def test_swap_pieces(nqubits):
state = utils.random_tensorflow_complex((2**nqubits, ), dtype=tf.float64)
target_state = tf.cast(np.copy(state.numpy()), dtype=state.dtype)
shape = (2, int(state.shape[0]) // 2)
for _ in range(10):
global_qubit = np.random.randint(0, nqubits)
local_qubit = np.random.randint(0, nqubits)
while local_qubit == global_qubit:
local_qubit = np.random.randint(0, nqubits)
transpose_order = ([global_qubit] + list(range(global_qubit)) +
list(range(global_qubit + 1, nqubits)))
qubits_t = qubits_tensor(nqubits, [global_qubit, local_qubit])
target_state = op.apply_swap(target_state, qubits_t, nqubits,
global_qubit, local_qubit)
target_state = tf.reshape(target_state, nqubits * (2, ))
target_state = tf.transpose(target_state, transpose_order)
target_state = tf.reshape(target_state, shape)
state = tf.reshape(state, nqubits * (2, ))
state = tf.transpose(state, transpose_order)
state = tf.reshape(state, shape)
piece0, piece1 = state[0], state[1]
if tf.config.list_physical_devices("GPU"): # pragma: no cover
# case not tested by GitHub workflows because it requires GPU
check_unimplemented_error(op.swap_pieces, piece0, piece1,
local_qubit - 1, nqubits - 1)
else:
op.swap_pieces(piece0, piece1,
local_qubit - int(global_qubit < local_qubit),
nqubits - 1)
np.testing.assert_allclose(target_state[0], piece0.numpy())
np.testing.assert_allclose(target_state[1], piece1.numpy())
def _swap(self, state: utils.DistributedState, global_qubit: int,
local_qubit: int):
m = self.queues.qubits.reduced_global[global_qubit]
m = self.nglobal - m - 1
t = 1 << m
for g in range(self.ndevices // 2):
i = ((g >> m) << (m + 1)) + (g & (t - 1))
local_eff = self.queues.qubits.reduced_local[local_qubit]
with tf.device(self.memory_device):
op.swap_pieces(state.pieces[i], state.pieces[i + t], local_eff,
self.nlocal)
def test_swap_pieces_zero_global(nqubits):
state = utils.random_tensorflow_complex((2**nqubits, ), dtype=tf.float64)
target_state = tf.cast(np.copy(state.numpy()), dtype=state.dtype)
shape = (2, int(state.shape[0]) // 2)
state = tf.reshape(state, shape)
for _ in range(10):
local = np.random.randint(1, nqubits)
qubits_t = qubits_tensor(nqubits, [0, local])
target_state = op.apply_swap(target_state, qubits_t, nqubits, 0, local)
target_state = tf.reshape(target_state, shape)
piece0, piece1 = state[0], state[1]
if tf.config.list_physical_devices("GPU"): # pragma: no cover
# case not tested by GitHub workflows because it requires GPU
check_unimplemented_error(op.swap_pieces, piece0, piece1,
local - 1, nqubits - 1)
else:
op.swap_pieces(piece0, piece1, local - 1, nqubits - 1)
np.testing.assert_allclose(target_state[0], piece0.numpy())
np.testing.assert_allclose(target_state[1], piece1.numpy())