def test_initializer_context_type_error(self):
focus = (_random_operation(1, 2), _random_operation(1))
with self.assertRaisesRegex(
TypeError,
r'context is not a TransformationContext \(found type: int\)'):
transform.AttentionCircuit(focus, 42)
def test_initializer_focus_type_error(self, focus, message):
context = transform.TransformationContext(circuit.Circuit(5, None),
circuit.Circuit(5, None),
circuit.Circuit(5, None))
with self.assertRaisesRegex(TypeError, message):
transform.AttentionCircuit(focus, context)
def test_initializer_empty_focus_error(self):
context = transform.TransformationContext(circuit.Circuit(5, None),
circuit.Circuit(5, None),
circuit.Circuit(5, None))
with self.assertRaisesRegex(ValueError, r'focus must not be empty'):
transform.AttentionCircuit((), context)
def test_initializer_and_getters(self):
# preparation work
focus_in = [_random_operation(1, 2)]
context_in = transform.TransformationContext(circuit.Circuit(5, None),
circuit.Circuit(5, None),
circuit.Circuit(5, None))
locations_in = (0, )
perform_rule = lambda operation_in: [operation_in]
rule_id = object()
# initialize the PointTransformation
transformation = transform.PointTransformation(
attention_circ=transform.AttentionCircuit(focus=focus_in,
context=context_in,
locations=locations_in),
perform_rule=perform_rule,
rule_id=rule_id)
# check type and value transformation.focus()
focus_out = transformation.focus()
self.assertIs(type(focus_out), tuple)
self.assertTrue(_elementwise_is(focus_out, focus_in))
# check transformation.context()
self.assertIs(transformation.context(), context_in)
# check type and value transformation.locations()
locations_out = transformation.locations()
self.assertIs(type(locations_out), tuple)
self.assertTrue(_elementwise_is(locations_out, locations_in))
# check transformation.context()
self.assertIs(transformation.rule_id(), rule_id)
def test_initializer_without_locations_and_getters(self):
# preparation work
focus_in = (_random_operation(1, 2), _random_operation(1))
focus_length = len(focus_in)
context = transform.TransformationContext(
circuit.Circuit(5, [
_random_operation(2),
_random_operation(3),
_random_operation(4)
]), circuit.Circuit(5, [_random_operation(0)]),
circuit.Circuit(5, [_random_operation(0),
_random_operation(1, 2)]))
# construct the AttentionCircuit
att_circ = transform.AttentionCircuit(focus_in,
context,
locations=None)
# check type and value for att_circ.focus()
focus_out = att_circ.focus()
self.assertIs(type(focus_out), tuple)
self.assertTrue(_elementwise_is(focus_out, focus_in))
# check att_circ.context()
self.assertIs(att_circ.context(), context)
# check that att_circ.locations() is None
self.assertIsNone(att_circ.locations())
# check type and value for len(att_circ)
length = len(att_circ)
self.assertIs(type(length), int)
self.assertEqual(length, focus_length)
def test_perform(self):
# preparation work
num_qubits = 5
operation_before1 = _random_operation(0)
operation_before2 = _random_operation(1)
operation_before3 = _random_operation(2)
operation_between1 = _random_operation(0)
operation_between2 = _random_operation(1)
operation_after = _random_operation(1)
operation_in1 = _random_operation(1)
operation_in2 = _random_operation(1)
operation_in3 = _random_operation(1)
operation_in4 = _random_operation(1)
operation_out1 = _random_operation(1)
operation_out2 = _random_operation(1)
operation_out3 = _random_operation(1)
# define the transformation rule
def perform_rule(operations_in):
# check type and value for operations_in
self.assertIs(type(operations_in), tuple)
self.assertTrue(
_elementwise_is(operations_in, [
operation_in1, operation_in2, operation_in3, operation_in4
]))
# return the modified operations
return [operation_out1, operation_out2, operation_out3]
# initialize the PointTransformation
transformation = transform.GroupTransformation(
attention_circ=transform.AttentionCircuit(
focus=[
operation_in1, operation_in2, operation_in3, operation_in4
],
context=transform.TransformationContext(
circuit.Circuit(num_qubits, [
operation_before1, operation_before2, operation_before3
]),
circuit.Circuit(num_qubits,
[operation_between1, operation_between2]),
circuit.Circuit(num_qubits, [operation_after]))),
perform_rule=perform_rule,
rule_id=None)
# call the method to be tested
circ_out = transformation.perform()
# check type for circ_out
self.assertIs(type(circ_out), circuit.Circuit)
# check the value for circ_out
self.assertTrue(
_elementwise_is(circ_out.get_operation_sequence(), [
operation_before1, operation_before2, operation_before3,
operation_out1, operation_out2, operation_out3,
operation_between1, operation_between2, operation_after
]))
def test_initializer_locations_type_error(self, locations, message):
focus = (_random_operation(1, 2), _random_operation(1))
context = transform.TransformationContext(circuit.Circuit(5, None),
circuit.Circuit(5, None),
circuit.Circuit(5, None))
with self.assertRaisesRegex(TypeError, message):
transform.AttentionCircuit(focus, context, locations=locations)
def _positive_example_circuit(*segments_and_operations):
operations = []
segments = {'focus': [], 'before': [], 'between': [], 'after': []}
max_qubit = 0
for location, (segment_tag,
operation) in enumerate(segments_and_operations):
operations.append(operation)
segments[segment_tag].append(location)
max_qubit = np.maximum(max_qubit, max(operation.get_qubits()))
