def test_custom_random_greedy():
eq, shapes = oe.helpers.rand_equation(10, 4, seed=42)
views = list(map(np.ones, shapes))
with pytest.raises(ValueError):
oe.RandomGreedy(minimize='something')
optimizer = oe.RandomGreedy(max_repeats=10, minimize='flops')
path, path_info = oe.contract_path(eq, *views, optimize=optimizer)
assert len(optimizer.costs) == 10
assert len(optimizer.sizes) == 10
assert path == optimizer.path
assert optimizer.best['flops'] == min(optimizer.costs)
assert path_info.largest_intermediate == optimizer.best['size']
assert path_info.opt_cost == optimizer.best['flops']
# check can change settings and run again
optimizer.temperature = 0.0
optimizer.max_repeats = 6
path, path_info = oe.contract_path(eq, *views, optimize=optimizer)
assert len(optimizer.costs) == 16
assert len(optimizer.sizes) == 16
assert path == optimizer.path
assert optimizer.best['size'] == min(optimizer.sizes)
assert path_info.largest_intermediate == optimizer.best['size']
assert path_info.opt_cost == optimizer.best['flops']
def test_custom_random_greedy():
eq, shapes = oe.helpers.rand_equation(10, 4, seed=42)
views = list(map(np.ones, shapes))
with pytest.raises(ValueError):
oe.RandomGreedy(minimize="something")
optimizer = oe.RandomGreedy(max_repeats=10, minimize="flops")
path, path_info = oe.contract_path(eq, *views, optimize=optimizer)
assert len(optimizer.costs) == 10
assert len(optimizer.sizes) == 10
assert path == optimizer.path
assert optimizer.best["flops"] == min(optimizer.costs)
assert path_info.largest_intermediate == optimizer.best["size"]
assert path_info.opt_cost == optimizer.best["flops"]
# check can change settings and run again
optimizer.temperature = 0.0
optimizer.max_repeats = 6
path, path_info = oe.contract_path(eq, *views, optimize=optimizer)
assert len(optimizer.costs) == 16
assert len(optimizer.sizes) == 16
assert path == optimizer.path
assert optimizer.best["size"] == min(optimizer.sizes)
assert path_info.largest_intermediate == optimizer.best["size"]
assert path_info.opt_cost == optimizer.best["flops"]
# check error if we try and reuse the optimizer on a different expression
eq, shapes = oe.helpers.rand_equation(10, 4, seed=41)
views = list(map(np.ones, shapes))
with pytest.raises(ValueError):
path, path_info = oe.contract_path(eq, *views, optimize=optimizer)
def test_parallel_random_greedy():
from concurrent.futures import ProcessPoolExecutor
pool = ProcessPoolExecutor(2)
eq, shapes = oe.helpers.rand_equation(10, 4, seed=42)
views = list(map(np.ones, shapes))
optimizer = oe.RandomGreedy(max_repeats=10, parallel=pool)
path, path_info = oe.contract_path(eq, *views, optimize=optimizer)
assert len(optimizer.costs) == 10
assert len(optimizer.sizes) == 10
assert path == optimizer.path
assert optimizer.parallel is pool
assert optimizer._executor is pool
assert optimizer.best["flops"] == min(optimizer.costs)
assert path_info.largest_intermediate == optimizer.best["size"]
assert path_info.opt_cost == optimizer.best["flops"]
# now switch to max time algorithm
optimizer.max_repeats = int(1e6)
optimizer.max_time = 0.2
optimizer.parallel = 2
path, path_info = oe.contract_path(eq, *views, optimize=optimizer)
assert len(optimizer.costs) > 10
assert len(optimizer.sizes) > 10
assert path == optimizer.path
assert optimizer.best["flops"] == min(optimizer.costs)
assert path_info.largest_intermediate == optimizer.best["size"]
assert path_info.opt_cost == optimizer.best["flops"]
optimizer.parallel = True
assert optimizer._executor is not None
assert optimizer._executor is not pool
are_done = [f.running() or f.done() for f in optimizer._futures]
assert all(are_done)
