def test_one_hot_enc_integer(self):
a = OneHotEncInteger("a", (0, 4), strength=Placeholder("s"))
H = (a - 3) ** 2
model = H.compile()
q, offset = model.to_qubo(feed_dict={"s": 10.0})
sampleset = dimod.ExactSolver().sample_qubo(q)
decoded = model.decode_sampleset(
sampleset, feed_dict={"s": 10.0})
best = min(decoded, key=lambda x: x.energy)
self.assertTrue(best.subh["a"]==3)
self.assertTrue(a.value_range == (0, 4))
expected_q = {('a[0]', 'a[1]'): 20.0,
('a[0]', 'a[2]'): 20.0,
('a[0]', 'a[3]'): 20.0,
('a[0]', 'a[4]'): 20.0,
('a[1]', 'a[2]'): 24.0,
('a[1]', 'a[3]'): 26.0,
('a[1]', 'a[4]'): 28.0,
('a[2]', 'a[3]'): 32.0,
('a[2]', 'a[4]'): 36.0,
('a[3]', 'a[4]'): 44.0,
('a[0]', 'a[0]'): -10.0,
('a[1]', 'a[1]'): -15.0,
('a[2]', 'a[2]'): -18.0,
('a[3]', 'a[3]'): -19.0,
('a[4]', 'a[4]'): -18.0}
expected_offset = 19
assert_qubo_equal(q, expected_q)
self.assertTrue(offset == expected_offset)
def test_one_hot_enc_integer(self):
a = OneHotEncInteger("a", 0, 4, strength=Placeholder("s"))
H = (a - 3) ** 2
model = H.compile()
q, offset = model.to_qubo(feed_dict={"s": 10.0})
sampleset = dimod.ExactSolver().sample_qubo(q)
response, broken, e = model.decode_dimod_response(
sampleset, topk=1, feed_dict={"s": 10.0})[0]
self.assertTrue(response["a"][0] == 0)
self.assertTrue(response["a"][1] == 0)
self.assertTrue(response["a"][2] == 0)
self.assertTrue(response["a"][3] == 1)
self.assertTrue(response["a"][4] == 0)
self.assertTrue(a.interval == (0, 4))
expected_q = {('a[0]', 'a[1]'): 40.0,
('a[0]', 'a[2]'): 40.0,
('a[0]', 'a[3]'): 40.0,
('a[0]', 'a[4]'): 40.0,
('a[1]', 'a[2]'): 44.0,
('a[1]', 'a[3]'): 46.0,
('a[1]', 'a[4]'): 48.0,
('a[2]', 'a[3]'): 52.0,
('a[2]', 'a[4]'): 56.0,
('a[3]', 'a[4]'): 64.0,
('a[0]', 'a[0]'): -20.0,
('a[1]', 'a[1]'): -25.0,
('a[2]', 'a[2]'): -28.0,
('a[3]', 'a[3]'): -29.0,
('a[4]', 'a[4]'): -28.0}
assert_qubo_equal(q, expected_q)
def test_to_qubo_with_index(self):
a, b = Qbit("a"), Qbit("b")
exp = 1 + a * b + a - 2
model = exp.compile()
qubo, offset = model.to_qubo(index_label=True)
assert_qubo_equal(qubo, {(0, 0): 1.0, (0, 1): 1.0, (1, 1): 0.0})
self.assertTrue(offset == -1)
def test_to_ising_with_index(self):
a, b = Qbit("a"), Qbit("b")
exp = 1 + a * b + a - 2
model = exp.compile()
linear, quad, offset = model.to_ising(index_label=True)
self.assertTrue(linear == {0: 0.75, 1: 0.25})
assert_qubo_equal(quad, {(0, 1): 0.25})
self.assertTrue(offset == -0.25)
def test_to_ising(self):
a, b = Qbit("a"), Qbit("b")
exp = 1 + a * b + a - 2
model = exp.compile()
linear, quad, offset = model.to_ising()
self.assertTrue(linear == {'a': 0.75, 'b': 0.25})
assert_qubo_equal(quad, {('a', 'b'): 0.25})
self.assertTrue(offset == -0.25)
def test_to_qubo(self):
a, b = Binary("a"), Binary("b")
exp = 1 + a * b + a - 2
