def test_largest_sequence_search_traverses_grid():
q00 = cirq.GridQubit(0, 0)
q10 = cirq.GridQubit(1, 0)
q11 = cirq.GridQubit(1, 1)
q20 = cirq.GridQubit(2, 0)
q30 = cirq.GridQubit(3, 0)
q40 = cirq.GridQubit(4, 0)
q41 = cirq.GridQubit(4, 1)
q42 = cirq.GridQubit(4, 2)
q50 = cirq.GridQubit(5, 0)
qubits = [q00, q10, q11, q20, q30, q40, q50, q41, q42]
device = _create_device(qubits)
search = greedy._PickLargestArea(device, q20)
# + + +-+-+ +
# |
# + +
# |
# +
assert search._choose_next_qubit(q20, {q20}) == q30
assert search._choose_next_qubit(q30, {q20, q30}) == q40
assert search._choose_next_qubit(q40, {q20, q30, q40}) == q41
assert search._choose_next_qubit(q41, {q20, q30, q40, q41}) == q42
assert search._choose_next_qubit(q42, {q20, q30, q40, q41, q42}) is None
method = greedy.GreedySequenceSearchStrategy('largest_area')
assert method.place_line(device, 7) == GridQubitLineTuple(
[q00, q10, q20, q30, q40, q41, q42])
with pytest.raises(NotFoundError):
_ = method.place_line(device, 8)
def test_greedy_search_method_returns_longest():
q00 = cirq.GridQubit(0, 0)
q10 = cirq.GridQubit(1, 0)
device = _create_device([q00, q10])
length = 1
method = greedy.GreedySequenceSearchStrategy()
assert method.place_line(device, length) == GridQubitLineTuple([q00])
def test_greedy_search_method_returns_empty_when_empty(minimal, largest):
largest.return_value.get_or_search.return_value = []
minimal.return_value.get_or_search.return_value = []
device = _create_device([])
length = 0
method = GreedySequenceSearchStrategy()
assert method.place_line(device, length) == GridQubitLineTuple()
def test_line_placement_str():
q00 = cirq.GridQubit(0, 0)
q01 = cirq.GridQubit(0, 1)
q02 = cirq.GridQubit(0, 2)
placement = GridQubitLineTuple([q00, q01, q02])
assert str(placement).strip() == """
(0, 0)━━(0, 1)━━(0, 2)
""".strip()
def place_line(self,
device: 'cirq.google.XmonDevice',
length: int) -> GridQubitLineTuple:
"""Runs line sequence search.
Args:
device: Chip description.
length: Required line length.
Returns:
Linear sequences found on the chip.
Raises:
ValueError: If search algorithm passed on initialization is not
recognized.
"""
if not device.qubits:
return GridQubitLineTuple()
start = min(device.qubits) # type: GridQubit
sequences = [] # type: List[LineSequence]
greedy_search = {
'minimal_connectivity': [
_PickFewestNeighbors(device, start),
],
'largest_area': [
_PickLargestArea(device, start),
],
'best': [
_PickFewestNeighbors(device, start),
_PickLargestArea(device, start),
]
} # type: Dict[str, List[GreedySequenceSearch]]
algos = greedy_search.get(self.algorithm)
if algos is None:
raise ValueError(
"Unknown greedy search algorithm %s" % self.algorithm)
for algorithm in algos:
sequences.append(algorithm.get_or_search())
return GridQubitLineTuple.best_of(sequences, length)
def test_line_placement_to_str():
q00 = cirq.GridQubit(0, 0)
q01 = cirq.GridQubit(0, 1)
q02 = cirq.GridQubit(0, 2)
q10 = cirq.GridQubit(1, 0)
q11 = cirq.GridQubit(1, 1)
placement = GridQubitLineTuple([q02, q01, q00, q10, q11])
assert str(placement).strip() == """
(0, 0)━━(0, 1)━━(0, 2)
┃
(1, 0)━━(1, 1)
""".strip()
def test_greedy_search_method_calls_minimal_only(minimal, largest):
q00 = cirq.GridQubit(0, 0)
q01 = cirq.GridQubit(0, 1)
device = _create_device([q00, q01])
length = 2
sequence = [q00, q01]
minimal.return_value.get_or_search.return_value = sequence
method = greedy.GreedySequenceSearchStrategy('minimal_connectivity')
assert method.place_line(device, length) == GridQubitLineTuple(sequence)
largest.return_value.get_or_search.assert_not_called()
minimal.return_value.get_or_search.assert_called_once_with()
def test_greedy_search_method_returns_longest(minimal, largest):
q00 = GridQubit(0, 0)
q10 = GridQubit(1, 0)
device = _create_device([])
length = 1
sequence_short = [q00]
sequence_long = [q00, q10]
largest.return_value.get_or_search.return_value = sequence_short
minimal.return_value.get_or_search.return_value = sequence_long
method = GreedySequenceSearchStrategy()
assert method.place_line(
device, length) == GridQubitLineTuple(sequence_long)[:length]
def place_line(self, device: XmonDevice, length: int) -> GridQubitLineTuple:
"""Runs line sequence search.
