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Add new @Retry() decorator (#7854)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Glenn Jocher 2024-01-27 20:07:31 +01:00 • committed by GitHub
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commit 1435f0e9de
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9 changed files with 372 additions and 269 deletions
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tests/test_engine.py
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@ -6,123 +6,123 @@ from ultralytics.engine.exporter import Exporter
from ultralytics.models.yolo import classify, detect, segment
from ultralytics.utils import ASSETS, DEFAULT_CFG, WEIGHTS_DIR
CFG_DET = 'yolov8n.yaml'
CFG_SEG = 'yolov8n-seg.yaml'
CFG_CLS = 'yolov8n-cls.yaml' # or 'squeezenet1_0'
CFG_DET = "yolov8n.yaml"
CFG_SEG = "yolov8n-seg.yaml"
CFG_CLS = "yolov8n-cls.yaml" # or 'squeezenet1_0'
CFG = get_cfg(DEFAULT_CFG)
MODEL = WEIGHTS_DIR / 'yolov8n'
MODEL = WEIGHTS_DIR / "yolov8n"
def test_func(*args): # noqa
"""Test function callback."""
print('callback test passed')
print("callback test passed")
def test_export():
"""Test model exporting functionality."""
exporter = Exporter()
exporter.add_callback('on_export_start', test_func)
assert test_func in exporter.callbacks['on_export_start'], 'callback test failed'
exporter.add_callback("on_export_start", test_func)
assert test_func in exporter.callbacks["on_export_start"], "callback test failed"
f = exporter(model=YOLO(CFG_DET).model)
YOLO(f)(ASSETS) # exported model inference
def test_detect():
"""Test object detection functionality."""
overrides = {'data': 'coco8.yaml', 'model': CFG_DET, 'imgsz': 32, 'epochs': 1, 'save': False}
CFG.data = 'coco8.yaml'
overrides = {"data": "coco8.yaml", "model": CFG_DET, "imgsz": 32, "epochs": 1, "save": False}
CFG.data = "coco8.yaml"
CFG.imgsz = 32
# Trainer
trainer = detect.DetectionTrainer(overrides=overrides)
trainer.add_callback('on_train_start', test_func)
assert test_func in trainer.callbacks['on_train_start'], 'callback test failed'
trainer.add_callback("on_train_start", test_func)
assert test_func in trainer.callbacks["on_train_start"], "callback test failed"
trainer.train()
# Validator
val = detect.DetectionValidator(args=CFG)
val.add_callback('on_val_start', test_func)
assert test_func in val.callbacks['on_val_start'], 'callback test failed'
val.add_callback("on_val_start", test_func)
assert test_func in val.callbacks["on_val_start"], "callback test failed"
val(model=trainer.best) # validate best.pt
# Predictor
pred = detect.DetectionPredictor(overrides={'imgsz': [64, 64]})
pred.add_callback('on_predict_start', test_func)
assert test_func in pred.callbacks['on_predict_start'], 'callback test failed'
result = pred(source=ASSETS, model=f'{MODEL}.pt')
assert len(result), 'predictor test failed'
pred = detect.DetectionPredictor(overrides={"imgsz": [64, 64]})
pred.add_callback("on_predict_start", test_func)
assert test_func in pred.callbacks["on_predict_start"], "callback test failed"
result = pred(source=ASSETS, model=f"{MODEL}.pt")
assert len(result), "predictor test failed"
overrides['resume'] = trainer.last
overrides["resume"] = trainer.last
trainer = detect.DetectionTrainer(overrides=overrides)
try:
trainer.train()
except Exception as e:
print(f'Expected exception caught: {e}')
print(f"Expected exception caught: {e}")
return
Exception('Resume test failed!')
Exception("Resume test failed!")
def test_segment():
"""Test image segmentation functionality."""
overrides = {'data': 'coco8-seg.yaml', 'model': CFG_SEG, 'imgsz': 32, 'epochs': 1, 'save': False}
CFG.data = 'coco8-seg.yaml'
overrides = {"data": "coco8-seg.yaml", "model": CFG_SEG, "imgsz": 32, "epochs": 1, "save": False}
CFG.data = "coco8-seg.yaml"
CFG.imgsz = 32
# YOLO(CFG_SEG).train(**overrides) # works
# Trainer
trainer = segment.SegmentationTrainer(overrides=overrides)
trainer.add_callback('on_train_start', test_func)
assert test_func in trainer.callbacks['on_train_start'], 'callback test failed'
trainer.add_callback("on_train_start", test_func)
assert test_func in trainer.callbacks["on_train_start"], "callback test failed"
trainer.train()
# Validator
val = segment.SegmentationValidator(args=CFG)
val.add_callback('on_val_start', test_func)
assert test_func in val.callbacks['on_val_start'], 'callback test failed'
val.add_callback("on_val_start", test_func)
assert test_func in val.callbacks["on_val_start"], "callback test failed"
val(model=trainer.best) # validate best.pt
# Predictor
pred = segment.SegmentationPredictor(overrides={'imgsz': [64, 64]})
pred.add_callback('on_predict_start', test_func)
assert test_func in pred.callbacks['on_predict_start'], 'callback test failed'
result = pred(source=ASSETS, model=f'{MODEL}-seg.pt')
assert len(result), 'predictor test failed'
pred = segment.SegmentationPredictor(overrides={"imgsz": [64, 64]})
pred.add_callback("on_predict_start", test_func)
assert test_func in pred.callbacks["on_predict_start"], "callback test failed"
result = pred(source=ASSETS, model=f"{MODEL}-seg.pt")
assert len(result), "predictor test failed"
# Test resume
overrides['resume'] = trainer.last
overrides["resume"] = trainer.last
trainer = segment.SegmentationTrainer(overrides=overrides)
try:
trainer.train()
except Exception as e:
print(f'Expected exception caught: {e}')
print(f"Expected exception caught: {e}")
return
Exception('Resume test failed!')
Exception("Resume test failed!")
def test_classify():
"""Test image classification functionality."""
overrides = {'data': 'imagenet10', 'model': CFG_CLS, 'imgsz': 32, 'epochs': 1, 'save': False}
CFG.data = 'imagenet10'
overrides = {"data": "imagenet10", "model": CFG_CLS, "imgsz": 32, "epochs": 1, "save": False}
CFG.data = "imagenet10"
CFG.imgsz = 32
# YOLO(CFG_SEG).train(**overrides) # works
# Trainer
trainer = classify.ClassificationTrainer(overrides=overrides)
trainer.add_callback('on_train_start', test_func)
assert test_func in trainer.callbacks['on_train_start'], 'callback test failed'
trainer.add_callback("on_train_start", test_func)
assert test_func in trainer.callbacks["on_train_start"], "callback test failed"
trainer.train()
# Validator
val = classify.ClassificationValidator(args=CFG)
val.add_callback('on_val_start', test_func)
assert test_func in val.callbacks['on_val_start'], 'callback test failed'
val.add_callback("on_val_start", test_func)
assert test_func in val.callbacks["on_val_start"], "callback test failed"
val(model=trainer.best)
# Predictor
pred = classify.ClassificationPredictor(overrides={'imgsz': [64, 64]})
pred.add_callback('on_predict_start', test_func)
assert test_func in pred.callbacks['on_predict_start'], 'callback test failed'
pred = classify.ClassificationPredictor(overrides={"imgsz": [64, 64]})
pred.add_callback("on_predict_start", test_func)
assert test_func in pred.callbacks["on_predict_start"], "callback test failed"
result = pred(source=ASSETS, model=trainer.best)
assert len(result), 'predictor test failed'
assert len(result), "predictor test failed"