model = exp.compile()
qubo, offset = model.to_qubo()
# assert_qubo_equal(qubo, {("a", "a"): 1.0, ("a", "b"): 1.0, ("b", "b"): 0.0})
assert_qubo_equal(qubo, {("a", "a"): 1.0, ("a", "b"): 1.0})
self.assertTrue(offset == -1)
def compile_check(self,
exp,
expected_qubo,
expected_offset,
expected_structure,
feed_dict=None):
model = exp.compile(strength=5)
qubo, offset = model.to_qubo(feed_dict=feed_dict)
assert_qubo_equal(qubo, expected_qubo)
self.assertEqual(qubo, expected_qubo)
self.assertEqual(offset, expected_offset)
self.assertEqual(model.structure, expected_structure)
def test_qubo_equal(self):
qubo1 = {('a', 'b'): 1.0}
qubo2 = {('b', 'a'): 1.0}
qubo3 = {('a', 'b'): 2.0}
qubo4 = {('b', 'a'): 2.0}
qubo5 = {('c', 'a'): 1.0}
assert_qubo_equal(qubo1, qubo2)
self.assertRaises(AssertionError,
lambda: assert_qubo_equal(qubo1, qubo3))
self.assertRaises(AssertionError,
lambda: assert_qubo_equal(qubo1, qubo4))
self.assertRaises(AssertionError,
lambda: assert_qubo_equal(qubo1, qubo5))
def test_placeholders(self):
a, b, p = Binary("a"), Binary("b"), Placeholder("p")
feed_dict = {'p': 2.0}
exp = p * (1 + a * b + a)
model = exp.compile()
qubo, offset = model.to_qubo(index_label=False, feed_dict=feed_dict)
dict_solution = {'a': 1, 'b': 0}
dict_energy = model.energy(dict_solution,
vartype="BINARY",
feed_dict=feed_dict)
list_solution = [1, 0]
list_energy = model.energy(list_solution,
vartype="BINARY",
feed_dict=feed_dict)
assert_qubo_equal(qubo, {
('a', 'b'): 2.0,
('a', 'a'): 2.0,
('b', 'b'): 0.0
})
self.assertEqual(offset, 2.0)
self.assertTrue(dict_energy, 2.0)
self.assertTrue(list_energy, 2.0)
# Test that `decode_dimod_response` accepts the `feed_dict` arg
import numpy as np
import dimod
n = 10
p = Placeholder("p")
feed_dict = {'p': 2}
A = [np.random.randint(-50, 50) for _ in range(n)]
S = Array.create('S', n, "BINARY")
H = sum(p * A[i] * S[i] for i in range(n))**2
model = H.compile()
binary_bqm = model.to_dimod_bqm(feed_dict=feed_dict)
sa = dimod.reference.SimulatedAnnealingSampler()
response = sa.sample(binary_bqm, num_reads=10, num_sweeps=5)
# Confirm that decode_dimod_response() accecpts a feed_dict. Test of accuracy delegated to decode_solution()
decoded_solutions = model.decode_dimod_response(response,
topk=2,
feed_dict=feed_dict)
for (decoded_solution, broken, energy) in decoded_solutions:
assert isinstance(decoded_solution, dict)
assert isinstance(broken, dict)
assert isinstance(energy, float)
def test_order_enc_integer(self):
a = OrderEncInteger("a", (0, 4), strength=Placeholder("s"))
model = ((a - 3)**2).compile()
q, offset = model.to_qubo(feed_dict={"s": 10.0})
expected_q = {
('a[3]', 'a[2]'): -8.0,
('a[0]', 'a[1]'): -8.0,
('a[3]', 'a[0]'): 2.0,
('a[2]', 'a[0]'): 2.0,
('a[1]', 'a[1]'): 5.0,
