def test_dataflow_timer_basic_profiler():
true_dataflow_time_per_ele = 0.1
true_max_epochs = 1
true_num_iters = 2
def dummy_data_loader(data):
while True:
for d in data:
time.sleep(true_dataflow_time_per_ele)
yield d
dummy_data = range(true_num_iters)
profiler = BasicTimeProfiler()
dummy_trainer = Engine(_do_nothing_update_fn)
profiler.attach(dummy_trainer)
dummy_trainer.run(dummy_data_loader(dummy_data), max_epochs=true_max_epochs, epoch_length=true_num_iters)
results = profiler.get_results()
dataflow_results = results["dataflow_stats"]
assert dataflow_results["min/index"][0] == approx(true_dataflow_time_per_ele, abs=1e-1)
assert dataflow_results["max/index"][0] == approx(true_dataflow_time_per_ele, abs=1e-1)
assert dataflow_results["mean"] == approx(true_dataflow_time_per_ele, abs=1e-1)
assert dataflow_results["std"] == approx(0.0, abs=1e-1)
assert dataflow_results["total"] == approx(true_num_iters * true_dataflow_time_per_ele, abs=1e-1)
def test_event_handler_get_batch_completed():
true_event_handler_time = 0.1
true_max_epochs = 1
true_num_iters = 2
profiler = BasicTimeProfiler()
dummy_trainer = Engine(_do_nothing_update_fn)
profiler.attach(dummy_trainer)
@dummy_trainer.on(Events.GET_BATCH_COMPLETED)
def delay_get_batch_completed(engine):
time.sleep(true_event_handler_time)
dummy_trainer.run(range(true_num_iters), max_epochs=true_max_epochs)
results = profiler.get_results()
event_results = results["event_handlers_stats"]["GET_BATCH_COMPLETED"]
assert event_results["min/index"][0] == approx(true_event_handler_time,
abs=1e-1)
assert event_results["max/index"][0] == approx(true_event_handler_time,
abs=1e-1)
assert event_results["mean"] == approx(true_event_handler_time, abs=1e-1)
assert event_results["std"] == approx(0.0, abs=1e-1)
assert event_results["total"] == approx(true_max_epochs * true_num_iters *
true_event_handler_time,
abs=1e-1)
def test_event_handler_iteration_started_basic_profiler():
true_event_handler_time = 0.1
true_max_epochs = 1
true_num_iters = 2
profiler = BasicTimeProfiler()
dummy_trainer = Engine(_do_nothing_update_fn)
profiler.attach(dummy_trainer)
@dummy_trainer.on(Events.ITERATION_STARTED)
def delay_iter_start(engine):
time.sleep(true_event_handler_time)
dummy_trainer.run(range(true_num_iters), max_epochs=true_max_epochs)
results = profiler.get_results()
event_results = results["event_handlers_stats"]["ITERATION_STARTED"]
assert event_results["min/index"][0] == approx(true_event_handler_time,
abs=1e-1)
assert event_results["max/index"][0] == approx(true_event_handler_time,
abs=1e-1)
assert event_results["mean"] == approx(true_event_handler_time, abs=1e-1)
assert event_results["std"] == approx(0.0, abs=1e-1)
assert event_results["total"] == approx(true_max_epochs * true_num_iters *
true_event_handler_time,
abs=1e-1)
def test_print_results_basic_profiler(capsys):
true_max_epochs = 1
true_num_iters = 5
profiler = BasicTimeProfiler()
dummy_trainer = get_prepared_engine_for_basic_profiler(true_event_handler_time=0.0125)
profiler.attach(dummy_trainer)
dummy_trainer.run(range(true_num_iters), max_epochs=true_max_epochs)
BasicTimeProfiler.print_results(profiler.get_results())
captured = capsys.readouterr()
out = captured.out
assert "BasicTimeProfiler._" not in out
assert "nan" not in out
def test_profilers_wrong_inputs():
profiler = BasicTimeProfiler()
with pytest.raises(TypeError, match=r"Argument engine should be ignite.engine.Engine"):
profiler.attach(None)
with pytest.raises(RuntimeError, match=r"Need pandas to write results as files"):
with patch.dict("sys.modules", {"pandas": None}):
profiler.write_results("")
profiler = HandlersTimeProfiler()
with pytest.raises(TypeError, match=r"Argument engine should be ignite.engine.Engine"):
profiler.attach(None)
with pytest.raises(RuntimeError, match=r"Need pandas to write results as files"):
with patch.dict("sys.modules", {"pandas": None}):
profiler.write_results("")
