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[Auto] Fix estimators #1619

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merged 5 commits into from
Feb 20, 2021
Merged

[Auto] Fix estimators #1619

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75bd14d
fix logdir after refit
zhreshold Feb 18, 2021
e053176
final fit trial
zhreshold Feb 20, 2021
653ddbe
fix
zhreshold Feb 20, 2021
a8897cc
fix
zhreshold Feb 20, 2021
75d6628
fix tests
zhreshold Feb 20, 2021
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1 change: 1 addition & 0 deletions gluoncv/auto/estimators/base_estimator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -155,6 +155,7 @@ def fit(self, train_data, val_data=None, train_size=0.9, random_state=None,
return self._fit(train_data, val_data, time_limit=time_limit) if not resume \
else self._resume_fit(train_data, val_data, time_limit=time_limit)

os.makedirs(self._logdir, exist_ok=True)
if val_data is None:
assert 0 <= train_size <= 1.0
if random_state:
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8 changes: 6 additions & 2 deletions gluoncv/auto/tasks/image_classification.py
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Expand Up @@ -121,8 +121,12 @@ def _train_image_classification(args, reporter):
if best_checkpoint:
estimator = estimator_cls.load(best_checkpoint)
if estimator is None:
result.update({'traceback': 'timeout'})
else:
if wall_clock_tick < tic:
result.update({'traceback': 'timeout'})
else:
# unknown error yet, try reproduce it
final_fit = False
if not final_fit:
# create independent log_dir for each trial
trial_log_dir = os.path.join(log_dir, '.trial_{}'.format(task_id))
args['log_dir'] = trial_log_dir
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8 changes: 6 additions & 2 deletions gluoncv/auto/tasks/object_detection.py
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Original file line number Diff line number Diff line change
Expand Up @@ -127,8 +127,12 @@ def _train_object_detection(args, reporter):
if best_checkpoint:
estimator = estimator_cls.load(best_checkpoint)
if estimator is None:
result.update({'traceback': 'timeout'})
else:
if wall_clock_tick < tic:
result.update({'traceback': 'timeout'})
else:
# unknown error
final_fit = False
if not final_fit:
# create independent log_dir for each trial
trial_log_dir = os.path.join(log_dir, '.trial_{}'.format(task_id))
args['log_dir'] = trial_log_dir
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16 changes: 8 additions & 8 deletions tests/auto/test_auto_tasks.py
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Expand Up @@ -10,7 +10,7 @@

def test_image_classification():
from gluoncv.auto.tasks import ImageClassification
task = ImageClassification({'num_trials': 1, 'epochs': 1})
task = ImageClassification({'num_trials': 1, 'epochs': 1, 'batch_size': 8})
classifier = task.fit(IMAGE_CLASS_DATASET)
assert task.fit_summary().get('valid_acc', 0) > 0
test_result = classifier.predict(IMAGE_CLASS_TEST)
Expand All @@ -19,39 +19,39 @@ def test_image_classification_custom_net():
from gluoncv.auto.tasks import ImageClassification
from gluoncv.model_zoo import get_model
net = get_model('resnet18_v1')
task = ImageClassification({'num_trials': 1, 'epochs': 1, 'custom_net': net})
task = ImageClassification({'num_trials': 1, 'epochs': 1, 'custom_net': net, 'batch_size': 8})
classifier = task.fit(IMAGE_CLASS_DATASET)
assert task.fit_summary().get('valid_acc', 0) > 0
test_result = classifier.predict(IMAGE_CLASS_TEST)

def test_object_detection_estimator():
from gluoncv.auto.tasks import ObjectDetection
task = ObjectDetection({'num_trials': 1, 'epochs': 1})
task = ObjectDetection({'num_trials': 1, 'epochs': 1, 'batch_size': 4})
detector = task.fit(OBJECT_DETECTION_TRAIN)
assert task.fit_summary().get('valid_map', 0) > 0
test_result = detector.predict(OBJECT_DETECTION_TEST)

def test_object_detection_estimator_transfer():
from gluoncv.auto.tasks import ObjectDetection
task = ObjectDetection({'num_trials': 1, 'epochs': 1, 'transfer': ag.Categorical('yolo3_darknet53_coco', 'ssd_512_resnet50_v1_voc'), 'estimator': 'ssd'})
task = ObjectDetection({'num_trials': 1, 'epochs': 1, 'transfer': ag.Categorical('yolo3_darknet53_coco', 'ssd_512_resnet50_v1_voc'), 'estimator': 'ssd', 'batch_size': 4})
detector = task.fit(OBJECT_DETECTION_TRAIN)
assert task.fit_summary().get('valid_map', 0) > 0
test_result = detector.predict(OBJECT_DETECTION_TEST)

def test_time_out_image_classification():
time_limit = 30
time_limit = 15
from gluoncv.auto.tasks import ImageClassification
task = ImageClassification({'num_trials': 1, 'epochs': 50})
task = ImageClassification({'num_trials': 1, 'epochs': 10, 'batch_size': 8})

tic = time.time()
classifier = task.fit(IMAGE_CLASS_DATASET, time_limit=time_limit)
# check time_limit with a little bit overhead
assert (time.time() - tic) < time_limit + 180

def test_time_out_detection():
time_limit = 30
time_limit = 15
from gluoncv.auto.tasks import ObjectDetection
task = ObjectDetection({'num_trials': 1, 'epochs': 50, 'time_limits': time_limit})
task = ObjectDetection({'num_trials': 1, 'epochs': 5, 'time_limits': time_limit, 'batch_size': 4})
tic = time.time()
detector = task.fit(OBJECT_DETECTION_TRAIN)
# check time_limit with a little bit overhead
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