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61 lines
2.1 KiB
61 lines
2.1 KiB
# Ultralytics YOLO 🚀, GPL-3.0 license
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from ultralytics.yolo.utils import LOGGER, TESTS_RUNNING
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from ultralytics.yolo.utils.torch_utils import get_flops, get_num_params
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try:
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import clearml
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from clearml import Task
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assert clearml.__version__ # verify package is not directory
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assert not TESTS_RUNNING # do not log pytest
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except (ImportError, AssertionError, AttributeError):
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clearml = None
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def _log_images(imgs_dict, group='', step=0):
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task = Task.current_task()
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if task:
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for k, v in imgs_dict.items():
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task.get_logger().report_image(group, k, step, v)
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def on_pretrain_routine_start(trainer):
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try:
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task = Task.init(project_name=trainer.args.project or 'YOLOv8',
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task_name=trainer.args.name,
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tags=['YOLOv8'],
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output_uri=True,
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reuse_last_task_id=False,
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auto_connect_frameworks={'pytorch': False})
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task.connect(vars(trainer.args), name='General')
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except Exception as e:
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LOGGER.warning(f'WARNING ⚠️ ClearML installed but not initialized correctly, not logging this run. {e}')
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def on_train_epoch_end(trainer):
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if trainer.epoch == 1:
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_log_images({f.stem: str(f) for f in trainer.save_dir.glob('train_batch*.jpg')}, 'Mosaic', trainer.epoch)
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def on_fit_epoch_end(trainer):
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task = Task.current_task()
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if task and trainer.epoch == 0:
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model_info = {
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'model/parameters': get_num_params(trainer.model),
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'model/GFLOPs': round(get_flops(trainer.model), 3),
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'model/speed(ms)': round(trainer.validator.speed['inference'], 3)}
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task.connect(model_info, name='Model')
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def on_train_end(trainer):
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task = Task.current_task()
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if task:
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task.update_output_model(model_path=str(trainer.best), model_name=trainer.args.name, auto_delete_file=False)
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callbacks = {
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'on_pretrain_routine_start': on_pretrain_routine_start,
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'on_train_epoch_end': on_train_epoch_end,
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'on_fit_epoch_end': on_fit_epoch_end,
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'on_train_end': on_train_end} if clearml else {}
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