circ = circuit.Circuit(max_qubit + 1, operations)
# <checking that the example circuit makes sense>
assert len(segments['focus']) == 2
location_first, location_second = segments['focus'] # length checked in previous line, so pylint: disable=unbalanced-tuple-unpacking
assert all(location_before < location_second
for location_before in segments['before'])
assert all(location_first < location_between < location_second
for location_between in segments['between'])
assert all(location_after > location_first
for location_after in segments['after'])
pool_to_the_left = [
location_before for location_before in segments['before']
if location_before > location_first
]
pool_to_the_right = [
location_after for location_after in segments['after']
if location_after < location_second
]
assert all(circ[location_second].commutes_trivially_with(circ[location])
for location in segments['between'] + pool_to_the_right)
assert all(circ[location_first].commutes_trivially_with(circ[location])
for location in pool_to_the_left + segments['between'])
assert all(loc0 < loc1 or circ[loc0].commutes_trivially_with(circ[loc1])
for loc0, loc1 in itertools.product(pool_to_the_left,
segments['between']))
assert all(loc0 < loc1 or circ[loc0].commutes_trivially_with(circ[loc1])
for loc0, loc1 in itertools.product(pool_to_the_left,
pool_to_the_right))
assert all(loc0 < loc1 or circ[loc0].commutes_trivially_with(circ[loc1])
for loc0, loc1 in itertools.product(segments['between'],
pool_to_the_right))
# </checking that the example circuit makes sense>
return circ, transform.AttentionCircuit(
focus=circ[segments['focus']].get_operation_sequence(),
context=transform.TransformationContext(
before=circ[segments['before']],
between=circ[segments['between']],
after=circ[segments['after']]),
locations=segments['focus'])
def test_initializer_focus_size_error(self):
attention_circ = transform.AttentionCircuit(
focus=[_random_operation(2)],
context=transform.TransformationContext(circuit.Circuit(5, None),
circuit.Circuit(5, None),
circuit.Circuit(5, None)))
perform_rule = lambda operation_in: [operation_in]
with self.assertRaisesRegex(
ValueError,
r'focus of attention_circ for PairTransformation must have size 2'
r' \(found: 1\)'):
transform.PairTransformation(attention_circ, perform_rule, None)
def test_initializer_redundant_transformation_error(self):
attention_circ = transform.AttentionCircuit(
focus=[_random_operation(2, 3),
_random_operation(5)],
context=transform.TransformationContext(circuit.Circuit(5, None),
circuit.Circuit(5, None),
circuit.Circuit(5, None)))
perform_rule = lambda operation_in: [operation_in]
with self.assertRaisesRegex(
ValueError,
r'transformation redundant because operations trivially commute'
):
transform.PairTransformation(attention_circ, perform_rule, None)
def test_initializer_locations_length_error(self):
focus = (_random_operation(1, 2), _random_operation(1))
context = transform.TransformationContext(
circuit.Circuit(5, [
_random_operation(2),
_random_operation(3),
_random_operation(4)
]), circuit.Circuit(5, [_random_operation(0)]),
circuit.Circuit(5, [_random_operation(0),
_random_operation(1, 2)]))
with self.assertRaisesRegex(
ValueError,
r'inconsistent lengths for focus and locations: 2 vs. 1'):
transform.AttentionCircuit(focus, context, locations=(3, ))
def test_perform(self):
# preparation work
num_qubits = 5
operation_before1 = _random_operation(0)
operation_before2 = _random_operation(1)
operation_before3 = _random_operation(2)
operation_between1 = _random_operation(0)
operation_between2 = _random_operation(1)
operation_after = _random_operation(1)
operation_in1 = _random_operation(1)
operation_in2 = _random_operation(1)
operations_out_first1 = _random_operation(1)
operations_out_first2 = _random_operation(1)
operations_out_second1 = _random_operation(1)
operations_out_second2 = _random_operation(1)
operations_out_second3 = _random_operation(1)
# define the transformation rule
def perform_rule(operation_first, operation_second):
# check operation_first and operation_second
self.assertIs(operation_first, operation_in1)
self.assertIs(operation_second, operation_in2)
# return the modified operations
operations_out_first = [
operations_out_first1,
operations_out_first2
]
operations_out_second = [
operations_out_second1,
operations_out_second2,
operations_out_second3
]
return operations_out_first, operations_out_second
# initialize the PointTransformation
transformation = transform.PairTransformation(
attention_circ=transform.AttentionCircuit(
focus=[operation_in1, operation_in2],
context=transform.TransformationContext(
circuit.Circuit(num_qubits, [
operation_before1,
operation_before2,
operation_before3
]),
circuit.Circuit(num_qubits, [
operation_between1,
operation_between2
]),
circuit.Circuit(num_qubits, [
operation_after
])
)
),
perform_rule=perform_rule,
rule_id=None
)
# call the method to be tested
circ_out = transformation.perform()
# check type for circ_out
self.assertIs(type(circ_out), circuit.Circuit)
# check the value for circ_out
self.assertTrue(_elementwise_is(
circ_out.get_operation_sequence(),
[
operation_before1,
operation_before2,
operation_before3,
operations_out_first1,
operations_out_first2,
operation_between1,
operation_between2,
operations_out_second1,
operations_out_second2,
operations_out_second3,
operation_after
]
))
