def test_meta_schedule_task_scheduler_single():
num_trials_per_iter = 3
max_trials_per_task = 10
sch_fn = ScheduleFn(sch_fn=_schedule_matmul)
replay = ReplayTrace(num_trials_per_iter, max_trials_per_task)
task = TuneContext(
MatmulModule,
target=tvm.target.Target("llvm"),
space_generator=sch_fn,
search_strategy=replay,
task_name="Test",
rand_state=42,
)
database = DummyDatabase()
round_robin = RoundRobin(
[task],
[1.0],
DummyBuilder(),
DummyRunner(),
database,
measure_callbacks=[measure_callback.AddToDatabase()],
max_trials=max_trials_per_task,
)
round_robin.tune()
assert len(database) == max_trials_per_task
def test_meta_schedule_measure_callback_fail():
@derived_object
class FailingMeasureCallback(PyMeasureCallback):
def apply(
self,
task_scheduler: TaskScheduler,
task_id: int,
measure_candidates: List[MeasureCandidate],
builds: List[BuilderResult],
results: List[RunnerResult],
) -> None:
raise ValueError("test")
measure_callback = FailingMeasureCallback()
with pytest.raises(ValueError, match="test"):
measure_callback.apply(
RoundRobin([], [],
DummyBuilder(),
DummyRunner(),
DummyDatabase(),
max_trials=1),
0,
[MeasureCandidate(Schedule(Matmul), None)],
[BuilderResult("test_build", None)],
[RunnerResult([1.0, 2.1], None)],
)
def test_meta_schedule_measure_callback():
@derived_object
class FancyMeasureCallback(PyMeasureCallback):
def apply(
self,
task_scheduler: TaskScheduler,
task_id: int,
measure_candidates: List[MeasureCandidate],
builds: List[BuilderResult],
results: List[RunnerResult],
) -> None:
assert len(measure_candidates) == 1
assert_structural_equal(measure_candidates[0].sch.mod, Matmul)
assert (len(builds) == 1 and builds[0].error_msg is None
and builds[0].artifact_path == "test_build")
assert (len(results) == 1 and results[0].error_msg is None
and len(results[0].run_secs) == 2)
measure_callback = FancyMeasureCallback()
measure_callback.apply(
RoundRobin([], [],
DummyBuilder(),
DummyRunner(),
DummyDatabase(),
max_trials=1),
0,
[MeasureCandidate(Schedule(Matmul), None)],
[BuilderResult("test_build", None)],
[RunnerResult([1.0, 2.1], None)],
)
def test_meta_schedule_task_scheduler_NIE(): # pylint: disable=invalid-name
@derived_object
class NIETaskScheduler(PyTaskScheduler):
pass
with pytest.raises(
TVMError,
match="PyTaskScheduler's NextTaskId method not implemented!"):
scheduler = NIETaskScheduler([], DummyBuilder(), DummyRunner(),
DummyDatabase(), 1)
scheduler.next_task_id()
def test_meta_schedule_task_scheduler_override_next_task_id_only(): # pylint: disable=invalid-name
num_trials_per_iter = 6
max_trials_per_task = 101
tasks = [
TuneContext(
MatmulModule,
target=tvm.target.Target("llvm"),
space_generator=ScheduleFn(sch_fn=_schedule_matmul),
search_strategy=ReplayTrace(num_trials_per_iter,
max_trials_per_task),
task_name="Matmul",
rand_state=42,
),
TuneContext(
MatmulReluModule,
target=tvm.target.Target("llvm"),
space_generator=ScheduleFn(sch_fn=_schedule_matmul),
search_strategy=ReplayTrace(num_trials_per_iter,
max_trials_per_task),
task_name="MatmulRelu",
rand_state=0xDEADBEEF,
),
TuneContext(
BatchMatmulModule,
target=tvm.target.Target("llvm"),
space_generator=ScheduleFn(sch_fn=_schedule_batch_matmul),
search_strategy=ReplayTrace(num_trials_per_iter,
max_trials_per_task),
task_name="BatchMatmul",
rand_state=0x114514,
),
]
database = DummyDatabase()
scheduler = MyTaskScheduler(
tasks,
DummyBuilder(),
DummyRunner(),
database,
measure_callbacks=[
measure_callback.AddToDatabase(),
],
max_trials=max_trials_per_task * len(tasks),
)
scheduler.tune()
assert len(database) == max_trials_per_task * len(tasks)
for task in tasks:
assert (len(
database.get_top_k(
database.commit_workload(task.mod),
100000,
)) == max_trials_per_task)
def test_meta_schedule_task_scheduler_multiple():
num_trials_per_iter = 6
max_trials_per_task = 101
tasks = [
TuneContext(
MatmulModule,
target=tvm.target.Target("llvm"),
space_generator=ScheduleFn(sch_fn=_schedule_matmul),
search_strategy=ReplayTrace(num_trials_per_iter,
max_trials_per_task),
task_name="Matmul",
rand_state=42,
),
TuneContext(
MatmulReluModule,
target=tvm.target.Target("llvm"),
space_generator=ScheduleFn(sch_fn=_schedule_matmul),
search_strategy=ReplayTrace(num_trials_per_iter,
max_trials_per_task),
task_name="MatmulRelu",
rand_state=0xDEADBEEF,
),
TuneContext(
BatchMatmulModule,
target=tvm.target.Target("llvm"),
space_generator=ScheduleFn(sch_fn=_schedule_batch_matmul),
search_strategy=ReplayTrace(num_trials_per_iter,
max_trials_per_task),
task_name="BatchMatmul",
rand_state=0x114514,
),
]
database = DummyDatabase()
round_robin = RoundRobin(
tasks,
[1.0],
DummyBuilder(),
DummyRunner(),
database,
measure_callbacks=[measure_callback.AddToDatabase()],
max_trials=max_trials_per_task * len(tasks),
)
round_robin.tune()
assert len(database) == max_trials_per_task * len(tasks)
for task in tasks:
assert (len(
database.get_top_k(
database.commit_workload(task.mod),
100000,
)) == max_trials_per_task)
def test_meta_schedule_task_scheduler_avoid_cyclic(): # pylint: disable=invalid-name
database = DummyDatabase()
scheduler = MyTaskScheduler(
[],
DummyBuilder(),
DummyRunner(),
database,
measure_callbacks=[
measure_callback.AddToDatabase(),
],
)
test = weakref.ref(scheduler) # test if it can be destructed successfully
del scheduler
assert test() is None
