def test_as_completed(self):
"""Submit a batch of problems then use `as_completed` to iterate over
all of them."""
# Connect
with Client(**config) as client:
solver = client.get_solver()
# Build a problem
linear = [0] * (max(solver.nodes) + 1)
for index in solver.nodes:
linear[index] = random.choice([-1, 1])
quad = {
key: random.choice([-1, 1])
for key in solver.undirected_edges
}
# Sample the solution 100x40 times
computations = [
solver.sample_ising(linear, quad, num_reads=40)
for _ in range(100)
]
# Go over computations, one by one, as they're done and check they're OK
for computation in dwave.cloud.computation.Future.as_completed(
computations):
self.assertTrue(computation.done())
self.assertTrue(40 == sum(computation.occurrences))
for energy, state in zip(computation.energies,
computation.samples):
self.assertTrue(
energy == evaluate_ising(linear, quad, state))
def test_as_completed(self):
"""Submit a batch of problems then use `as_completed` to iterate over
all of them."""
with Client(**config) as client:
solver = client.get_solver()
linear, quad = generate_random_ising_problem(solver)
# Sample the solution 100x40 times
computations = [solver.sample_ising(linear, quad, num_reads=40) for _ in range(100)]
# Go over computations, one by one, as they're done and check they're OK
for computation in dwave.cloud.computation.Future.as_completed(computations):
self.assertTrue(computation.done())
self.assertEqual(40, sum(computation.occurrences))
for energy, state in zip(computation.energies, computation.samples):
self.assertAlmostEqual(energy, evaluate_ising(linear, quad, state))