('a[3]', 'a[1]'): 2.0,
('a[2]', 'a[1]'): -8.0,
('a[3]', 'a[3]'): 5.0,
('a[0]', 'a[0]'): -5.0,
('a[2]', 'a[2]'): 5.0
}
response = dimod.ExactSolver().sample_qubo(q)
decoded = model.decode_sampleset(response, feed_dict={"s": 10.0})[0]
self.assertTrue(decoded.subh["a"] == 3)
self.assertTrue(a.value_range == (0, 4))
assert_qubo_equal(q, expected_q)
def test_params(self):
a, b, p = Qbit("a"), Qbit("b"), Param("p")
params = {'p': 2.0}
exp = p * (1 + a * b + a)
model = exp.compile()
qubo, offset = model.to_qubo(index_label=False, params=params)
dict_solution = {'a': 1, 'b': 0}
dict_energy = model.energy(dict_solution,
var_type="binary",
params=params)
list_solution = [1, 0]
list_energy = model.energy(list_solution,
var_type="binary",
params=params)
assert_qubo_equal(qubo, {
('a', 'b'): 2.0,
('a', 'a'): 2.0,
('b', 'b'): 0.0
})
self.assertEqual(offset, 2.0)
self.assertTrue(dict_energy, 2.0)
self.assertTrue(list_energy, 2.0)
def test_placeholders(self):
a, b, p = Qbit("a"), Qbit("b"), Placeholder("p")
feed_dict = {'p': 2.0}
exp = p * (1 + a * b + a)
model = exp.compile()
qubo, offset = model.to_qubo(index_label=False, feed_dict=feed_dict)
dict_solution = {'a': 1, 'b': 0}
dict_energy = model.energy(dict_solution,
vartype="BINARY",
feed_dict=feed_dict)
list_solution = [1, 0]
list_energy = model.energy(list_solution,
vartype="BINARY",
feed_dict=feed_dict)
assert_qubo_equal(qubo, {
('a', 'b'): 2.0,
('a', 'a'): 2.0,
('b', 'b'): 0.0
})
self.assertEqual(offset, 2.0)
self.assertTrue(dict_energy, 2.0)
self.assertTrue(list_energy, 2.0)
def test_unary_enc_integer(self):
a = UnaryEncInteger("a", (0, 3))
b = UnaryEncInteger("b", (0, 3))
M = 2.0
H = (2 * a - b - 1)**2 + M * (a + b - 3)**2
model = H.compile()
q, offset = model.to_qubo()
sampleset = dimod.ExactSolver().sample_qubo(q)
decoded = model.decode_sampleset(sampleset)[0]
self.assertTrue(decoded.subh["a"] == 1)
self.assertTrue(decoded.subh["b"] == 2)
self.assertTrue(a.value_range == (0, 3))
self.assertTrue(b.value_range == (0, 3))
expected_q = {
('a[0]', 'a[1]'): 12.0,
('a[0]', 'a[2]'): 12.0,
('a[0]', 'b[0]'): 0.0,
('a[0]', 'b[1]'): 0.0,
('a[0]', 'b[2]'): 0.0,
('a[1]', 'a[2]'): 12.0,
('a[1]', 'b[0]'): 0.0,
('a[1]', 'b[1]'): 0.0,
('a[1]', 'b[2]'): 0.0,
('a[2]', 'b[0]'): 0.0,
('a[2]', 'b[1]'): 0.0,
('a[2]', 'b[2]'): 0.0,
('b[0]', 'b[1]'): 6.0,
('b[0]', 'b[2]'): 6.0,
('b[1]', 'b[2]'): 6.0,
('a[0]', 'a[0]'): -10.0,
('a[1]', 'a[1]'): -10.0,
('a[2]', 'a[2]'): -10.0,
('b[0]', 'b[0]'): -7.0,
('b[1]', 'b[1]'): -7.0,
('b[2]', 'b[2]'): -7.0
}
assert_qubo_equal(q, expected_q)
def test_log_enc_integer(self):
a = LogEncInteger("a", 0, 4)
b = LogEncInteger("b", 0, 4)
M = 2.0
H = (2 * a - b - 1) ** 2 + M * (a + b - 5) ** 2
model = H.compile()
q, offset = model.to_qubo()