Args:
device: Chip description.
length: Required line length.
Returns:
List of linear sequences on the chip found by simulated annealing
method.
"""
seqs = AnnealSequenceSearch(device, self.seed).search(self.trace_func)
return GridQubitLineTuple.best_of(seqs, length)
def place_line(self, device: 'cirq.google.XmonDevice',
length: int) -> GridQubitLineTuple:
"""Runs line sequence search.
Args:
device: Chip description.
length: Required line length.
Returns:
List of linear sequences on the chip found by simulated annealing
method.
"""
seqs = AnnealSequenceSearch(device, self.seed).search(self.trace_func)
return GridQubitLineTuple.best_of(seqs, length)
def place_line(self, device: XmonDevice, length: int) -> GridQubitLineTuple:
"""Runs line sequence search.
Args:
device: Chip description.
length: Required line length.
Returns:
Linear sequences found on the chip.
Raises:
ValueError: If search algorithm passed on initialization is not
recognized.
"""
def lower_left():
cand = None
for n in device.qubits:
if cand is None or yx_cmp(n, cand) < 0:
cand = n
return cand
start = lower_left()
greedy_search = {
'minimal_connectivity':
MinimalConnectivityGreedySequenceSearch(device, start),
'largest_area':
LargestAreaGreedySequenceSearch(device, start)
}
if (self.algorithm not in greedy_search.keys() and
self.algorithm != self.BEST):
raise ValueError(
"Unknown greedy search algorithm %s" % self.algorithm)
sequence = [] # type: List[GridQubit]
for algorithm in greedy_search:
if algorithm == self.algorithm or self.algorithm == self.BEST:
candidate = greedy_search[algorithm].get_or_search()
if len(sequence) < len(candidate):
sequence = candidate
return GridQubitLineTuple.best_of([sequence], length)
def place_line(self, device: XmonDevice,
length: int) -> GridQubitLineTuple:
"""Runs line sequence search.
Args:
device: Chip description.
length: Required line length.
Returns:
Linear sequences found on the chip.
Raises:
ValueError: If search algorithm passed on initialization is not
recognized.
"""
def lower_left():
cand = None
for n in device.qubits:
if cand is None or yx_cmp(n, cand) < 0:
cand = n
return cand
start = lower_left()
greedy_search = {
'minimal_connectivity':
MinimalConnectivityGreedySequenceSearch(device, start),
'largest_area':
LargestAreaGreedySequenceSearch(device, start)
}
if (self.algorithm not in greedy_search.keys()
and self.algorithm != self.BEST):
raise ValueError("Unknown greedy search algorithm %s" %
self.algorithm)
sequence = [] # type: List[GridQubit]
for algorithm in greedy_search:
if algorithm == self.algorithm or self.algorithm == self.BEST:
candidate = greedy_search[algorithm].get_or_search()
if len(sequence) < len(candidate):
sequence = candidate
return GridQubitLineTuple.best_of([sequence], length)
def test_greedy_search_method_returns_empty_when_empty():
device = _create_device([])
length = 0
method = greedy.GreedySequenceSearchStrategy()
assert method.place_line(device, length) == GridQubitLineTuple()
def test_best_of_gets_longest_needs_minimum():
q00 = cirq.GridQubit(0, 0)
q01 = cirq.GridQubit(0, 1)
assert GridQubitLineTuple.best_of([[]], 0) == ()
assert GridQubitLineTuple.best_of([[], [q00]], 0) == ()
assert GridQubitLineTuple.best_of([[q00], []], 0) == ()
assert GridQubitLineTuple.best_of([[], [q00]], 1) == (q00,)
assert GridQubitLineTuple.best_of([[q00], []], 1) == (q00,)
assert GridQubitLineTuple.best_of([[q00, q01], [q00]], 1) == (q00,)
assert GridQubitLineTuple.best_of([[q00, q01], [q00]], 2) == (q00, q01)
assert GridQubitLineTuple.best_of([[q00, q01]], 2) == (q00, q01)
with pytest.raises(NotFoundError):
_ = GridQubitLineTuple.best_of([], 0)
with pytest.raises(NotFoundError):
_ = GridQubitLineTuple.best_of([[]], 1)
with pytest.raises(NotFoundError):
_ = GridQubitLineTuple.best_of([[q00]], 2)
