def test_make_ilp():
x = theano.tensor.matrix('x')
y = theano.tensor.matrix('y')
z = theano.tensor.dot(x, x) + y[:,0].sum() - x*y
env = theano.FunctionGraph([x, y], [z])
machine_ids = ["ankaa", "arroyitos"]
prob, X, S, Cmax = make_ilp(env, machine_ids, dummy_compute_cost,
dummy_comm_cost, dummy_ability, 100)
prob.solve()
assert Cmax.value() == 5
def test_make_ilp():
x = theano.tensor.matrix('x')
y = theano.tensor.matrix('y')
z = theano.tensor.dot(x, x) + y[:, 0].sum() - x * y
env = theano.FunctionGraph([x, y], [z])
machine_ids = ["ankaa", "arroyitos"]
prob, X, S, Cmax = make_ilp(env, machine_ids, dummy_compute_cost,
dummy_comm_cost, dummy_ability, 100)
prob.solve()
assert Cmax.value() == 5
def test_compute_schedule():
x = theano.tensor.matrix('x')
y = theano.tensor.matrix('y')
z = theano.tensor.dot(x, x) + y[:,0].sum() - x*y
env = theano.FunctionGraph([x, y], [z])
machine_ids = ["ankaa", "arroyitos"]
sched = compute_schedule(*make_ilp(env, machine_ids, dummy_compute_cost,
dummy_comm_cost, dummy_ability, 100))
# nodes are the jobs
assert env.apply_nodes == set([job for job, (time, id) in sched])
times = [time for job, (time, id) in sched]
# jobs are sorted by time
assert list(sorted(times)) == times
# the machine ids match what we put in
assert all(id in machine_ids for job, (time, id) in sched)
def test_compute_schedule():
x = theano.tensor.matrix('x')
y = theano.tensor.matrix('y')
z = theano.tensor.dot(x, x) + y[:, 0].sum() - x * y
env = theano.FunctionGraph([x, y], [z])
machine_ids = ["ankaa", "arroyitos"]
sched = compute_schedule(*make_ilp(env, machine_ids, dummy_compute_cost,
dummy_comm_cost, dummy_ability, 100))
# nodes are the jobs
assert env.apply_nodes == set([job for job, (time, id) in sched])
times = [time for job, (time, id) in sched]
# jobs are sorted by time
assert list(sorted(times)) == times
# the machine ids match what we put in
assert all(id in machine_ids for job, (time, id) in sched)