def test_event_handler_total_time_basic_profiler():
true_event_handler_time = 0.125
true_max_epochs = 1
true_num_iters = 1
profiler = BasicTimeProfiler()
dummy_trainer = Engine(_do_nothing_update_fn)
profiler.attach(dummy_trainer)
@dummy_trainer.on(Events.STARTED)
def delay_start(engine):
time.sleep(true_event_handler_time)
@dummy_trainer.on(Events.COMPLETED)
def delay_complete(engine):
time.sleep(true_event_handler_time)
@dummy_trainer.on(Events.EPOCH_STARTED)
def delay_epoch_start(engine):
time.sleep(true_event_handler_time)
@dummy_trainer.on(Events.EPOCH_COMPLETED)
def delay_epoch_complete(engine):
time.sleep(true_event_handler_time)
@dummy_trainer.on(Events.ITERATION_STARTED)
def delay_iter_start(engine):
time.sleep(true_event_handler_time)
@dummy_trainer.on(Events.ITERATION_COMPLETED)
def delay_iter_complete(engine):
time.sleep(true_event_handler_time)
@dummy_trainer.on(Events.GET_BATCH_STARTED)
def delay_get_batch_started(engine):
time.sleep(true_event_handler_time)
@dummy_trainer.on(Events.GET_BATCH_COMPLETED)
def delay_get_batch_completed(engine):
time.sleep(true_event_handler_time)
dummy_trainer.run(range(true_num_iters), max_epochs=true_max_epochs)
results = profiler.get_results()
event_results = results["event_handlers_stats"]
assert event_results["total_time"].item() == approx(
true_event_handler_time * 8, abs=1e-1)
def test_event_handler_completed_basic_profiler():
true_event_handler_time = 0.1
true_max_epochs = 2
true_num_iters = 2
profiler = BasicTimeProfiler()
dummy_trainer = Engine(_do_nothing_update_fn)
profiler.attach(dummy_trainer)
@dummy_trainer.on(Events.COMPLETED)
def delay_complete(engine):
time.sleep(true_event_handler_time)
dummy_trainer.run(range(true_num_iters), max_epochs=true_max_epochs)
results = profiler.get_results()
event_results = results["event_handlers_stats"]["COMPLETED"]
assert event_results["total"] == approx(true_event_handler_time, abs=1e-1)
def test_get_intermediate_results_during_run_basic_profiler(capsys):
true_event_handler_time = 0.0645
true_max_epochs = 2
true_num_iters = 5
profiler = BasicTimeProfiler()
dummy_trainer = get_prepared_engine_for_basic_profiler(true_event_handler_time)
profiler.attach(dummy_trainer)
@dummy_trainer.on(Events.ITERATION_COMPLETED(every=3))
def log_results(_):
results = profiler.get_results()
profiler.print_results(results)
captured = capsys.readouterr()
out = captured.out
assert "BasicTimeProfiler._" not in out
assert "nan" not in out
assert " min/index: (0.0, " not in out, out
dummy_trainer.run(range(true_num_iters), max_epochs=true_max_epochs)
def test_processing_timer_basic_profiler():
true_processing_time = 0.1
true_max_epochs = 2
true_num_iters = 2
def train_updater(engine, batch):
time.sleep(true_processing_time)
profiler = BasicTimeProfiler()
dummy_trainer = Engine(train_updater)
profiler.attach(dummy_trainer)
dummy_trainer.run(range(true_num_iters), max_epochs=true_max_epochs)
results = profiler.get_results()
processing_results = results["processing_stats"]
assert processing_results["min/index"][0] == approx(true_processing_time, abs=1e-1)
assert processing_results["max/index"][0] == approx(true_processing_time, abs=1e-1)
assert processing_results["mean"] == approx(true_processing_time, abs=1e-1)
assert processing_results["std"] == approx(0.0, abs=1e-1)
assert processing_results["total"] == approx(true_max_epochs * true_num_iters * true_processing_time, abs=1e-1)
def test_write_results_basic_profiler(dirname):
true_event_handler_time = 0.125
true_max_epochs = 3
true_num_iters = 2
profiler = BasicTimeProfiler()
dummy_trainer = get_prepared_engine_for_basic_profiler(true_event_handler_time)
profiler.attach(dummy_trainer)
dummy_trainer.run(range(true_num_iters), max_epochs=true_max_epochs)
fp = dirname / "test_log.csv"
profiler.write_results(fp)
assert fp.is_file()
file_length = 0
with open(fp) as f:
for _ in f:
file_length += 1
assert file_length == (true_max_epochs * true_num_iters) + 1