sampleset = dimod.ExactSolver().sample_qubo(q)
response, broken, e = model.decode_dimod_response(sampleset, topk=1)[0]
sol_a = sum(2 ** k * v for k, v in response["a"].items())
sol_b = sum(2 ** k * v for k, v in response["b"].items())
self.assertTrue(sol_a == 2)
self.assertTrue(sol_b == 3)
self.assertTrue(a.interval == (0, 4))
self.assertTrue(b.interval == (0, 4))
expected_q = {('a[0]', 'a[1]'): 24.0,
('a[0]', 'a[2]'): 48.0,
('a[0]', 'b[0]'): 0.0,
('a[0]', 'b[1]'): 0.0,
('a[0]', 'b[2]'): 0.0,
('a[1]', 'a[2]'): 96.0,
('a[1]', 'b[0]'): 0.0,
('a[1]', 'b[1]'): 0.0,
('a[1]', 'b[2]'): 0.0,
('a[2]', 'b[0]'): 0.0,
('a[2]', 'b[1]'): 0.0,
('a[2]', 'b[2]'): 0.0,
('b[0]', 'b[1]'): 12.0,
('b[0]', 'b[2]'): 24.0,
('b[1]', 'b[2]'): 48.0,
('a[0]', 'a[0]'): -18.0,
('a[1]', 'a[1]'): -24.0,
('a[2]', 'a[2]'): 0.0,
('b[0]', 'b[0]'): -15.0,
('b[1]', 'b[1]'): -24.0,
('b[2]', 'b[2]'): -24.0}
assert_qubo_equal(q, expected_q)
def test_order_enc_integer(self):
a = OrderEncInteger("a", 0, 4, strength=Placeholder("s"))
model = ((a - 3) ** 2).compile()
q, offset = model.to_qubo(feed_dict={"s": 10.0})
expected_q = {('a[0]', 'a[1]'): -18.0,
('a[0]', 'a[2]'): 2.0,
('a[0]', 'a[3]'): 2.0,
('a[1]', 'a[2]'): -18.0,
('a[1]', 'a[3]'): 2.0,
('a[2]', 'a[3]'): -18.0,
('a[0]', 'a[0]'): -5.0,
('a[1]', 'a[1]'): 15.0,
('a[2]', 'a[2]'): 15.0,
('a[3]', 'a[3]'): 15.0}
response = dimod.ExactSolver().sample_qubo(q)
response, broken, e = model.decode_dimod_response(
response, topk=1, feed_dict={"s": 10.0})[0]
self.assertTrue(response["a"][0] == 1)
self.assertTrue(response["a"][1] == 1)
self.assertTrue(response["a"][2] == 1)
self.assertTrue(response["a"][3] == 0)
self.assertTrue(a.interval == (0, 4))
assert_qubo_equal(q, expected_q)
def test_unary_enc_integer(self):
a = UnaryEncInteger("a", 0, 3)
b = UnaryEncInteger("b", 0, 3)
M = 2.0
H = (2 * a - b - 1) ** 2 + M * (a + b - 3) ** 2
model = H.compile()
q, offset = model.to_qubo()
sampleset = dimod.ExactSolver().sample_qubo(q)
response, broken, e = model.decode_dimod_response(sampleset, topk=1)[0]
self.assertTrue(sum(response["a"].values()) == 1)
self.assertTrue(sum(response["b"].values()) == 2)
self.assertTrue(a.interval == (0, 3))
self.assertTrue(b.interval == (0, 3))
expected_q = {('a[0]', 'a[1]'): 12.0,
('a[0]', 'a[2]'): 12.0,
('a[0]', 'b[0]'): 0.0,
('a[0]', 'b[1]'): 0.0,
('a[0]', 'b[2]'): 0.0,
('a[1]', 'a[2]'): 12.0,
('a[1]', 'b[0]'): 0.0,
('a[1]', 'b[1]'): 0.0,
('a[1]', 'b[2]'): 0.0,
('a[2]', 'b[0]'): 0.0,
('a[2]', 'b[1]'): 0.0,
('a[2]', 'b[2]'): 0.0,
('b[0]', 'b[1]'): 6.0,
('b[0]', 'b[2]'): 6.0,
('b[1]', 'b[2]'): 6.0,
('a[0]', 'a[0]'): -10.0,
('a[1]', 'a[1]'): -10.0,
('a[2]', 'a[2]'): -10.0,
('b[0]', 'b[0]'): -7.0,
('b[1]', 'b[1]'): -7.0,
('b[2]', 'b[2]'): -7.0}
assert_qubo_equal(q, expected_q)
