)
def test_run_bit_flips(dtype):
q0, q1 = cirq.LineQubit.range(2)
simulator = TFWaveFunctionSimulator(dtype=dtype)
for b0 in [0, 1]:
for b1 in [0, 1]:
circuit = cirq.Circuit.from_ops((cirq.X**b0)(q0), (cirq.X**b1)(q1))
circuit_op = simulator.simulate(circuit)
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
wf = sess.run(circuit_op)
measurements = cirq.sample_state_vector(wf, [0, 1])
np.testing.assert_array_almost_equal(measurements[0], [b0, b1])
expected_state = np.zeros(shape=(2, 2))
expected_state[b0][b1] = 1.0
cirq.testing.assert_allclose_up_to_global_phase(wf.reshape(-1),
np.reshape(
expected_state, 4),
atol=1e-6)
def test_tf_wavefunction_simulator_vs_cirq_parametrized_two_qubit_gates(g, e):
circuit = cirq.Circuit.from_ops(g(exponent=e)(q(0), q(1)))
wf = cirq.testing.random_superposition(4).astype(np.complex64)
cirq_result = cirq.Simulator().simulate(
circuit, initial_state=np.copy(wf)).final_state
circuit_op = TFWaveFunctionSimulator(dtype=tf.complex64).simulate(
circuit, initial_state=np.copy(wf))
with tf.Session() as sess:
tf_result = sess.run(circuit_op).reshape(-1)
np.testing.assert_array_almost_equal(tf_result, cirq_result)
def test_tf_wavefunction_simulator_vs_cirq_parametrized_single_qubit_gates(
g, e):
inst = g(e)(q(0))
circuit = cirq.Circuit.from_ops(inst)
# wrapped = tf_gate_wrapper(inst)
wf = cirq.testing.random_superposition(2).astype(np.complex64)
cirq_result = cirq.Simulator().simulate(
circuit, initial_state=np.copy(wf)).final_state
circuit_op = TFWaveFunctionSimulator(dtype=tf.complex64).simulate(
circuit, initial_state=np.copy(wf))
with tf.Session() as sess:
tf_result = sess.run(circuit_op).reshape(-1)
np.testing.assert_array_almost_equal(tf_result, cirq_result, decimal=4)
def compile_tensorboard_session():
theta = tf.Variable(np.pi)
circuit = cirq.Circuit.from_ops(
cirq.Ry(theta)(q(0)), cirq.CNOT(q(0), q(1)))
tf.summary.scalar('theta', theta)
initial_state = np.asarray([1, 0, 0, 0])
circuit_op = TFWaveFunctionSimulator(dtype=tf.complex64).simulate(
circuit, initial_state=initial_state)
# with tf.Session() as sess:
# sess.run(tf.global_variables_initializer())
# wf = sess.run(circuit_op)
# return
tensorboard_session(circuit_op, {theta: np.pi / 2})
def test_tf_wavefunction_simulator_vs_cirq_single_qubit_gates(g):
wf = np.complex64(cirq.testing.random_superposition(2))
# print(rand_init)
for wf in [
np.array([1, 0], dtype=np.complex64),
np.array([0, 1], dtype=np.complex64)
]:
circuit = cirq.Circuit.from_ops(g(q(0)))
cirq_result = cirq.Simulator().simulate(
circuit, initial_state=np.copy(wf)).final_state
circuit_op = TFWaveFunctionSimulator(dtype=tf.complex64).simulate(
circuit, initial_state=np.copy(wf))
with tf.Session() as sess:
tf_result = sess.run(circuit_op).reshape(-1)
# !hep-qml CHANGES: testing assertion
np.testing.assert_array_almost_equal(tf_result, cirq_result)
def test_resolve_scalar_placeholder():
"""Resolve scalar placeholders via feed_dict."""
wf = cirq.testing.random_superposition(4).astype(np.complex64)
params = [0.83, 1.2]
theta_x = tf.placeholder(tf.complex64, shape=(), name="theta_x")
theta_y = tf.placeholder(tf.complex64, shape=(), name="theta_y")
placeholder_circuit = cirq.Circuit.from_ops([
cirq.Rx(theta_x)(q(0)),
cirq.Ry(theta_y)(q(1)),
])
circuit_op = TFWaveFunctionSimulator(dtype=tf.complex64).simulate(
placeholder_circuit, initial_state=wf)
feed_dict = dict(zip([theta_x, theta_y], params))
with tf.Session() as sess:
tf_result = sess.run(circuit_op, feed_dict=feed_dict).reshape(-1)
circuit = cirq.Circuit.from_ops([
cirq.Rx(params[0])(q(0)),
cirq.Ry(params[1])(q(1)),
])
cirq_result = cirq.Simulator().simulate(
circuit, initial_state=np.copy(wf)).final_state
np.testing.assert_array_almost_equal(tf_result, cirq_result)
def test_tf_wavefunction_simulator_instantiate():
_ = TFWaveFunctionSimulator()