ClearMLVisBackend¶
- class mmengine.visualization.ClearMLVisBackend(save_dir=None, init_kwargs=None, artifact_suffix=('.py', '.pth'))[source]¶
Clearml visualization backend class. It requires clearml to be installed.
Examples
>>> from mmengine.visualization import ClearMLVisBackend >>> from mmengine import Config >>> import numpy as np >>> vis_backend = ClearMLVisBackend(save_dir='temp_dir') >>> img = np.random.randint(0, 256, size=(10, 10, 3)) >>> vis_backend.add_image('img.png', img) >>> vis_backend.add_scalar('mAP', 0.6) >>> vis_backend.add_scalars({'loss': 0.1,'acc':0.8}) >>> cfg = Config(dict(a=1, b=dict(b1=[0, 1]))) >>> vis_backend.add_config(cfg)
- Parameters:
save_dir (str, optional) – Useless parameter. Just for interface unification. Defaults to None.
init_kwargs (dict, optional) – A dict contains the arguments of
clearml.Task.init
. See taskinit for more details. Defaults to Noneartifact_suffix (Tuple[str] or str) – The artifact suffix. Defaults to (‘.py’, ‘pth’).
- add_config(config, **kwargs)[source]¶
Record the config to clearml.
- Parameters:
config (Config) – The Config object
- Return type:
None
- add_scalar(name, value, step=0, **kwargs)[source]¶
Record the scalar data to clearml.
- Parameters:
name (str) – The scalar identifier.
value (int, float, torch.Tensor, np.ndarray) – Value to save.
step (int) – Global step value to record. Defaults to 0.
- Return type:
None
- add_scalars(scalar_dict, step=0, file_path=None, **kwargs)[source]¶
Record the scalar’s data to clearml.
- property experiment¶
Return clearml object.